WO1997005558A1 - Method for determining seismic data traveltime fields on a massively parallel computer - Google Patents
Method for determining seismic data traveltime fields on a massively parallel computer Download PDFInfo
- Publication number
- WO1997005558A1 WO1997005558A1 PCT/US1996/012261 US9612261W WO9705558A1 WO 1997005558 A1 WO1997005558 A1 WO 1997005558A1 US 9612261 W US9612261 W US 9612261W WO 9705558 A1 WO9705558 A1 WO 9705558A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- ofthe
- group
- traveltime
- slices
- data
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. analysis, for interpretation, for correction
- G01V1/30—Analysis
- G01V1/301—Analysis for determining seismic cross-sections or geostructures
Definitions
- This invention relates to the field of geophysical prospecting. Specifically, the invention involves a method of using parallel processors to obtain traveltime fields for applications such as seismic imaging, tomographic inversion and amplitude-versus- offset analysis in three-dimensional (3-D) geometries.
- the search for subsurface hydrocarbon deposits typically involves a sequence of data acquisition, analysis, and interpretation procedures.
- the data acquisition phase involves use of an energy source to generate signals that propagate into the earth and reflect from various subsurface geologic structures.
- the reflected signals are recorded by a multitude of receivers on or near the surface ofthe earth, or in an overlying body of water.
- the received signals which are often referred to as seismic traces, consist of amplitudes of acoustic energy which vary as a function of time, receiver position, and source position and, most importantly, vary as a function ofthe physical properties ofthe structures from which the signals reflect.
- the data analyst uses these traces along with a geophysical model to develop an image ofthe subsurface geologic structures.
- the analysis phase involves procedures that vary depending on the nature of the geological structure being investigated, and on the characteristics ofthe dataset itself.
- the purpose of a typical seismic data processing effort is to produce an image ofthe geologic structure from the recorded data. That image is developed using theoretical and empirical models ofthe manner in which the signals are transmitted into the earth, attenuated by the subsurface strata, and reflected from the geologic structures.
- the quality ofthe final product ofthe data processing sequence is heavily dependent on the accuracy ofthese analysis procedures.
- the final phase is the interpretation ofthe analyzed results.
- the interpreter's task is to assess the extent to which subsurface hydrocarbon deposits are present, thereby aiding such decisions as whether additional exploratory drilling is warranted or what an optimum hydrocarbon recovery scenario may be.
- the interpretation ofthe image involves a variety of different efforts.
- the interpreter often studies the imaged results to obtain an understanding of the regional subsurface geology. This may involve marking main structural features, such as faults, synclines and anticlines. Thereafter, a preliminary contouring of horizons may be performed. A subsequent step of continuously tracking horizons across the various vertical sections, with correlations ofthe interpreted faults, may also occur.
- the quality and accuracy ofthe results ofthe data analysis step ofthe seismic sequence have a significant impact on the accuracy and usefulness ofthe results of this interpretation phase.
- the seismic image can be developed using a three-dimensional geophysical model of seismic wave propagation, thereby facilitating accurate depth and azimuthal scaling of all reflections in the data.
- Accurately specified reflections greatly simplify data interpretation, since the interpretational focus can be on the nature ofthe geologic structure involved and not on the accuracy ofthe image.
- the analyst faces a processing volume challenge.
- a typical data acquisition exercise may involve hundreds to hundreds of thousands of source locations, with each source location having hundreds of receiver locations. Because each source-receiver pair may make a valuable contribution to the desired output image, the data handling load (i.e., the input/output data transfer demand) can be a burden in itself, independent ofthe computation burden.
- Figure 1 depicts a perspective view of a region 20 ofthe earth for which a geophysical image is desired.
- shot lines 2 consist of a sequence of positions at which a seismic source 3 is placed and from which seismic signals with ray paths 5 are transmitted into the earth.
- Receivers 4 placed along each line receive the signals from each source position after reflection from various subsurface reflectors 6.
- a first method of managing the seismic data burdens discussed above involves careful definition ofthe region over which the data are acquired. Specifically, use of any available preliminary geologic and geophysical information may facilitate the minimization ofthe surface area over which seismic data may need to be acquired. Such a minimization will directly reduce the amount of data that is ultimately acquired. Furthermore, similarly careful planning ofthe spacing between shot lines will optimize the analysis effort by reducing data volume. And finally, optimization ofthe number of sources and receivers that are used, and ofthe spacing between adjacent source and receiver positions, will also benefit the data analyst.
- Sequential computing involves use of analytic routines that perform only a single procedure, or perhaps focus on a single subset ofthe data or image, at any given time. This is a direct result of a computer having only one CPU. For that reason, the only optimization procedures that can be employed on single CPU computers are those which increase the efficiency ofthe processing as to the procedure or subset. Because all calculations must ultimately be performed by that single CPU, however, the options for obtaining high performance are innately limited.
