Indian Patents. 260364:SYSTEM AND METHOD FOR PROCESSING A REGION OF INTEREST RELATIVE TO A PREDETERMINED EVENT

Title of Invention	SYSTEM AND METHOD FOR PROCESSING A REGION OF INTEREST RELATIVE TO A PREDETERMINED EVENT
Abstract	A system and method are disclosed for analyzing a three-dimensional (3-D) region of interest relative to a predetermined event. The system and method are particularly useful as analytical, diagnostic and interpretive tools for any type of scientific data. Figure 2 is the representative figure.

Full Text	Field of the Invention The present invention relates to a system and method for analyzing a three-dimensional region of interest relative to a predetennmed event He system and method may be used to locate and image t preferred feature of the region of interest otherwise indistingoishable from the event. In die applied sciences, various fields of study require the analysis of two-dimensional (2-D) or three-dimensional (3-D) volume data sets wherein each data set may have multiple attributes representing different physical properties. An attribute, sometimes referred to as a data value, represents a particular physical property of an object within a defined 2-D or 3-D space. A dam value may, for instance, be an 8-byte data word which includes 256 possible values, The location of an attribute is represented by (i, y, data value) or (x, y, z, data value). If die attnbate represents pressure at & particular location, then die attribute location may be expressed as (x, y, z, pressure). In die medical field, a computerized axial topography (CAT) scanner or mapetkreK>rianceifflagtag(MIU)dew^ some specific area of a person's body, typically representing the cooldinate aid a determined attribute, Normally, each attribute within a predetermined location most be imaged separate and apart from another attribute. For example, one attribute representing temperature at a predetermined location is typically imaged separate from another attribute representing pressure at the same location. Thus, the diagnosis of a particular condition sased upon these attributes is limited by the ability to display a single attribute at a predetermined location. In the field of earth sciences, seismic sounding is used for exploring the subterranean geology of an earth formation. An underground explosion excites seismic waves, similar to low-frequency sound waves that travel below the surface of the earth and are detected by seismographs. The seismographs record the time of arrival cf seismic waves, both direct and reflected waves. Knowing the time and place of the explosion the time of travel of the waves through the interior can be calculated and used to measure the velocity of the waves in the interior. A similar technique can be used for offshore oil and gas exploration. In offshore exploration, a ship tows a sound source and underwater hydrophones. Low frequency, (e.g., SO Hz) sound waves are generated by, for example, a pneumatic device that works lite a balloon burst The sounds bounce off rock layers below the sea floor and are picked op by the hydrophones. In either application, subsurface sedimentary structures that trap oil, such as faults and domes are mapped by the reflective waves. The date is collected and processed to produce 3-D volume data sea A 3-D volume data set is made up of "voxels" or volume elements having x, y, z coordinates. Each voxel represents a numeric data value {attribute) associated with some measured or calculated physical property at a particular location. Examples of geological data values include amplitude, phase, frequency, and semblance. Different data values are stored in different 3-D volume data sets, wherein each 3-D volume data set represents a different dam value. In order to analyze certain geological structures referred to as "events," information from different 3-D volume data sets must be separately imaged in order to analyze the event Certain techniques have been developed in thia field, howewr, for imaging multiple 3-D volume data sets in a single display. One example includes the technique published in The Leading Edge coiled "Constructing Faults from Seed Picks by Voxel Tracking" by Jack Lees. This technique combines two 3-D volume data sets in a single display, thereby restricting each original 256-value attribute to 128 values of the full 256-value range. Another conventional method combines the display of two 3-D volume data sets, containing two different attributes, by making some data values more transparent than others. This technique becomes untenable when more than two attributes are combined, Other, more advanced, techniques used to combine two different 3-D volume date sets in the same image are illustrated in U.S. patent application No. 09/936,780 and No. 101528,781 assigned to Magic Earth, Inc. and incorporated herein by reference. The 780 application describes a technique for combining a first 3-D volume data set representing a first attribute and a second 3-D volume data set representing a second attribute in a single enhanced 3-D volume data set by comparing each of the first and second attribute data values with a preselected data value range or criteria. For each data value where the criteria are met, a first selected data value is inserted at a position corresponding with the respective data value in the enhanced 3-D volume data set For each data value where the criteria are not met, a second selected data value is inserted at a position corresponding with the respective data value in the enhanced 3-D volume data set. The first selected data value may be related to the first attribute and the second selected data value may be related to the second attribute. The resulting image is an enhanced 3-D volume data set comprising a combination of the original first 3-D volume data set and the second 3-D volume data set. The '780 application also describes a technique for displaying an enhanced 3-D volume data set related to one of a plurality of attributes by selecting attribute data values within a predetermined data value range and inserting a preselected data value at a position corresponding with the data value in the enhanced 3-D volume data set when the data value is within the data value range, or inserting another preselected data value at a position corresponding with the respective data valae in the enhanced 3-D volume data set when the data value is not within the data value range. The resulting image is an enhanced 3-D volume data set comprising a combination of the original enhanced 3-D volume data set data values, the preselected data values and/or me another preselected data values. In either technique, the image may be further enhanced by the application of an autopicking technique that utilizes an initial seed pick to autopick all connected data values having the same data value as the seed pick. This technique is particularly useful for determining the extent of an event related to a physical phenomenon. The '781 application describes another technique for corendering multiple attributes in real time thus, forming a combined image of die attributes. The combined image is visually Intuitive in that it distinguishes certain features of an object that are otherwise substantially indistinguishable in their natural environment Another technique used to analyze certain geological events, like faults and otter formation anomalies, is illustrated in U.S. patent application Ho. 09/936,682 assigned to Magic Earth, Inc. and incorporated herein by reference. The '682 application describes a technique for imaging and/or tracking a physical phenomena, such as a geological fault, by selecting control points from various locations correspondhig to a 3-D data volume set to define a first spline curve and a second spline curve, A surface may be interfolated between the first spline curve and the second spline curve that is representative of the physical phenomena. This technique may also be used to define other surfaces and boundaries of geological formations. Another technique used to analyze similar geological events is illustrated in US, patent application 09/119,635 assigned to Magic Karth, Inc. and incorporated herein by reference. The '635 application describes a technique for imaging and manipulating the image of a 3-D sampling probe, in real time, that is a subset of a larger 3-D volume data set As the 3-D sampling probe moves through the larger 3-D volume data set, the imaging on the surfaces of the 3-D sampling probe is redrawn "on the fly" so that the image is perceived to change in real time with movement of the 3-D sampling probe thus, enabling a more intuitive analysis of the geological events represented by the 3-D volume data set. The techniques thus described may be used to locate an image certain attributes representative of geological events like gas-producing regions found in sand and sandstone. Gas-producing regions, however, may be difficult to distinguish from other geological regions comprising limestone and dolomite. In other words, attributes representing gas-producing sands may be masked or otherwise obscured by attributes representing limestone or dolomite. Therefore, there is a need to effectively locate and distinguish attributes representing gas-producing sands from other related geological regions comprising limestone and dolomite. SUMMARY OF THE INVENTION The present invention provides an effective system and method for analyzing a 3-D region of interest relative to a predetermined event when therc is a condation between attributes representing a preferred feature of the region of interest and attributes representing the event. The method generally comprises the steps of defining the region of interest relative to a boundary of tte event. A first attribute and a second attribute are selected representing the region of interest. A first attribute volume and a second attribute volume are calculated for the region of interest The first attribute volume and the second attribute volume each comprise a plurality of voxels, wherein each voxel is defined by a set of x,y,z coordinates and a data value. A first set of voxels is selected from the first attribute volume that has a data value within a first attribute data value range. Hie first set of voxels represents a preferred feature of toe region of interest, A second set of voxels is selected from the second attribute volume that has a data value within a second attribute data value range. The second set of voxels also represents the preferred feature. The first set of voxels and the second set of voxels may be imaged representing the preferred feature. The system for performing the method of the present invention may comprise a program storage device readable by a machine. The storage device may embody ft program of instructions executable by the machine for performing the method of the present invention. BRIBT DESCRIPTION OF THE DRAWINGS The patent or application file contains at least one drawing executed in color. •t Copies of mis patent or patent application publication with color drawing(s) mil be provided by the Office upon request and payment of the necessary fee, The invention will now be described with reference to the accompanying drawings, in which lite elements are referenced with like reference numerals, and in which: FIG. 1 is a block diagram illustrating one embodiment of a software program for Implementing the present invention, FIG, 2 is a flow diagram illustrating one embodiment of a method for implementing the present invention, FIG, 3 is a flow diagram illustrating step 206 in FIG. 2. PIG. 4 is a color drawing illustrating seismic data attributes representing a geological event and a boundary of the event. FIG. S is a color drawing illustrating seismic data attributes representing a region of interest and a preferred feature of the region of interest DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention may be implemented using hardware, software or a combination thereof, and may be implemented in a computer system or other processing system. The following description applies the present invention to various seismic data attributes, which are contained within a specified space or volume Bach volume comprises voxel data represented by x, y, z coordinates and a data value. Each data value is associated with a particular seismic data attribute at a specified location (x, y, z). The present invention, therefore, may employ one or more of the hardware and software system components required to display and analyze the volume as described in the '634, '780 and 781 applications. In addition to the foregoing hardware and/or software system components that may be employed, the present invention may be implemented using current high performance graphics and personal computer comniodity hardware in order to mure real tune performance. Examples of available hardware include graphics cards like GeForce® marketed by NVIDIA® and 2.40hz x86 instruction set computer processors manufactured by Intel or AMD. One embodiment of a software or program stractwre for inpfementing the present invention is shown in FIG. 1. At the base of program structure 100 is an operating system 102. Suitable operating systems may include, for example, UNIX or LINUX® operating systems, Windows NT®, and other operating systems generally known in the art. Menu and interface software 104 overlays operating system 102. Menu and interface software 104 are used to provide various menus and windows to facilitate interaction with the user, and to obtain user input and instructions. Menu and interface software 104 may include, for example, Microsoft Windows, X Free 86, MOTIF, and other menu and interface software generally known in the art A basic graphics library 106 overlays menu and interface software 104. Basic graphics library 106 is an application programming interface (API) for 3-D computer graphics. The functions performed by basic graphics library 106 include, for example, geometric and raster primitives, ROB A or color index mode, display list or immediate mode, viewing and modeling transformations, lighting and shading, hidden surface removal, alpha blending (tramlBcency), anti-aliasing, texture mapping, atmospheric effects (fog, smoke, haze), feedback and selection, stencil planes, and accumulation buffer. A particularly useful basic graphics library 106 is OpenGL31, marketed by Silicon Graphics, Inc. ("SGI"), The OpenGL® API is a multi-platform jndustyy standard that is hardware, window, and operating system independent. OpenGL® is designed to be callable from C, Of, FORTRAN* Ada and Java programming lanpiges. OpenGL® performs each of the functions