- the multiple CPU capability of MPPs offers an obvious simultaneous computation advantage.
- This advantage is that the total time required to solve a computational problem can be reduced by subdividing the work to be done among the various CPUs, provided that the subdivision allows each CPU to perform useful work while the other CPUs are also performing work.
- the disadvantage of multiple CPU hardware is that the sequential processing methods that have long been used in software development must be replaced by more appropriate parallelized computing methods.
- MPPs require that processing methods be developed which make efficient use ofthe multiple CPU hardware. Ideally, these methods should organize the distribution of work relatively evenly among the processors, and ensure that all processors are performing necessary computations all ofthe time, rather than awaiting intermediate results from other processors.
- Seismic data consists generally of a large number of individual traces, each recorded somewhat independently ofthe other traces.
- Logically enough, sequential computing methods that require the analytic focus to be placed on a single calculation at a time adapt well to analysis ofthese independent traces. This is true even though computational bottlenecks may exist. For example, portions ofthe analytic sequence may require relatively more computation time than other portions, must be completed before other calculations may proceed, or may rely on similar input data as other traces, for example traveltimes.
- each of three principal processing components — data, model, and image — may be considered to be a candidate for distributing computational work among the various processors in an MPP.
- One option for distributing work among the processors would be to assign different groups ofthe input seismic trace data to different processors. For example, traces may be grouped by source locations, with different processors being assigned different groups. Similarly, the output image could be subdivided and assigned to different processors.
- the geophysical model used to generate the output image may also be possible to subdivide the geophysical model used to generate the output image into groupings that can be assigned to the various processors.
- That model is generally considered to be embodied in the arithmetic operations required by the mathematical model that is the subject ofthe processing effort.
- the mathematical model is often based on the wave equation).
- the data may be transformed into the frequency domain, with individual frequencies assigned to individual processors.
- combinations ofthese approaches For example, groups of processors may be assigned collective responsibility for specific frequencies in the model and all depths in the image, while having individual responsibility for specific horizontal locations in the image.
- the challenge to the seismic data analyst is to determine methods of subdividing the seismic data, model, and image into components that can be assigned to individual processors in the MPP, thus allowing calculations to be performed in each processor independently of other processors.
- This subdivision of seismic data analysis into individual components is commonly referred to as seismic decomposition.
- MPP has from thousands to tens of thousands of relatively unsophisticated processing elements.
- the processing elements typically perform the same operation on multiple data streams, a Single Instruction, Multiple Data stream (SIMD) machine.
- SIMD Single Instruction, Multiple Data stream
- An example is the CM2, a product ofthe Thinking Machines Corporation.
- These kinds of machines typically lack shared memory, i.e., each processor has its own separate memory unit and the information in the memory cannot be directly accessed by other processors.
- the individual processors typically have limited computing capability and memory. Because ofthe large number of processing elements and a lack of shared memory, data transfer between the processing elements is a major bottleneck in efficient utilization ofthe capability ofthe machines. Even with sophisticated interconnection techniques, such as in a hypercube arrangement, transfer of data between processors is a major factor in the running time of programs.
- T3D a product of Cray Research Corporation
- MIMD Multiple Instruction Multiple Data stream
- tomographic inversion is becoming an increasingly common technique.
- a multiplicity of receivers in a number of wells record traveltimes from a multiplicity of shots placed in a number of other, possibly different, wells.
- the measured traveltimes are compared to the calculated traveltimes for an initial velocity model ofthe subsurface and used to obtain an improved velocity model ofthe subsurface.
- This improved velocity model is a useful aid in inte ⁇ retation ofthe structure ofthe subsurface and the fluids in the data volume encompassed by the wells.
- US Patent No. 5,394,325 issued to Schneider teaches a method for calculation of traveltimes in a 3-D data volume.
- the process involves a finite-difference solution to the eikonal equation in spherical coordinates, with refinements to increase the stability ofthe calculation and cope with numerical roundoff error as well as turning- ray problems.
- the resulting 3-D grid of traveltimes are useful in depth migration, velocity analysis, raytracing for modeling of synthetic seismograms, 3-D traveltime inversion, and map migration.
- the present invention meets the need for an efficient MPP implementation of a process that determines traveltimes for seismic data analysis in hydrocarbon exploration and production.
- the present invention is a method of using parallel processors, preferably a massively parallel processor (MPP), to compute traveltime fields for a 3-D volume of the subsurface ofthe earth.
- the input to the process is either a velocity model or a slowness model ofthe 3-D volume.