listed above for basic graphics library 106. Some commands in OpenGL® specify geometric objects to be drawn, and others control how the objects are handled. All elements of the OpenGL® states, even the contents of the texture memory and the frame buffer, can be obtained by a client application using OpenGL* OpenGL® and the client application may operate on the same or different machines because OpenGL* is network transparent OpenGL® is described in more detail in the OpenGL® Programming Guide (ISBN: 0-201-63274-8) and ttie OpenGL* Reference Manual (ISBN: 0-201-632764), both of which are incorporated herein by reference. Visoal simulation graphics library 108 overlays the basic graphics library 106, Visual simulation graphics library 108 is an API for creating real-time, multi-processed 3-D visual simulation graphics applications. Visual simulation graphics library 108 provides functions that bundle together graphics library state control functions such as lighting, materials, texture, and transparency. These fonctions track state and the creation of display lists that can be rendered later. A particularly useful visual simulation graphics library IDS is OpenGL Performer®, which is available from SGI. OpenGL Performer® supports the OpenGL graphics library discussed above. OpenGL Performer® includes two main libraries (libpf and libpr) and four associated libraries (Hbpfdu, libpldb, libpfui, and libpfntil), The basis of OpenGL Performer® is the performance rendering library libpr, a low-level library providing high speed rendering functions based on GeoSets and graphics state control wing GcoStates. QeoSets are collections of drawable geometry that group same-type graphics primitives (e.g., triangles or quads) into one data object The GeoSet contains no geometry itself, only pointers to data arrays and index arrays. Because all the primitives in a GeoSet are of the same type and have the same attributes, rendering of most databases is performed at maximum hardware speed. GcoStates provide graphics state definitions (e.g., texture or material) for GeoSets. Layered above libpr is libpf, a real-time visual simulation environment providing a liigfl-perfoiinaace multi-process database rendering system that optimizes use of multiprocessing hardware. The database utility library, libpfdu, provides functions for defining both geometric and appearance attributes of 3-D objects, shares state and materials, and generates triangle strips from independent polygonal input The database library libpfdb uses the facilities of libpfdu, libpf and libpr to import database files in a number of industry standard database formats. The libpfui is a user interface library that provides building blocks for writing manipulation components for user interfaces (C and GM- programming languages). Finally, the libpfutil is the utility library that provides routines for implementing tasks and graphical user interface (GUI) tools. An application program which uses OpenGL Performer* and OpenGL® API typically perfbrras the following steps in preparing for real-time 3-0 visual sirralation: 1. Initialize OpenGL Performer; 2. Specify number of graphics pipelines, choose the imilttprocessiag configuration, and specify hardware mode as needed; 3. Initialize chosen multiprocessing mode; 4. Initialize frame rate and set frame-extend policy; 5. Create, configure, and open windows as required; and 6. Create and configure display channels as required. Once the application program has created a graphical rendering environment by carrying oat steps 1 through 6 above, then the application program typically iterates through the following main simulation loop once per frame: 7. Compute dynamics, update model matrices, etc.; 8. Delay until the next frame time; 9. Perform latency critical viewpoint updates; and 10. Draw a frame. Alternatively, Open Scene Graph9 can be used as the visual simulation graphics library 108. Open Scene Graph operates in the same manner as OpenGL Performer®, providing programming tools written in C/C+4 for a large variety of computer platforms. Open Scene Graph* is based on OpenGL0 and is available through www.opcnscenegraph.com. A region analysis program 110 representing the present invention overlays visual simulation graphics library 108. In a manner generally well known in the art, program 110 interfaces with, and utilizes the functions carried out by, the visual simulation graphics library 108, basic graphics library 106, menu and interface software 104, and operating system 102. Program 110 is preferably written in an object oriented programming language to allow the creation and use of objects and object functionality. One preferred object oriented programming language is C++. to this particular embodiment, program 110 stores the 3-D volume data set in a manner generally well known in the art. Par example, the format for a particular data volume may include two parts: a volume header followed by the body of date that is as long as the size of the data set, The volume header typically includes information in a prescribed sequence, such as the file path (location) of the data set, size, dimensions in the x, y, and z directions, annotations for the x, y, and z axes, annotations for the data value, etc. The body of data is a binary sequence of bytes and may include one or mom bytes per data value. For example, the first byte is the data value at volume location (0,0,0); the second byte is the data value at volume location (1,0,0); and the third byte is the data value at volume location (2,0,0)- When the x dimension is exhausted, then the y dimension and the z dimension are incremented, respectively. This embodiment is not limited in any way to a particular data format The program 110 facilitates input from a user to identify one or more 3-D volume data sets to use for analysis and imaging. When a plurality of data volumes are used, the data value for each of die plurality of data volumes represents a different physical parameter or attribute for the same geographic space. By way of example, a plurality of data volumes could include a geology volume, a temperature volume, and a water-saturation volume. The voxels in the geology volume can be expressed in the form (x,y,z, seismic amplitude). The voxels jn the temperature volume can be expressed in. the form (x,y,z, °C). The voxels in the water-saturation volume can be expressed in the form (x,y,z, %saturation). The physical or geographic space defined by the voxels in each of these volumes is the same. However, for any specific spatial location (xo,yo,2o)> the seismic amplitude would be contained in the geology volume, the temperature in the temperature volams, and the water-saniration in the water-saturation volume. The operation of program 110 is described in reference to FIGs, 2 through 5. Referring now to FIG. 2, a method 200 is illustrated for analyzing a 3-D region of interest relative to a predetermined event. In step 202, a first attribute and a second attribute sue selected from the available attributes using the GUI tools (menu/interface software 104) described in reference to 116.1. The first attribute and the second attribute represent a geological region of interest where gas-bearing sands may be found. The first attribute and the second attribute each represent an acoustic signal comprising instantaneous amplitude and instantaneous frequency, respectively. Although there are other available well-known attributes such as amplitude, frequency, phase, instantaneous phase, semblance, and coherence, instantaneous amplitude and instantaneous frequency are the preferred attributes representing the presence of sand and/or sandstone in the region of interest. In step 204, an event boundary is defined to provide a reference point for the region of interest- Because there ® a known correlation between sand or sandstone and limestone or dolomite, these formation properties are the preferred or predetermined event. Referring to FIG. 3, the process of defining the event boundary (step 204) as a reference point is more fully described. In step 302, a thin) attribute and a fourth attribute are selected from the available attributes using the GUI tools (menu/interface software 104) described in reference to FIG. 1. The third attribute and the fourth attribute represent die predetermined event, that is limestone or dolomite. The third attribute and fourth attribute each represent an acoustic signal comprising amplitude and phase, respectively. Although other well-known available attributes may be selected, in combination, or alone, amplitude and phase are the preferred attributes representing the presence of limestone or dolomite. In step 304, a third attribute volume is calculated using the third attribute and a fourth attribute volume is calculated using the fourth attribute. Hie third attribute volume 402 and the fourth attribute volume 404 are illustrated in FIG. 4. Although the third attribute volume 402 and the fourth attribute volume 404 me illustrated side-by-side in FIG. 4, they have the same spatial coordinates but a different data value. The third attribute volume 402 and the fourth attribute volume 404 may be calculated using conventional shading/opacity (texture mapping) techniques, however, may also be calculated using volume rendering techniques generally well known in the art. In order to display seismic data in the manner thus described, voxel data is read front memory and converted into a specified color representing a specified texture. Textures are tiled in a 256 pixel by 256 pixel images. For larger volumes, many tiles exist on a single plane or surface. This process is commonly referred to by those skilled in the art as sampling, and is coordinated among multiple CPUs on a per tile basis. This technique, and others employed herein, are more fully described and illustrated in the 780, 781, '682, and '635 applications. In step 306, a third attribute data value range is set. the third attribute data value range is pfcforably measured on a voxel scale between atwuit 0 and about 255, however, may be between about -128 and about +127. The third attribute data value range is preferably set between about 50 and about 127, Other data value ranges may be preferred, depending on the application or selected attributes. . In step 308, a fourth attribute data value range is set. Hie fourtii attribute data value range is also measured on a voxel scale between about 0 and about 255, however, may be between about -128 and +127. The fourth attribute data value range is preferably set between about -5 and about +5, Other data value ranges may be preferred, depending on the application or selected attributes. In step 310, a third set of voxels are selected from the third attribute volume 402 that have a data value within die third attribute data value range. In step 312, a fourth set of voxels are selected from the fourth attribute volume 404 that have a data value within the fourth attribute data value range. In step 314, the third set of voxels and the fourth set of voxel* are imaged and represent the event boundary 406 illustrated in FIG. 4. The event boundary 40$ represents the boundary or horizon of the limestone or dolomite that appears as a blue layer of voxels at the bottom of the third attribute volume 402 and be fourth attribute volume 404. The techniques described to die '780 application may be utilised to image the third set of voxels and the fourth set of voxels. One technique involves combining the third set of voxels and die fourth set of voxels to form a combined set of voxels representing the event boundary 406. Each voxel in the combined set of voxels is assigned a new data value that is the same for each voxel hi the combined set of voxels and is within a combined data value range between about 0 and about 127, measured on a voxel scale between about 0 and about 255. A voxel may then be selected from the combined set of voxels that represents a seed voxel. From th« seed voxel, all other voxels from the combined set of voxels that are connected to the seed voxel and have the same data value may be autopicked and displayed to a user. Alternatively, a voxel from at least one of the third set of voxels and the fourth set of voxels may be selected that represents a seed voxel. Voxels from the third set of voxels and the fourth set of voxels that are connected to tbe seed voxel and have the same data value may be autopicked and displayed to a user. Once the event boundary 406 is defined, the geological region of interest relative to the event boundary 406 may be determined as illustrated in step 206. The presence of sand or sandstone is often found within aboat 300 feet above or below the limestone or dolomite event boundary 406. In FIG. 5, the region of interest 506 is illustrated comprising sand or sandstone below the event boundary 406. In step 208, a first attribute volume 502 is calculated using ihe first attribute and a second attribute volume 504 is calculated using the second attribute. The first attribute volume 502 and the second attribute volume 504 are illustrated in FIG. 5. Although the first attribute volume 502 and tbe second attribute volume 504 are illustrated side-by-side in FIG. 5, they have the same spatial coordinates, but a different data value. Hie first attribute volume 502 and the second attribute volume 504 may be calculated in the same manner described in reference to calculating the third attribute volume 402 and the fourth attribute volume 404, In step 210, a first attribute data value range is set based on a voxel scale between about 0 and about 255, however, may be between about -128 and 4-127. The first attribute data value range is preferably set between about 10 and about 140, based upon experimental results revealing the potential for gas-bearing sands where instantaneous amplitude voxels have a data value within this range. Although this is the preferred data value range for the first attribute, other data value ranges between about 37 and about 110; between about 37 and about 120; and between about 37 and about 130 may be used when the first attribute represents instantaneous amplitade, Other data value ranges may be preferred, depending on the application or selected attribute. In step 212, a second attribute data value range is set based on a voxel scab between about 0 and aboot 255, however, may be between about -128 and -f 177. The second attribute data value range is preferably set between about € and about 48, based upon experimental results revealing the potential for gas-bearing sands where instantaneous frequency voxels have a data value within this range. Although this is the