- the end product ofthe invention is a set of traveltimes on a 3-D grid over this volume. As is known to those skilled in the art, such a grid is necessary for integral-type migration of seismic data.
- the invention in a preferred embodiment, starts with a 3-D rectangular grid of velocities or slowness defined in (x, y, z) coordinates.
- slowness is defmed as the reciprocal of velocity.
- a finite difference solution ofthe eikonal equation in 3-D spherical coordinates is used to compute the traveltimes for acoustic waves emanating from the shot location. The resulting traveltimes are inte ⁇ olated to give a traveltime field on a rectangular 3-D grid.
- the present invention provides for decomposition ofthe task of traveltime computations onto groups of processors associated with individual shots. This decomposition allows for maximization ofthe number of processors that are assigned to analysis tasks, thus increasing overall throughput. As part of the present invention, an initial computation ofthe total memory required for each shot is used to determine the number of processors in a group.
- each processor group the individual processors perform the traveltime calculations for a number of.y- slices for a portion ofthe data volume, preferably, but not necessarily, centered at the shot position.
- Each processor performs its traveltime computations independent of each other processor. Data transfer between processors handling adjacent >-slices facilitate the independent computations.
- the groups of processors used in the analysis are under the direction of a control processor that can dynamically assign work to processor groups. This ensures that the load on the processors is balanced, thus efficiently taking advantage ofthe computational capabilities ofthe MPP.
- Figures 1 and 1 A schematically illustrate the data acquisition configuration typically used in 3-D seismic exploration.
- Figure 2 depicts a simplified functional block diagram of a parallel processing system on which traveltime field determination using the present method may be performed.
- Figure 3 depicts a block diagram ofthe steps involved in the traveltime computation by each processing element.
- Figure 4 shows the relation between the rectangular coordinate system and the spherical coordinate system ofthe invention.
- Figure 5 shows the inte ⁇ olation between spherical and rectangular coordinates carried out in the invention.
- Figure 6 depicts a preferred allocation of traveltime calculation tasks for a single group of PEs.
- FIGS 7A and 7B depict the data exchange process that takes place at the boundaries between slices.
- Figure 8 shows the characterization ofthe computational front at the interface between two PEs.
- the present invention is a method of using a massively parallel processor to obtain traveltime fields in a portion ofthe subsurface ofthe earth.
- the method may be employed on any type of parallel processing computer that has more than one processor available to perform analysis and/or input/output tasks.
- a Cray Y-MP which has up to eight processors may be employed.
- Networked personal computers or workstations may also be employed.
- the method will be employed on a massively parallel processor (MPP) having 64 or more processing elements ("PEs").
- MPP massively parallel processor
- PEs processing elements
- T3D made by the Cray Research Co ⁇ oration.
- MPP For convenience, and not to be construed as limiting, the abbreviation MPP will be used herein to refer to any parallel processing computer suitable for the present method. However, use of MPP in that manner is in no way to be construed as limiting application ofthe present method to solely those computers deemed by the commercial marketplace to be massively parallel.
- FIG. 1 depicts a perspective view of a region 20 ofthe earth for which a geophysical image is desired.
- shot lines 2 consist of a sequence of positions at which a seismic source 3 is placed and from which seismic signals with ray paths 5 are transmitted into the earth.
- Receivers 4 placed along each line receive the signals from each source position after reflection from various subsurface reflectors 6.
- the process of prestack depth migration in the time-space domain requires the computation of traveltimes for seismic waves emanating from a grid of surface locations down to a 3-D grid of subsurface positions in the data.
- the sampling in the horizontal directions of this volume may be different from the sampling in the vertical direction and may also be different from the shot, receiver and line spacing used in the acquisition ofthe 3-D data set. This will be familiar to those knowledgeable in the art.
- the description ofthe present method of computing traveltimes may be simplified by describing one embodiment of an MPP system on which the method may be implemented.
- the components ofthe MPP system will typically consist of an MPP 100, a data tape storage facility 102, data disks 104, output disks 106, and a host computer 108.
- the MPP 100 should be capable of perfo ⁇ ning in the multiple instruction stream multiple data stream mode of operation (MIMD). This mode of operation allows each processor to perform different tasks simultaneously and on different sets of data, if programmed to do so.
- the method may also be advantageously employed on computers using other modes of operation, for example single instruction stream multiple data stream (SIMD). This mode of operation has all processors simultaneously performing the same tasks, but on different sets of data.
- MIMD multiple instruction stream multiple data stream
- SIMD single instruction stream multiple data stream
- An MPP suitable for use is the T3D manufactured by Cray Research, Inc., which is a MIMD MPP.
- MPP systems suitable for processing seismic data using the present method will be known to those skilled in the art.
- one ofthe PEs in MPP, 100 is designated as the control PE, 110.
- the other PEs in the preferred embodiment are partitioned into groups of analysis PEs, 112. Within each group of analysis PEs, one PE is designated as the lead PE, 114.
- the other PEs, 116, in each group are more limited in their activities than the lead PE in each group.
- the control PE, 110 is a necessary part of the preferred embodiment, whereas the tasks performed by the lead PEs, 114, could easily be done by the other PEs, 116, in each group of PEs, 112.
- the host computer, 108 stores a velocity model for the region 20 in Figure 1 on data disks, 104, as slowness information (slowness is the reciprocal ofthe velocity). This is a matter of computational efficiency because the computations of traveltimes involve multiplication by the slowness.
- the slowness data are stored in v-slices.
- the analyst designates, as an input parameter to the host 108, the shot positions for which traveltime computations are needed. Usually, the shot positions will be along a number of lines, 1, on the surface ofthe 3-D volume corresponding to the lines of data acquisition. The designated positions are transferred by the host to the control PE, 110.
- the present invention performs a finite difference solution of a partial differential equation with an adaptive step size. It will be appreciated by those knowledgeable in the art that, at the outset, in a scheme for solution of finite difference equations with an adaptive step size, the memory allocation requirements for the PEs is difficult to predict. Specifically, in the present method it is desirable to obtain an estimate ofthe number of PEs that will be required in each group to compute and store the traveltimes for the traveltime subregion the analyst selects for the family of shot positions to be assigned to the group.
- the traveltime subregion is a rectangular parallelepiped volume that encloses the shot location over which the traveltime fields are to be computed.
- the top ofthe subregion can be a square with its lateral dimensions defined by an analyst-specified input parameter.
- the vertical dimension ofthe traveltime computation will be to the maximum depth of region 20.
- a limited traveltime calculation simulation is performed, as discussed in the next two paragraphs.
- the limited simulation consists of selecting two shot locations, 3, for every line, 2, on surface 18. For a typical survey, this means that simulations are carried out for several hundred shot locations.
- the initial simulation is performed with only one group 112 and with one PE in the group.
- spherical computation fronts are propagated with a fixed radial increment. For pu ⁇ oses of this simulation, this radial increment is set equal to one-tenth ofthe maximum step size that is permissible in the actual traveltime calculations.
- the radial increment and step size parameters are discussed further below in reference to Figure 3. This simulation itself is merely a number counting exercise to determine the maximum number of traveltime points that would have to be stored in the memory of an individual PE. Traveltime sampling density considerations are also discussed below in reference to Figure 3.
- the simulation is repeated using two PEs in the group. If two PEs are not sufficient, the number is increased to three, and so on. Based on this simulation, the control PE, 110, makes a decision on the number of PEs that are allocated to each group, 112. Typically, the number is between one and three. Tests ofthe present method indicate that, for datasets of typical interest to geophysical analysts, more than three PEs per group will rarely be required. If necessary, however, this number can be changed during processing, as is discussed further below.
- the control PE passes to the lead PE, 114, in each group, 112, the shot location associated with the group and the subregion over which the group is to compute traveltimes.
- the traveltime computations are performed by each group of PEs for their designated shot locations independently of the other groups of PEs.
- the shot locations passed to the lead PE may be a fixed initial table of locations to be assigned to the group, or may simply be the first location to be handled by the group. The latter option facilitates the dynamic load balancing feature ofthe present method which is discussed further below.
- Figure 6 illustrates the allocation of tasks between the PEs in each group 112.
- FIG. 1 An exploded view ofthe 3-D subregion 151 ofthe overall data volume, 20, from Figure 1 is shown. This is the portion of data volume 20 for which a particular group of processors, 112 in Figure 2, will be performing traveltime calculations. A shot location, 3, on the surface ofthe earth is also indicated.
- each ofthe PEs in the group 112 is allocated a number of v-slices
- each PE will perform traveltime calculations.
- This v-slice allocation corresponds to both the input slowness data and the output traveltime data.
- the v-slices will be identical within subregion 151 for both the slowness and the traveltime data.
- the present method is not limited to embodiments in which the slowness and traveltime -slices are identically- distributed; rather the traveltime v-slices may be more or less densely distributed through subregion 151 depending on the needs ofthe analysis to be performed.
- Each ofthe PEs in the group will be responsible for a different set of slices, 152. At this point, there is no distinction between the lead PE in a group, 114, and the remaining PEs, 116.
- the distance between the traveltime slices may be unrelated to the spacing between the seismic lines 2 in Figure 1.
- the v-slices are shown in groups of three; this is for pu ⁇ oses of illustration only and is not to be construed as a limitation.