preferred data value range for the second attribute, other data value ranges between about 2 and about 36; and between about 3 and about 37, may be used when the second attribute represents instantaneous frequency. Other data value ranges may be preferred, depending on the application or selected attribute. In step 214, a first set of voxels is selected from die first attribute volume 502 that have a data value within the first attribute data value range. The fust set of voxels represent a preferred feature of the region of interest that comprises gas-bearing sands. In step 216, a second set of voxels is selected from the second attribute volume 504 that have a date value wittin the second attribute date value range, The second set of voxels also represent the preferred feature of the region of interest In step 218, the first set of voxels and the second set of voxels representing the preferred feature (gas-bearing Sands) are imaged. The techniques described in reference to imaging the third set of voxeis and the fourth set of voxels in step 314 may be used here as well. The image of a portion of the voxels representing the gas-bearing sands is illustrated in FIG. 5 as a plurality of yellow points tot reside in a plane containing the tegion of interest The techniques thus described are particttMy mefnl as analytical, diagnostic and interpretive took for any type of scientific data, including seismic data, and may be applied to the discovery and development of energy resources. Those skilled in die art will therefore, appreciate that the foregoing techniques may be applied to the analysis of other types of attributes representing a regicn of interest and is not limited to geological formations and/or seismic data attributes, Consequently, the foregoing description of the invention is illustrative and various details of the illustraled construction or combinations of features of the various dements and/or steps may be made without departing from the spirit of the invention. We Claim: 1. A computer implemented method for processing a three dimensional region of interest relative to a predetermined event, the method comprising the steps of: defining a boundary of the event with a GUI tool and a voxel scale; defining the region of interest relative to the boundary of the event; selecting a first attribute and a second attribute with a GUI tool, the first attribute and second attribute representing the region of interest; calculating a first attribute volume and a second attribute volume for the region of interest, the first attribute volume and the second attribute volume each comprising a plurality of voxels, each voxel being defined by a set of x, y, z coordinates and a data value; selecting a first set of voxels from the first attribute volume that have a data value within a first attribute data value range set on the voxel scale, the first set of voxels representing a preferred feature of the region of interest; selecting a second set of voxels from the second attribute volume that have a data value within a second attribute data value range set on the voxel scale, the second set of voxels representing the preferred feature; and displaying with multiple processing units the first set of voxels and the second set of voxels. 2. The method as claimed in Claim 1, wherein the preferred feature comprises at least one of sand or sandstone. 3. The method as claimed in Claim 2, wherein the first attribute represents an acoustic signal comprising instantaneous amplitude and the second attribute represents an acoustic signal comprising instantaneous frequency. 4. The method as claimed in of Claim 3, wherein the region of interest is defined as within about 300 feet from the boundary of the event. 5. The method as claimed in Claim 3, wherein the first attribute data value range is between about 10 and about 140, and the second attribute data value range is between about 0 and about 48, the first attribute data value range and the second attribute data value range being measured on the voxel scale between about 0 and about 255. 6. The method as claimed in Claim 5, wherein the first attribute data value range is between about 37 and about 110, and the second attribute data value range is between about 2 and about 36. 7. The method as claimed in claim 5, wherein the first attribute data value range is between about 37 and about 120, and the second attribute data value range is between about 2 and about 36. 8. The method as claimed in claim 5, wherein the first attribute data value range is between about 37 and about 130, and the second attribute data value range is between about 3 and about 37. 9. The method as claimed in Claim 1, wherein defining the boundary of the event comprises the steps of: selecting a third attribute with the GUI tool, the third attribute representing the event; calculating a third attribute volume for the event, the third attribute volume comprising a plurality of voxels, each voxel being defined by a set of x, y, z coordinates and a data value; selecting a third set of voxels from the third attribute volume that have a data value within a third attribute data value range based on the voxel scale, the third set of voxels representing the boundary of the event; and imaging the third set of voxels. 10. The method as claimed in Claim 9, wherein the event is a geological formation comprising at least one of dolomite or limestone. 11. The method as claimed in Claim 10, wherein the third attribute represents an acoustic signal comprising at least one of amplitude, phase, frequency, instantaneous amplitude, instantaneous phase, instantaneous frequency, coherence or semblance. 12. The method as claimed in Claim 11, wherein the third attribute data value range is between at least one of about 50 and about 127 and about- 5 and about +5, the third attribute data value range being measured on the voxel scale between at least one of about 0 and about 255 and about-128 and about +127. 13. The method as claimed in Claim 12, wherein imaging the third set of voxels comprises the steps of: selecting a voxel from the third set of voxels, the selected voxel representing a seed voxel; autopicking voxels from the third set of voxels that are connected to the seed voxel and have the same data value; and displaying the autopicked voxels from the third set of voxels to a user. 14. The method as claimed in Claim 12, wherein imaging the third set of voxels comprises the steps of: assigning a new data value to each voxel in the third set of voxels, the new data value having the same data value within a new data value range between about 0 and about 127 on the voxel scale; selecting a voxel from the third set of voxels, the selected voxel representing a seed voxel; autopicking voxels from the third set of voxels that are connected to the seed voxel and have the same data value; and displaying the autopicked voxels from the third set of voxels to a user. 15. The method as claimed in claim 1, wherein imaging the first set of voxels and the second set of voxels comprises the steps of: combining the first set of voxels and the second set of voxels to form a combined set of voxels representing the preferred feature, each voxel in the combined set of voxels being assigned a new data value, the new data value having the same data value within a combined data value range between about 0 and about 127 on the vcoxel scale; selecting a voxel from the combined set of voxels, the selected voxel representing a seed voxel; autopicking voxels from the combined set of voxels that are connected to the seed voxel and have the same data value; and displaying the autopicked voxels from the combined set of voxels to a user. 16. The method as claimed in claim 1, wherein imaging the first set of voxels and the second set of voxels comprises the steps of: selecting a voxel from at least one of the first set of voxels and the second set of voxels, the selected voxel representing a seed voxel; autopicking voxels from the first set of voxels that are connected to the seed voxel and have the same data value; autopicking voxels from the second set of voxels that are connected to the seed voxel and have the same data value; and displaying the autopicked voxels from the first set of voxels and the second set of voxels to a user. 17. A system for processing a three dimensional region of interest relative to a predetermined event, said system comprising: a first system for defining a boundary of the event; a second system for defining the region of interest relative to the boundary of the event. a GUI tool for selecting a first attribute and a second attribute, the first attribute and second attribute representing the region of interest; means for calculating a first attribute volume and a second attribute volume for the region of interest, the first attribute volume and the second attribute volume each comprising a plurality of voxels, each voxel being defined by a set of x, y, z coordinates and a data value; a voxel scale for defining a data value within a first attribute data value range in the first attribute volume from which a first set of voxels is selected, the first set of voxels representing a preferred feature of the region of interest; a voxel scale for defining a data value within a second attribute data value range in the second attribute volume from which a second set of voxels is selected, the second set of voxels representing the preferred feature; and multiple processing units for displaying the first set of voxels and the second set of voxels. 18. The system as claimed in claim 17, wherein the region of interest is a geological formation and the preferred feature comprises at least one of sand or sandstone. 19. The system as claimed in claim 18, wherein the first attribute represents an acoustic signal comprising instantaneous amplitude and the second attribute represents an acoustic signal comprising instantaneous frequency. 20. The system as claimed in claim 19, wherein the region of interest is defined as within about 300 feet from the boundary of the event. 21. The system as claimed in claim 19, wherein the first attribute data value range is between about 10 and about 140, and the second attribute data value range is between about 0 and about 48, the first attribute data value range and the second attribute data value range being measured on the voxel scale between about 0 and about 255. 22. The system as claimed in claim 21, wherein the first attribute data value range is between about 37 and about 110, and the second attribute data value range is between about 2 and about 36. 23. The system as claimed in claim 21, wherein the first attribute data value range is between about 37 and about 120, and the second attribute data value range is between about 2 and about 36. 24. The system as claimed in claim 21, wherein the first attribute data value range is between about 37 and about 130, and the second attribute data value range is between about 3 and about 37. 25. The system as claimed in claim 17, wherein the system for defining the boundary of the event comprises: a GUI tool for selecting a third attribute, the third attribute representing the event; means for calculating a third attribute volume for the event, the third attribute volume comprising a plurality of voxels, each voxel being defined by a set of x, y, z coordinates and a data value; a voxel scale for defining a data value within a third attribute data value range in the third attribute volume from which a third set of voxels is selected, the third set of voxels representing the boundary of the event; and multiple processing units for displaying the third set of voxels. 26. The system as claimed in claim 25, wherein the event is a geological formation comprising at least one of dolomite or limestone. 27. The system as claimed in claim 26, wherein the third attribute represents an acoustic signal comprising at least one of amplitude, phase, frequency, instantaneous amplitude, instantaneous phase, instantaneous frequency, coherence or semblance. 28. The system as claimed in claim 27, wherein the third attribute data value range is between at least one of about 50 and about 127 and about- 5 and about +5, the third attribute data value range being measured on the voxel scale between at least one of about 0 and about 255 and about-128 and about +127. 29. The system as claimed in claim 28, wherein imaging the third set of voxels comprises: selecting a voxel from the third set of voxels with a GUI tool, the selected voxel representing a seed voxel; autopicking voxels from the third set of voxels that are connected to the seed voxel and have the same data value; and displaying the autopicked voxels from the third set of voxels to a user. 30. The system as claimed in claim 28, wherein imaging the third set of voxels comprises: assigning a new data value to each voxel in the third set of voxels with a voxel scale, the new data value having the same data value within a new data value range between about 0 and about 127; selecting a voxel from the third set of voxels with a voxel scale, the selected voxel representing a seed voxel ; autopicking voxels from the third set of voxels that are connected to the seed voxel and have the same data value; and displaying the autopicked voxels from the third set of voxels to a user. 31. The system as claimed in claim 17, wherein imaging the first set of voxels and the second set of voxels comprises the steps of: combining the first set of voxels and the second set of voxels to form a combined set of voxels representing the preferred feature, each voxel in the combined set of voxels being assigned a new data value, the new data value having the same data value within a combined data value range between about 0 and about 127; selecting a voxel from the combined set of voxels, the selected voxel representing a seed voxel; autopicking voxels from the combined set of voxels that are connected to the seed voxel and have the same data value; and displaying the autopicked voxels from the combined set of voxels to a user. 32. The system as claimed in claim 17, wherein imaging the first set of voxels and the second set of voxels comprises the steps of: selecting a voxel from at least one of the first set of voxels and the second set of voxels, the selected voxel representing a seed voxel; autopicking voxels from the first set of voxels that are connected to the seed voxel and have the same data value; autopicking voxels from the second set of voxels that are connected to the seed voxel and have the same data value; and displaying the autopicked voxels from the first set of voxels and the second set of voxels to a user.

Full Text

Field of the Invention
The present invention relates to a system and method for analyzing a three-dimensional region of interest relative to a predetennmed event He system and method may be used to locate and image t preferred feature of the region of interest otherwise indistingoishable from the event.
In die applied sciences, various fields of study require the analysis of two-dimensional (2-D) or three-dimensional (3-D) volume data sets wherein each data set may have multiple attributes representing different physical properties. An attribute, sometimes referred to as a data value, represents a particular physical property of an object within a defined 2-D or 3-D space. A dam value may, for instance, be an 8-byte data word which includes 256 possible values, The location of an attribute is represented by (i, y, data value) or (x, y, z, data value). If die attnbate represents pressure at & particular location, then die attribute location may be expressed as (x, y, z, pressure).
In die medical field, a computerized axial topography (CAT) scanner or mapetkreK>rianceifflagtag(MIU)dew^
some specific area of a person's body, typically representing the cooldinate aid a determined attribute, Normally, each attribute within a predetermined location most be imaged separate and apart from another attribute. For example, one attribute representing temperature at a predetermined location is typically imaged separate from another attribute representing

pressure at the same location. Thus, the diagnosis of a particular condition sased upon these attributes is limited by the ability to display a single attribute at a predetermined location.
In the field of earth sciences, seismic sounding is used for exploring the subterranean geology of an earth formation. An underground explosion excites seismic waves, similar to low-frequency sound waves that travel below the surface of the earth and are detected by seismographs. The seismographs record the time of arrival cf seismic waves, both direct and reflected waves. Knowing the time and place of the explosion the time of travel of the waves through the interior can be calculated and used to measure the velocity of the waves in the interior. A similar technique can be used for offshore oil and gas exploration. In offshore exploration, a ship tows a sound source and underwater hydrophones. Low frequency, (e.g., SO Hz) sound waves are generated by, for example, a pneumatic device that works lite a balloon burst The sounds bounce off rock layers below the sea floor and are picked op by the hydrophones. In either application, subsurface sedimentary structures that trap oil, such as faults and domes are mapped by the reflective waves.
The date is collected and processed to produce 3-D volume data sea A 3-D volume data set is made up of "voxels" or volume elements having x, y, z coordinates. Each voxel represents a numeric data value {attribute) associated with some measured or calculated physical property at a particular location. Examples of geological data values include amplitude, phase, frequency, and semblance. Different data values are stored in different 3-D volume data sets, wherein each 3-D volume data set represents a different dam value. In order to analyze certain geological structures referred to as "events," information from different 3-D volume data sets must be separately imaged in order to analyze the event