- the lead PE, 114 may determine the number ofy- slices to be allocated to each PE 116 in the group, or, alternatively, that number may be input by the analyst.
- the slowness data will generally be stored on disk iny-slice format, but that is not a limitation ofthe present method. Initially, the slowness form data are on a rectangular three dimensional grid ofthe subsurface, 121. On the other hand, the traveltime computations are performed in spherical coordinates (r, ⁇ , ⁇ ), and part ofthe present method involves the inte ⁇ olation of slownesses in spherical coordinates from the slownesses in rectangular coordinates.
- the relationship between the spherical coordinates (r, ⁇ , ⁇ ) and the rectangular coordinates (x, y, z) is shown in Figure 4.
- the origin ofthe coordinate system is at the shot location 3.
- ⁇ is measured from the y- axis to the line defined by r.
- the angle ⁇ is an angle lying in the x-z plane which is measured from the x-y plane to a plane containing r and the y-axis.
- depth slicing would mean that the PEs responsible for deeper traveltime computations would be idle while the shallow traveltimes were being computed.
- y-slices arises because the coordinate system in which the calculations are performed measures ⁇ from the y-axis.
- a constant ⁇ corresponds to a circular arc on a constant y- plane. This way, each PE can operate on a range of ⁇ s and on all ⁇ s for each ⁇ , which therefore corresponds to the range of y-slices assigned to that PE.
- each PE within a group be responsible for a depth (i.e. horizontal) slice.
- depth i.e. horizontal
- the disclosure in the present application of vertical slices is not to be construed as a limitation.
- Figure 6 shows the shot position, 3, as being in the center ofthe upper surface ofthe subregion 151 volume. This is for computational efficiency; when there are an odd number of PEs in a group the idle time of adjacent processors in the group is reduced, as is discussed further below in relation to Figures 7 A and 7B. If, on the other hand, there are an even number of PEs in a group, the shot position would be positioned as close as possible to the middle ofthe subregion 151, but still within one PE. Those knowledgeable in the art will recognize that such a placement may not always be feasible. For example, such a placement is not possible when the shot position coincided with a comer of subregion 151, allocated to the group of processors, 112.
- r max The maximum radius, r max , is determined by J selecting ° that comer of subregion 151 which is farthest from the shot location. This would be the distance from the shot location 3 to one ofthe bottom comers of subregion 151.
- the maximum incremental radial and minimum angular values for the traveltime grid , ⁇ r , ⁇ , and ⁇ are set.
- the incremental radius will be set equal to the minimum grid spacing in the rectangular grid, whether it is in the x, y or z direction.
- ⁇ r min ⁇ x, ⁇ y, ⁇ z ⁇ where ⁇ r, ⁇ y, and ⁇ _r the grid sizes in the three respective directions. This ensures that the computations will not occur on a coarser scale than that found in the rectangular grid.
- the incremental angles are set equal to said minimum grid spacing divided by r .
- the initial radial and angular increments ⁇ r, ⁇ , and ⁇ are set for the first extrapolation step.
- the initial radial increment is set to nine- tenths of ⁇ r max , while the angular increments are set to roug a hly 0.1 radians, as a result ofa calculation set forth in the disclosure of
- the slownesses are inte ⁇ olated from the rectangular grid to the spherical computation front at the first radius, 123, which is determined by the initial radial increment. This process of inte ⁇ olation from a rectangular grid to a spherical grid would be familiar to those knowledgeable in the art.
- the three components ofthe traveltime gradient vector at the initial radius are extrapolated at step 124 to the next radius via an advancing calculation front and the traveltime t is computed for each point on the calculation front at the new radius. In a preferred embodiment this is performed using the method of Schneider.
- the radius ofthe new front and that ofthe previous front are checked against the rectangular traveltime grid to determine whether points in the rectangular traveltime grid are located between these two spherical computation fronts, 125. If any exist, an inte ⁇ olation is performed between the two spherical computational fronts to give traveltimes on the rectangular grid, 126, using techniques known to those skilled in the art. That inte ⁇ olation is discussed further below in reference to Figure 5.
- the previous computation front is discarded and an adaptive radial step search is then performed to determine the value ofthe next step Ar k and, accordingly, the radius ofthe next computation front, 131.
- the process retums to the slowness inte ⁇ olation step and the steps starting at 123 are repeated.
- the computation is complete when the computation front reaches or exceeds r max , 127.
- Each PE takes the differences of traveltimes for adjacent slices and scales these traveltime differences into 8 bits, 132. These are sent to the lead PE, 114, in the group.
- the lead PE packs all the traveltime differences into a minimum number of computer words and writes these out on disk, 106, along with the traveltime for its own first y- slice which is written out in 16 bits.
- the lead PE under instructions from the control PE, 110 proceeds to the next shot to be assigned to the group, 134.
- the steps indicated in Figure 3 are performed by each PE independent of each other PE in the group. However, as is discussed further below, as a computational front approaches a slice assigned to an adjacent PE in the group, data transfer between the PEs is required. That data transfer occurs in association with steps 124 of Figure 3.
- the finite difference traveltime calculations are performed by a solution ofthe eikonal equation in spherical coordinates (r, ⁇ , ⁇ ) with an origin at the shot position, 3 in Figure 4, to extrapolate from one computational front to another, step 124, as is given by Schneider.
- traveltimes on spherical fronts 142 and 142' would be inte ⁇ olated to give traveltimes to the points 140' on the rectangular grid.
- the traveltimes to points 140" cannot be determined until a later spherical front is calculated. Once all traveltimes for all the rectangular grid points between the fronts 142 and 142' have been obtained, there is no longer a need to keep the front 142. Traveltime inte ⁇ olation would then proceed using 142' and the next spherical front.
- each PE independently calculates traveltimes for the slices for which it is responsible, does not require interaction with other PEs in the group.
- data transfer between the PEs may be required to allow each PE to continue the independent traveltime calculation process.
- the data to be transferred may include traveltime field data, slowness data, spatial traveltime derivatives, or other, depending on the embodiment involved.
- the data transfer process between the PEs, 114 and 116, in a group, 112, is discussed with reference to Figures 7 A and 7B.
- Figure 7 A shows an exploded view of a portion ofthe subregion shown in Figure 6.
- each set 152 in Figure 6 is not shown separately, but rather are depicted in Figure 7A and 7B solely as slice block 152'.
- This depiction is for pu ⁇ oses of simplifying the following discussion only.
- the shot location, 3 is above, below, or at the surface ofthe earth, but will in any case be on the surface of or within the volume ofthe subregion, 151.
- the x and y axes have been rotated by 90 compared to Figure 6.
- three PEs are shown as being part ofthe group, 112. These are the lead processor, 114, and two other PEs in the group, 116 and 116'.
- the lead PE, 114 will typically be responsible for y- slices with smaller y-coordinate values than are associated with the other PEs in the group. This facilitates traveltime data storage, as is discussed further below.
- a computational front 160 for shot location 3 which was computed by PE 116. As is indicated, the computational front is confined to they- slices for which PE 116 is responsible. For the spherical front calculation depicted in Figure 7 A, the other PEs, 114 and 116' have been idle and the steps given in Figure 3 were carried out only by PE 116.
- Figure 7B shows the computation front 160' at a later stage ofthe spherical front calculations in each ofthe slice blocks, 152'.
- the computational front is no longer confined to a single PE. Instead, the PEs in the group must exchange information about the components ofthe computational front at their common boundaries.
- data in PE 116 must be transferred at these boundaries to the adjoining PEs 114 and 116' and vice versa.
- a given value of ⁇ defines a circle on the boundary between adjacent PEs.
- the advancing front calculations in this invention proceed at successive increments in r; therefore, the data transfer between PEs occurs at a fixed ⁇ and all ⁇ for each r.
- FIG. 8 This data transfer/indexing feature is illustrated in Figure 8, where a block 152', for which a PE, 116, is responsible is shown. Also shown are two successive spherical computational fronts, 142 and 142', at a point for which the information must be passed to another PE (not shown). With the coordinate system as defined, the points on the front 142 to be communicated to the next processor are defined by a fixed angle ⁇ , 172. Different points on the front, 142, will have the same radius r, 170, in the spherical coordinate system and different angles ⁇ , not shown. The next spherical computational front, 142' , is characterized by radius 170' and angles ⁇ 172 '. The data points exchanged between processors can be indexed in terms of a fixed ⁇ and all angles ⁇ .
- the present method includes a feature which evenly distributes the y-slices, and therefore balances the work load among all PEs in a group. For most shots in a survey, this effectively places the source location at the center of one ofthe processor groups whenever possible.
- the invention ensures that the time for which PE 116 in Figure 7A and 7B is solely performing calculations is relatively small, and also ensures that the other PEs in the group begin calculations at approximately the same time. This maximizes the distribution of all necessary calculations across all analysis PEs.
- the shot would preferably be placed on a slice near the edge ofthe block 152' assigned to one ofthe processors, but close to the middle ofthe processor group. That assignment ensures that other PEs quickly begin calculations, thereby increasing MPP throughput. As the shot location approaches the edge ofthe survey, the shot is skewed toward the outer PEs and the computation proceeds with some loss of efficiency since the other PE's cannot as quickly initiate calculations.