Certain techniques have been developed in thia field, howewr, for imaging multiple 3-D volume data sets in a single display. One example includes the technique published in The Leading Edge coiled "Constructing Faults from Seed Picks by Voxel Tracking" by Jack Lees. This technique combines two 3-D volume data sets in a single display, thereby restricting each original 256-value attribute to 128 values of the full 256-value range. Another conventional method combines the display of two 3-D volume data sets, containing two different attributes, by making some data values more transparent than others. This technique becomes untenable when more than two attributes are combined,
Other, more advanced, techniques used to combine two different 3-D volume date sets in the same image are illustrated in U.S. patent application No. 09/936,780 and No. 101528,781 assigned to Magic Earth, Inc. and incorporated herein by reference.
The *780 application describes a technique for combining a first 3-D volume data set representing a first attribute and a second 3-D volume data set representing a second attribute in a single enhanced 3-D volume data set by comparing each of the first and second attribute data values with a preselected data value range or criteria. For each data value where the criteria are met, a first selected data value is inserted at a position corresponding with the respective data value in the enhanced 3-D volume data set For each data value where the criteria are not met, a second selected data value is inserted at a position corresponding with the respective data value in the enhanced 3-D volume data set. The first selected data value may be related to the first attribute and the second selected data value may be related to the second attribute. The resulting image is an enhanced 3-D volume data set comprising a combination of the original first 3-D volume data set and the second 3-D volume data set. The '780 application also describes a technique for displaying an enhanced

3-D volume data set related to one of a plurality of attributes by selecting attribute data values within a predetermined data value range and inserting a preselected data value at a position corresponding with the data value in the enhanced 3-D volume data set when the data value is within the data value range, or inserting another preselected data value at a position corresponding with the respective data valae in the enhanced 3-D volume data set when the data value is not within the data value range. The resulting image is an enhanced 3-D volume data set comprising a combination of the original enhanced 3-D volume data set data values, the preselected data values and/or me another preselected data values. In either technique, the image may be further enhanced by the application of an autopicking technique that utilizes an initial seed pick to autopick all connected data values having the same data value as the seed pick. This technique is particularly useful for determining the extent of an event related to a physical phenomenon.
The '781 application describes another technique for corendering multiple attributes in real time thus, forming a combined image of die attributes. The combined image is visually Intuitive in that it distinguishes certain features of an object that are otherwise substantially indistinguishable in their natural environment
Another technique used to analyze certain geological events, like faults and otter formation anomalies, is illustrated in U.S. patent application Ho. 09/936,682 assigned to Magic Earth, Inc. and incorporated herein by reference. The '682 application describes a technique for imaging and/or tracking a physical phenomena, such as a geological fault, by selecting control points from various locations correspondhig to a 3-D data volume set to define a first spline curve and a second spline curve, A surface may be interfolated between the first spline curve and the second spline curve that is representative of the physical

phenomena. This technique may also be used to define other surfaces and boundaries of geological formations.
Another technique used to analyze similar geological events is illustrated in US, patent application 09/119,635 assigned to Magic Karth, Inc. and incorporated herein by reference. The '635 application describes a technique for imaging and manipulating the image of a 3-D sampling probe, in real time, that is a subset of a larger 3-D volume data set As the 3-D sampling probe moves through the larger 3-D volume data set, the imaging on the surfaces of the 3-D sampling probe is redrawn "on the fly" so that the image is perceived to change in real time with movement of the 3-D sampling probe thus, enabling a more intuitive analysis of the geological events represented by the 3-D volume data set.
The techniques thus described may be used to locate an image certain attributes representative of geological events like gas-producing regions found in sand and sandstone. Gas-producing regions, however, may be difficult to distinguish from other geological regions comprising limestone and dolomite. In other words, attributes representing gas-producing sands may be masked or otherwise obscured by attributes representing limestone or dolomite. Therefore, there is a need to effectively locate and distinguish attributes representing gas-producing sands from other related geological regions comprising limestone and dolomite.
SUMMARY OF THE INVENTION
The present invention provides an effective system and method for analyzing a 3-D region of interest relative to a predetermined event when therc is a condation between

attributes representing a preferred feature of the region of interest and attributes representing
the event.
The method generally comprises the steps of defining the region of interest relative to a boundary of tte event. A first attribute and a second attribute are selected representing the region of interest. A first attribute volume and a second attribute volume are calculated for the region of interest The first attribute volume and the second attribute volume each comprise a plurality of voxels, wherein each voxel is defined by a set of x,y,z coordinates and a data value. A first set of voxels is selected from the first attribute volume that has a data value within a first attribute data value range. Hie first set of voxels represents a preferred feature of toe region of interest, A second set of voxels is selected from the second attribute volume that has a data value within a second attribute data value range. The second set of voxels also represents the preferred feature. The first set of voxels and the second set of voxels may be imaged representing the preferred feature.
The system for performing the method of the present invention may comprise a program storage device readable by a machine. The storage device may embody ft program of instructions executable by the machine for performing the method of the present invention.
BRIBT DESCRIPTION OF THE DRAWINGS
The patent or application file contains at least one drawing executed in color.
•t Copies of mis patent or patent application publication with color drawing(s) mil be provided
by the Office upon request and payment of the necessary fee,
The invention will now be described with reference to the accompanying drawings, in which lite elements are referenced with like reference numerals, and in which:

FIG. 1 is a block diagram illustrating one embodiment of a software program for Implementing the present invention,
FIG, 2 is a flow diagram illustrating one embodiment of a method for implementing the present invention,
FIG, 3 is a flow diagram illustrating step 206 in FIG. 2.
PIG. 4 is a color drawing illustrating seismic data attributes representing a geological event and a boundary of the event.
FIG. S is a color drawing illustrating seismic data attributes representing a region of interest and a preferred feature of the region of interest
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
The present invention may be implemented using hardware, software or a combination thereof, and may be implemented in a computer system or other processing system. The following description applies the present invention to various seismic data attributes, which are contained within a specified space or volume Bach volume comprises voxel data represented by x, y, z coordinates and a data value. Each data value is associated with a particular seismic data attribute at a specified location (x, y, z). The present invention, therefore, may employ one or more of the hardware and software system components required to display and analyze the volume as described in the '634, '780 and 781 applications.

In addition to the foregoing hardware and/or software system components that may be employed, the present invention may be implemented using current high performance graphics and personal computer comniodity hardware in order to mure real tune performance. Examples of available hardware include graphics cards like GeForce® marketed by NVIDIA® and 2.40hz x86 instruction set computer processors manufactured by Intel* or AMD*.
One embodiment of a software or program stractwre for inpfementing the present invention is shown in FIG. 1. At the base of program structure 100 is an operating system 102. Suitable operating systems may include, for example, UNIX* or LINUX® operating systems, Windows NT®, and other operating systems generally known in the art.
Menu and interface software 104 overlays operating system 102. Menu and interface software 104 are used to provide various menus and windows to facilitate interaction with the user, and to obtain user input and instructions. Menu and interface software 104 may include, for example, Microsoft Windows*, X Free 86*, MOTIF*, and other menu and interface software generally known in the art
A basic graphics library 106 overlays menu and interface software 104. Basic graphics library 106 is an application programming interface (API) for 3-D computer graphics. The functions performed by basic graphics library 106 include, for example, geometric and raster primitives, ROB A or color index mode, display list or immediate mode, viewing and modeling transformations, lighting and shading, hidden surface removal, alpha blending (tramlBcency), anti-aliasing, texture mapping, atmospheric effects (fog, smoke, haze), feedback and selection, stencil planes, and accumulation buffer.

A particularly useful basic graphics library 106 is OpenGL31, marketed by Silicon Graphics, Inc. ("SGI*"), The OpenGL® API is a multi-platform jndustyy standard that is hardware, window, and operating system independent. OpenGL® is designed to be callable from C, Of, FORTRAN* Ada and Java programming lanpiges. OpenGL® performs each of the functions listed above for basic graphics library 106. Some commands in OpenGL® specify geometric objects to be drawn, and others control how the objects are handled. All elements of the OpenGL® states, even the contents of the texture memory and the frame buffer, can be obtained by a client application using OpenGL* OpenGL® and the client application may operate on the same or different machines because OpenGL* is network transparent OpenGL® is described in more detail in the OpenGL® Programming Guide (ISBN: 0-201-63274-8) and ttie OpenGL* Reference Manual (ISBN: 0-201-632764), both of which are incorporated herein by reference.
Visoal simulation graphics library 108 overlays the basic graphics library 106, Visual simulation graphics library 108 is an API for creating real-time, multi-processed 3-D visual simulation graphics applications. Visual simulation graphics library 108 provides functions that bundle together graphics library state control functions such as lighting, materials, texture, and transparency. These fonctions track state and the creation of display lists that can be rendered later.
A particularly useful visual simulation graphics library IDS is OpenGL Performer®, which is available from SGI*. OpenGL Performer® supports the OpenGL* graphics library discussed above. OpenGL Performer® includes two main libraries (libpf and libpr) and four associated libraries (Hbpfdu, libpldb, libpfui, and libpfntil),

The basis of OpenGL Performer® is the performance rendering library libpr, a low-level library providing high speed rendering functions based on GeoSets and graphics state control wing GcoStates. QeoSets are collections of drawable geometry that group same-type graphics primitives (e.g., triangles or quads) into one data object The GeoSet contains no geometry itself, only pointers to data arrays and index arrays. Because all the primitives in a GeoSet are of the same type and have the same attributes, rendering of most databases is performed at maximum hardware speed. GcoStates provide graphics state definitions (e.g., texture or material) for GeoSets.
Layered above libpr is libpf, a real-time visual simulation environment providing a liigfl-perfoiinaace multi-process database rendering system that optimizes use of multiprocessing hardware. The database utility library, libpfdu, provides functions for defining both geometric and appearance attributes of 3-D objects, shares state and materials, and generates triangle strips from independent polygonal input The database library libpfdb uses the facilities of libpfdu, libpf and libpr to import database files in a number of industry standard database formats. The libpfui is a user interface library that provides building blocks for writing manipulation components for user interfaces (C and GM- programming languages). Finally, the libpfutil is the utility library that provides routines for implementing tasks and graphical user interface (GUI) tools.
An application program which uses OpenGL Performer* and OpenGL® API typically perfbrras the following steps in preparing for real-time 3-0 visual sirralation:
1. Initialize OpenGL Performer*;
2. Specify number of graphics pipelines, choose the imilttprocessiag
configuration, and specify hardware mode as needed;

3. Initialize chosen multiprocessing mode;
4. Initialize frame rate and set frame-extend policy;
5. Create, configure, and open windows as required; and
6. Create and configure display channels as required.
Once the application program has created a graphical rendering environment by carrying oat steps 1 through 6 above, then the application program typically iterates through the following main simulation loop once per frame:
7. Compute dynamics, update model matrices, etc.;
8. Delay until the next frame time;
9. Perform latency critical viewpoint updates; and
10. Draw a frame.
Alternatively, Open Scene Graph9 can be used as the visual simulation graphics library 108. Open Scene Graph* operates in the same manner as OpenGL Performer®, providing programming tools written in C/C+4 for a large variety of computer platforms. Open Scene Graph* is based on OpenGL0 and is available through www.opcnscenegraph.com.
A region analysis program 110 representing the present invention overlays visual simulation graphics library 108. In a manner generally well known in the art, program 110 interfaces with, and utilizes the functions carried out by, the visual simulation graphics library 108, basic graphics library 106, menu and interface software 104, and operating system 102. Program 110 is preferably written in an object oriented programming language

to allow the creation and use of objects and object functionality. One preferred object oriented programming language is C++.
to this particular embodiment, program 110 stores the 3-D volume data set in a manner generally well known in the art. Par example, the format for a particular data volume may include two parts: a volume header followed by the body of date that is as long as the size of the data set, The volume header typically includes information in a prescribed sequence, such as the file path (location) of the data set, size, dimensions in the x, y, and z directions, annotations for the x, y, and z axes, annotations for the data value, etc. The body of data is a binary sequence of bytes and may include one or mom bytes per data value. For example, the first byte is the data value at volume location (0,0,0); the second byte is the data value at volume location (1,0,0); and the third byte is the data value at volume location (2,0,0)- When the x dimension is exhausted, then the y dimension and the z dimension are incremented, respectively. This embodiment is not limited in any way to a particular data format
The program 110 facilitates input from a user to identify one or more 3-D volume data sets to use for analysis and imaging. When a plurality of data volumes are used, the data value for each of die plurality of data volumes represents a different physical parameter or attribute for the same geographic space. By way of example, a plurality of data volumes could include a geology volume, a temperature volume, and a water-saturation volume. The voxels in the geology volume can be expressed in the form (x,y,z, seismic amplitude). The voxels jn the temperature volume can be expressed in. the form (x,y,z, °C). The voxels in the water-saturation volume can be expressed in the form (x,y,z, %saturation). The physical or geographic space defined by the voxels in each of these volumes is the same.

However, for any specific spatial location (xo,yo,2o)> the seismic amplitude would be contained in the geology volume, the temperature in the temperature volams, and the water-saniration in the water-saturation volume. The operation of program 110 is described in reference to FIGs, 2 through 5.
Referring now to FIG. 2, a method 200 is illustrated for analyzing a 3-D region of interest relative to a predetermined event. In step 202, a first attribute and a second attribute sue selected from the available attributes using the GUI tools (menu/interface software 104) described in reference to 1*16.1. The first attribute and the second attribute represent a geological region of interest where gas-bearing sands may be found. The first attribute and the second attribute each represent an acoustic signal comprising instantaneous amplitude and instantaneous frequency, respectively. Although there are other available well-known attributes such as amplitude, frequency, phase, instantaneous phase, semblance, and coherence, instantaneous amplitude and instantaneous frequency are the preferred attributes representing the presence of sand and/or sandstone in the region of interest.
In step 204, an event boundary is defined to provide a reference point for the region of interest- Because there ® a known correlation between sand or sandstone and limestone or dolomite, these formation properties are the preferred or predetermined event.
Referring to FIG. 3, the process of defining the event boundary (step 204) as a reference point is more fully described. In step 302, a thin) attribute and a fourth attribute are selected from the available attributes using the GUI tools (menu/interface software 104) described in reference to FIG. 1. The third attribute and the fourth attribute represent die predetermined event, that is limestone or dolomite. The third attribute and fourth attribute each represent an acoustic signal comprising amplitude and phase, respectively. Although

other well-known available attributes may be selected, in combination, or alone, amplitude and phase are the preferred attributes representing the presence of limestone or dolomite.
In step 304, a third attribute volume is calculated using the third attribute and a fourth attribute volume is calculated using the fourth attribute. Hie third attribute volume 402 and the fourth attribute volume 404 are illustrated in FIG. 4. Although the third attribute volume 402 and the fourth attribute volume 404 me illustrated side-by-side in FIG. 4, they have the same spatial coordinates but a different data value. The third attribute volume 402 and the fourth attribute volume 404 may be calculated using conventional shading/opacity (texture mapping) techniques, however, may also be calculated using volume rendering techniques generally well known in the art. In order to display seismic data in the manner thus described, voxel data is read front memory and converted into a specified color representing a specified texture. Textures are tiled in a 256 pixel by 256 pixel images. For larger volumes, many tiles exist on a single plane or surface. This process is commonly referred to by those skilled in the art as sampling, and is coordinated among multiple CPUs on a per tile basis. This technique, and others employed herein, are more fully described and illustrated in the 780, *781, '682, and '635 applications.
In step 306, a third attribute data value range is set. the third attribute data value range is pfcforably measured on a voxel scale between atwuit 0 and about 255, however, may be between about -128 and about +127. The third attribute data value range is preferably set between about 50 and about 127, Other data value ranges may be preferred, depending on the application or selected attributes. .
In step 308, a fourth attribute data value range is set. Hie fourtii attribute data value range is also measured on a voxel scale between about 0 and about 255, however, may

be between about -128 and +127. The fourth attribute data value range is preferably set between about -5 and about +5, Other data value ranges may be preferred, depending on the application or selected attributes.
In step 310, a third set of voxels are selected from the third attribute volume 402 that have a data value within die third attribute data value range. In step 312, a fourth set of voxels are selected from the fourth attribute volume 404 that have a data value within the fourth attribute data value range.
In step 314, the third set of voxels and the fourth set of voxel* are imaged and represent the event boundary 406 illustrated in FIG. 4. The event boundary 40$ represents the boundary or horizon of the limestone or dolomite that appears as a blue layer of voxels at the bottom of the third attribute volume 402 and be fourth attribute volume 404.
The techniques described to die '780 application may be utilised to image the third set of voxels and the fourth set of voxels. One technique involves combining the third set of voxels and die fourth set of voxels to form a combined set of voxels representing the event boundary 406. Each voxel in the combined set of voxels is assigned a new data value that is the same for each voxel hi the combined set of voxels and is within a combined data value range between about 0 and about 127, measured on a voxel scale between about 0 and about 255. A voxel may then be selected from the combined set of voxels that represents a seed voxel. From th« seed voxel, all other voxels from the combined set of voxels that are connected to the seed voxel and have the same data value may be autopicked and displayed to a user.