- the PE designated as the lead PE, 114 is also responsible for the task of writing the traveltime data, after they have been inte ⁇ olated to a rectangular grid. This was discussed above in reference to Step 132 of Figure 3.
- the processors that are not lead processors, 116 send the packed traveltime data to the lead PE, 114, after all the traveltime calculations for the shot have been performed
- the lead PE. 114 accumulates the information from all the PEs in the group through inter-processor communication. At this point, the lead PE, 114, writes out the packed traveltime information to the output disk 106. This was mentioned above with reference to 106 in Figure 2 and 134 in Figure 3.
- the lead PE, 114 writes the traveltime data for its first y-slice, (the one with minimum y- value), in 16 bit format.
- the traveltime data for all the other y- slices in the group are stored in 8 bit format in incremental form, i.e., for any other y- slice, only differences between the computed traveltimes and the accumulated total ofthe prior differences.
- This incremental format makes it possible to pack the data without accumulating errors, leading to reduced data storage and data transfer requirements. This method of storing incremental bits will be familiar to those knowledgeable in the art.
- the traveltime fields when written out to disk are in depth slices, with each depth slice being partitioned into constant x-vectors.
- FIG 2 it sends a signal to the control processor, 110.
- the control processor checks to see ifthere are any more shot locations for which traveltimes are to be computed. If so, the control processor, 110, initiates the process of transmitting information on the next shot location to the processor group, 112. The processor group then performs the computations for the new shot location. This provides for a dynamic load balancing between the groups of PEs. When a group of PEs completes its assigned traveltime computations for a shot location, it simply moves on to the next shot position for which calculations are required
- control processor, 110 determines that traveltimes have been calculated for all the shot locations for a shot line, it sends a signal to the host computer, 108. At this point, the host computer, 108, starts reading the traveltime data for that shot line off the disks, 106, and writes that data onto tape, 102, or other mass storage device, for use in migration or other seismic processing techniques.
- One ofthe features ofthe invention is the ability to stop and restart the traveltime calculations.
- the desirability of having such a restart feature will be known to those familiar with the art.
- a natural restart point is when all the shots in a line have been computed.
- stops and restarts may be initiated by the analyst for pu ⁇ oses such as maintenance ofthe MPP.
- a unique feature in a preferred embodiment ofthe present method allows the restart feature to be automatically used in cases where, due to complications in the velocity model, the memory available on the individual processors becomes inadequate. In such cases, an error message is sent by the PE that is running out of memory to the control PE, which then starts shutting down the other groups of PEs. After all the groups have been shut down, the control processor assigns an increased number of PEs to each group, and calculations are then restarted. This ability to do a dynamic reallocation of the processors is an advance over prior art.
- the above method can be used in a number of different seismic processing applications.
- the method can be used to generate traveltimes for prestack Kirchhoff time or depth migration.
- An altemate application ofthe generated traveltimes from this invention is in tomographic inversion of crosswell seismic data.
Abstract
Description
Claims
Priority Applications (8)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
AU65996/96A AU706652B2 (en) | 1995-07-28 | 1996-07-25 | Method for determining seismic data traveltime fields on a massively parallel computer |
DE0842482T DE842482T1 (en) | 1995-07-28 | 1996-07-25 | METHOD FOR DETERMINING RUNTIME FIELDS OF SEISMAL DATA ON A SOLID-PARALLEL COMPUTER |
DE69624362T DE69624362T2 (en) | 1995-07-28 | 1996-07-25 | METHOD FOR DETERMINING RUNTIME FIELDS OF SEISMAL DATA ON A SOLID-PARALLEL COMPUTER |
EP96925504A EP0842482B1 (en) | 1995-07-28 | 1996-07-25 | Method for determining seismic data traveltime fields on a massively parallel computer |
JP9507753A JPH11510281A (en) | 1995-07-28 | 1996-07-25 | A method for determining seismic data travel time fields on a massively parallel computer |
US09/117,529 US5991695A (en) | 1995-07-28 | 1996-07-25 | Method for determining seismic data traveltime fields on a massively parallel computer |
CA002222721A CA2222721C (en) | 1995-07-28 | 1996-07-25 | Method for determining seismic data traveltime fields on a massively parallel computer |