Alternatively, a voxel from at least one of the third set of voxels and the fourth set of voxels may be selected that represents a seed voxel. Voxels from the third set of voxels and the fourth set of voxels that are connected to tbe seed voxel and have the same data value may be autopicked and displayed to a user.
Once the event boundary 406 is defined, the geological region of interest relative to the event boundary 406 may be determined as illustrated in step 206. The presence of sand or sandstone is often found within aboat 300 feet above or below the limestone or dolomite event boundary 406. In FIG. 5, the region of interest 506 is illustrated comprising sand or sandstone below the event boundary 406.
In step 208, a first attribute volume 502 is calculated using ihe first attribute and a second attribute volume 504 is calculated using the second attribute. The first attribute volume 502 and the second attribute volume 504 are illustrated in FIG. 5. Although the first attribute volume 502 and tbe second attribute volume 504 are illustrated side-by-side in FIG. 5, they have the same spatial coordinates, but a different data value. Hie first attribute volume 502 and the second attribute volume 504 may be calculated in the same manner described in reference to calculating the third attribute volume 402 and the fourth attribute volume 404,
In step 210, a first attribute data value range is set based on a voxel scale between about 0 and about 255, however, may be between about -128 and 4-127. The first attribute data value range is preferably set between about 10 and about 140, based upon experimental results revealing the potential for gas-bearing sands where instantaneous amplitude voxels have a data value within this range. Although this is the preferred data value range for the first attribute, other data value ranges between about 37 and about 110;

between about 37 and about 120; and between about 37 and about 130 may be used when the first attribute represents instantaneous amplitade, Other data value ranges may be preferred, depending on the application or selected attribute.
In step 212, a second attribute data value range is set based on a voxel scab between about 0 and aboot 255, however, may be between about -128 and -f 177. The second attribute data value range is preferably set between about € and about 48, based upon experimental results revealing the potential for gas-bearing sands where instantaneous frequency voxels have a data value within this range. Although this is the preferred data value range for the second attribute, other data value ranges between about 2 and about 36; and between about 3 and about 37, may be used when the second attribute represents instantaneous frequency. Other data value ranges may be preferred, depending on the application or selected attribute.
In step 214, a first set of voxels is selected from die first attribute volume 502 that have a data value within the first attribute data value range. The fust set of voxels represent a preferred feature of the region of interest that comprises gas-bearing sands.
In step 216, a second set of voxels is selected from the second attribute volume 504 that have a date value wittin the second attribute date value range, The second set of voxels also represent the preferred feature of the region of interest
In step 218, the first set of voxels and the second set of voxels representing the preferred feature (gas-bearing Sands) are imaged. The techniques described in reference to imaging the third set of voxeis and the fourth set of voxels in step 314 may be used here as well. The image of a portion of the voxels representing the gas-bearing sands is illustrated in

FIG. 5 as a plurality of yellow points tot reside in a plane containing the tegion of interest
The techniques thus described are particttMy mefnl as analytical, diagnostic and interpretive took for any type of scientific data, including seismic data, and may be applied to the discovery and development of energy resources.
Those skilled in die art will therefore, appreciate that the foregoing techniques may be applied to the analysis of other types of attributes representing a regicn of interest and is not limited to geological formations and/or seismic data attributes, Consequently, the foregoing description of the invention is illustrative and various details of the illustraled construction or combinations of features of the various dements and/or steps may be made without departing from the spirit of the invention.

We Claim:
1. A computer implemented method for processing a three dimensional region of interest relative to a predetermined event, the method comprising the steps of:
defining a boundary of the event with a GUI tool and a voxel scale;
defining the region of interest relative to the boundary of the event;
selecting a first attribute and a second attribute with a GUI tool, the first attribute and second attribute representing the region of interest;
calculating a first attribute volume and a second attribute volume for the region of interest, the first attribute volume and the second attribute volume each comprising a plurality of voxels, each voxel being defined by a set of x, y, z coordinates and a data value;
selecting a first set of voxels from the first attribute volume that have a data value within a first attribute data value range set on the voxel scale, the first set of voxels representing a preferred feature of the region of interest;
selecting a second set of voxels from the second attribute volume that have a data value within a second attribute data value range set on the voxel scale, the second set of voxels representing the preferred feature; and
displaying with multiple processing units the first set of voxels and the second set of voxels.

2. The method as claimed in Claim 1, wherein the preferred feature comprises at least one of sand or sandstone.
3. The method as claimed in Claim 2, wherein the first attribute represents an acoustic signal comprising instantaneous amplitude and the second attribute represents an acoustic signal comprising instantaneous frequency.
4. The method as claimed in of Claim 3, wherein the region of interest is defined as within about 300 feet from the boundary of the event.
5. The method as claimed in Claim 3, wherein the first attribute data value range is between about 10 and about 140, and the second attribute data value range is between about 0 and about 48, the first attribute data value range and the second attribute data value range being measured on the voxel scale between about 0 and about 255.
6. The method as claimed in Claim 5, wherein the first attribute data value range is between about 37 and about 110, and the second attribute data value range is between about 2 and about 36.
7. The method as claimed in claim 5, wherein the first attribute data value range is between about 37 and about 120, and the second attribute data value range is between about 2 and about 36.
8. The method as claimed in claim 5, wherein the first attribute data value range is between about 37 and about 130, and the second attribute data value range is between about 3 and about 37.
9. The method as claimed in Claim 1, wherein defining the boundary of the event comprises the steps of:

selecting a third attribute with the GUI tool, the third attribute representing the event;
calculating a third attribute volume for the event, the third attribute volume comprising a plurality of voxels, each voxel being defined by a set of x, y, z coordinates and a data value;
selecting a third set of voxels from the third attribute volume that have a data value within a third attribute data value range based on the voxel scale, the third set of voxels representing the boundary of the event; and
imaging the third set of voxels.
10. The method as claimed in Claim 9, wherein the event is a geological formation comprising at least one of dolomite or limestone.
11. The method as claimed in Claim 10, wherein the third attribute represents an acoustic signal comprising at least one of amplitude, phase, frequency, instantaneous amplitude, instantaneous phase, instantaneous frequency, coherence or semblance.
12. The method as claimed in Claim 11, wherein the third attribute data value range is between at least one of about 50 and about 127 and about- 5 and about +5, the third attribute data value range being measured on the voxel scale between at least one of about 0 and about 255 and about-128 and about +127.
13. The method as claimed in Claim 12, wherein imaging the third set of voxels comprises the steps of:
selecting a voxel from the third set of voxels, the selected voxel representing a seed voxel;

autopicking voxels from the third set of voxels that are connected to the seed voxel and have the same data value; and
displaying the autopicked voxels from the third set of voxels to a user.
14. The method as claimed in Claim 12, wherein imaging the third set of voxels comprises
the steps of:
assigning a new data value to each voxel in the third set of voxels, the new data value having the same data value within a new data value range between about 0 and about 127 on the voxel scale;
selecting a voxel from the third set of voxels, the selected voxel representing a seed voxel;
autopicking voxels from the third set of voxels that are connected to the seed voxel and have the same data value; and
displaying the autopicked voxels from the third set of voxels to a user.
15. The method as claimed in claim 1, wherein imaging the first set of voxels and the second
set of voxels comprises the steps of:
combining the first set of voxels and the second set of voxels to form a combined set of voxels representing the preferred feature, each voxel in the combined set of voxels being assigned a new data value, the new data value having the same data value within a combined data value range between about 0 and about 127 on the vcoxel scale;

selecting a voxel from the combined set of voxels, the selected voxel representing a seed voxel;
autopicking voxels from the combined set of voxels that are connected to the seed voxel and have the same data value; and
displaying the autopicked voxels from the combined set of voxels to a user.
16. The method as claimed in claim 1, wherein imaging the first set of voxels and the second
set of voxels comprises the steps of:
selecting a voxel from at least one of the first set of voxels and the second set of voxels, the selected voxel representing a seed voxel;
autopicking voxels from the first set of voxels that are connected to the seed voxel and have the same data value;
autopicking voxels from the second set of voxels that are connected to the seed voxel and have the same data value; and
displaying the autopicked voxels from the first set of voxels and the second set of voxels to a user.
17. A system for processing a three dimensional region of interest relative to a
predetermined event, said system comprising:
a first system for defining a boundary of the event;
a second system for defining the region of interest relative to the boundary of the event.

a GUI tool for selecting a first attribute and a second attribute, the first attribute and second attribute representing the region of interest;
means for calculating a first attribute volume and a second attribute volume for the region of interest, the first attribute volume and the second attribute volume each comprising a plurality of voxels, each voxel being defined by a set of x, y, z coordinates and a data value;
a voxel scale for defining a data value within a first attribute data value range in the first attribute volume from which a first set of voxels is selected, the first set of voxels representing a preferred feature of the region of interest;
a voxel scale for defining a data value within a second attribute data value range in the second attribute volume from which a second set of voxels is selected, the second set of voxels representing the preferred feature; and
multiple processing units for displaying the first set of voxels and the second set of voxels.
18. The system as claimed in claim 17, wherein the region of interest is a geological formation and the preferred feature comprises at least one of sand or sandstone.
19. The system as claimed in claim 18, wherein the first attribute represents an acoustic signal comprising instantaneous amplitude and the second attribute represents an acoustic signal comprising instantaneous frequency.
20. The system as claimed in claim 19, wherein the region of interest is defined as within about 300 feet from the boundary of the event.

21. The system as claimed in claim 19, wherein the first attribute data value range is between about 10 and about 140, and the second attribute data value range is between about 0 and about 48, the first attribute data value range and the second attribute data value range being measured on the voxel scale between about 0 and about 255.
22. The system as claimed in claim 21, wherein the first attribute data value range is between about 37 and about 110, and the second attribute data value range is between about 2 and about 36.
23. The system as claimed in claim 21, wherein the first attribute data value range is between about 37 and about 120, and the second attribute data value range is between about 2 and about 36.
24. The system as claimed in claim 21, wherein the first attribute data value range is between about 37 and about 130, and the second attribute data value range is between about 3 and about 37.
25. The system as claimed in claim 17, wherein the system for defining the boundary of the event comprises:
a GUI tool for selecting a third attribute, the third attribute representing the event;
means for calculating a third attribute volume for the event, the third attribute volume comprising a plurality of voxels, each voxel being defined by a set of x, y, z coordinates and a data value;
a voxel scale for defining a data value within a third attribute data value range in the third attribute volume from which a third set of voxels is selected, the third set of voxels representing the boundary of the event; and

multiple processing units for displaying the third set of voxels.
26. The system as claimed in claim 25, wherein the event is a geological formation comprising at least one of dolomite or limestone.
27. The system as claimed in claim 26, wherein the third attribute represents an acoustic signal comprising at least one of amplitude, phase, frequency, instantaneous amplitude, instantaneous phase, instantaneous frequency, coherence or semblance.
28. The system as claimed in claim 27, wherein the third attribute data value range is between at least one of about 50 and about 127 and about- 5 and about +5, the third attribute data value range being measured on the voxel scale between at least one of about 0 and about 255 and about-128 and about +127.
29. The system as claimed in claim 28, wherein imaging the third set of voxels comprises:
selecting a voxel from the third set of voxels with a GUI tool, the selected voxel representing a seed voxel;
autopicking voxels from the third set of voxels that are connected to the seed voxel and have the same data value; and
displaying the autopicked voxels from the third set of voxels to a user.
30. The system as claimed in claim 28, wherein imaging the third set of voxels comprises:
assigning a new data value to each voxel in the third set of voxels with a voxel scale, the new data value having the same data value within a new data value range between about 0 and about 127;

selecting a voxel from the third set of voxels with a voxel scale, the selected voxel representing a seed voxel ;
autopicking voxels from the third set of voxels that are connected to the seed voxel and have the same data value; and
displaying the autopicked voxels from the third set of voxels to a user.
31. The system as claimed in claim 17, wherein imaging the first set of voxels and the second
set of voxels comprises the steps of:
combining the first set of voxels and the second set of voxels to form a combined set of voxels representing the preferred feature, each voxel in the combined set of voxels being assigned a new data value, the new data value having the same data value within a combined data value range between about 0 and about 127;
selecting a voxel from the combined set of voxels, the selected voxel representing a seed voxel;
autopicking voxels from the combined set of voxels that are connected to the seed voxel and have the same data value; and
displaying the autopicked voxels from the combined set of voxels to a user.
32. The system as claimed in claim 17, wherein imaging the first set of voxels and the second
set of voxels comprises the steps of:
selecting a voxel from at least one of the first set of voxels and the second set of voxels, the selected voxel representing a seed voxel;

autopicking voxels from the first set of voxels that are connected to the seed voxel and have the same data value;
autopicking voxels from the second set of voxels that are connected to the seed voxel and have the same data value; and
displaying the autopicked voxels from the first set of voxels and the second set of voxels to a user.

Documents:

2724-DELNP-2006-Abstract-(06-08-2009).pdf

2724-delnp-2006-abstract.pdf

2724-delnp-2006-Assignment (20-11-2013).pdf

2724-delnp-2006-Claims-(06-01-2014).pdf

2724-DELNP-2006-Claims-(06-08-2009).pdf

2724-delnp-2006-Claims-(20-11-2013).pdf

2724-delnp-2006-claims.pdf

2724-delnp-2006-Correspondence Others-(06-01-2014).pdf

2724-DELNP-2006-Correspondence Others-(14-02-2012).pdf

2724-delnp-2006-Correspondence Others-(20-11-2013).pdf

2724-DELNP-2006-Correspondence-Others-(06-08-2009).pdf

2724-DELNP-2006-Correspondence-Others-(30-06-2010).pdf

2724-DELNP-2006-Correspondence-Others-(31-08-2010).pdf

2724-delnp-2006-correspondence-others-1.pdf

2724-DELNP-2006-Correspondence-Others.pdf

2724-delnp-2006-description (complete).pdf

2724-delnp-2006-drawings.pdf

2724-delnp-2006-Form-1 (20-11-2013).pdf

2724-DELNP-2006-Form-1-(06-08-2009).pdf

2724-DELNP-2006-Form-1.pdf

2724-delnp-2006-Form-13-(20-11-2013).pdf

2724-DELNP-2006-Form-18.pdf

2724-DELNP-2006-Form-2-(06-08-2009).pdf

2724-delnp-2006-form-2.pdf

2724-DELNP-2006-Form-26.pdf

2724-DELNP-2006-Form-3-(06-08-2009).pdf

2724-DELNP-2006-Form-3-(14-02-2012).pdf

2724-DELNP-2006-Form-3.pdf

2724-delnp-2006-form-5.pdf

2724-delnp-2006-GPA-(20-11-2013).pdf

2724-delnp-2006-pct-101.pdf

2724-delnp-2006-pct-220.pdf

2724-delnp-2006-pct-237.pdf

2724-delnp-2006-pct-308.pdf

2724-delnp-2006-pct-409.pdf

2724-delnp-2006-pct-416.pdf

2724-delnp-2006-pct-search report.pdf

2724-DELNP-2006-Petition-137-(06-08-2009).pdf

2724-DELNP-2006-Petition-138-(06-08-2009).pdf

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Patent Number

260364

Indian Patent Application Number

2724/DELNP/2006

PG Journal Number

18/2014

Publication Date

02-May-2014

Grant Date

25-Apr-2014

Date of Filing

15-May-2006

Name of Patentee

LANDMARK GRAPHICS CORPORATION

Applicant Address

2101, CITY WEST BLVD., HOUSTON, TEXAS 77042, USA

Inventors:

#	Inventor's Name	Inventor's Address
1	LEES, JACK	6403 EDLOE, HOUSTON, TX 77005 (US)
2	SHEFFIELD, TATUM	4927 CAVE RUN DRIVE, MISSOURI CITY, TX 77459 (US)

PCT International Classification Number

G09G 5/00

PCT International Application Number

PCT/US2004/039117

PCT International Filing date

2004-11-19

PCT Conventions:

#	PCT Application Number	Date of Convention	Priority Country
1	10/718,018	2003-11-20	U.S.A.