NO980292A NO980292L (en) | 1995-07-28 | 1998-01-22 | Method for determining the latency fields for seismic data, using parallel processors |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US160495P | 1995-07-28 | 1995-07-28 | |
US60/001,604 | 1995-07-28 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO1997005558A1 true WO1997005558A1 (en) | 1997-02-13 |
Family
ID=21696928
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US1996/012261 WO1997005558A1 (en) | 1995-07-28 | 1996-07-25 | Method for determining seismic data traveltime fields on a massively parallel computer |
Country Status (9)
Country | Link |
---|---|
US (1) | US5991695A (en) |
EP (1) | EP0842482B1 (en) |
JP (1) | JPH11510281A (en) |
AU (1) | AU706652B2 (en) |
CA (1) | CA2222721C (en) |
DE (2) | DE69624362T2 (en) |
MY (1) | MY132159A (en) |
NO (1) | NO980292L (en) |
WO (1) | WO1997005558A1 (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2000019371A1 (en) * | 1998-09-25 | 2000-04-06 | Drummond Brian L | A method and apparatus for performing image processing on seismic data |
US6885946B1 (en) | 1998-09-25 | 2005-04-26 | Complex Data Technologies | Method and apparatus for performing image process of seismic data |
Families Citing this family (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7058513B2 (en) * | 1999-11-08 | 2006-06-06 | Vecta Technology, L.P. | Method of seismic exploration by discriminating horizontal and vertical shear waves |
FR2818387B1 (en) * | 2000-12-18 | 2003-02-14 | Inst Francais Du Petrole | METHOD FOR OBTAINING REFLECTION TRAVEL TIMES FROM AN INTERPRETATION OF SEISMIC DATA IN MIGRATED CYLINDRIC WAVES |
US6778909B1 (en) | 2002-10-05 | 2004-08-17 | 3Dgeo Development, Inc. | Seismic data processing systems and methods |
US6915212B2 (en) * | 2003-05-08 | 2005-07-05 | Moac, Llc | Systems and methods for processing complex data sets |
US6996470B2 (en) * | 2003-08-01 | 2006-02-07 | Moac Llc | Systems and methods for geophysical imaging using amorphous computational processing |
AU2004304279B2 (en) * | 2003-12-12 | 2008-12-18 | Exxonmobil Upstream Research Company | Method for seismic imaging in geologically complex formations |
US7426749B2 (en) * | 2004-01-20 | 2008-09-16 | International Business Machines Corporation | Distributed computation in untrusted computing environments using distractive computational units |
US8983779B2 (en) | 2011-06-10 | 2015-03-17 | International Business Machines Corporation | RTM seismic imaging using incremental resolution methods |
US9291734B2 (en) | 2011-06-10 | 2016-03-22 | International Business Machines Corporation | Full waveform inversion using combined shot data and no scratch disk |
US9291735B2 (en) | 2011-06-10 | 2016-03-22 | Globalfoundries Inc. | Probablistic subsurface modeling for improved drill control and real-time correction |
US9063248B2 (en) | 2011-06-10 | 2015-06-23 | International Business Machines Corporation | RTM seismic imaging using combined shot data |
US9207991B2 (en) | 2012-06-25 | 2015-12-08 | International Business Machines Corporation | Methods and apparatus for processing load balancing in distributed problem processing |
WO2014035488A1 (en) * | 2012-08-29 | 2014-03-06 | Chevron U.S.A. Inc. | System and method of processing seismic data on a co-processor device |
US10591638B2 (en) * | 2013-03-06 | 2020-03-17 | Exxonmobil Upstream Research Company | Inversion of geophysical data on computer system having parallel processors |
WO2016099747A1 (en) * | 2014-12-18 | 2016-06-23 | Exxonmobil Upstream Research Company | Scalable scheduling of parallel iterative seismic jobs |
US10267934B2 (en) * | 2015-01-13 | 2019-04-23 | Chevron U.S.A. Inc. | System and method for generating a depositional sequence volume from seismic data |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5198979A (en) * | 1989-09-26 | 1993-03-30 | Shell Oil Company | Seismic migration of multiprocessor computer |
US5349527A (en) * | 1991-12-20 | 1994-09-20 | Schlumberger Technology Corporation | Method of seismic time migration using a massively parallel computer |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5537319A (en) * | 1993-12-01 | 1996-07-16 | Schlumberger Technology Corporation | Method for load balancing seismic migration processing on a multiproccessor computer |
US5657223A (en) * | 1994-06-03 | 1997-08-12 | Exxon Production Research Company | Method for seismic data processing using depth slice decomposition |
US5504678A (en) * | 1994-06-03 | 1996-04-02 | Exxon Production Research Company | Method for seismic data processing using depth slice decomposition |
US5584489A (en) * | 1995-06-07 | 1996-12-17 | Exxon Production Research Company | Primary and secondary seal assemblies with contacting convex surfaces |
US5734829A (en) * | 1995-10-20 | 1998-03-31 | International Business Machines Corporation | Method and program for processing a volume of data on a parallel computer system |
-
1996
- 1996-07-25 EP EP96925504A patent/EP0842482B1/en not_active Expired - Lifetime
- 1996-07-25 US US09/117,529 patent/US5991695A/en not_active Expired - Fee Related
- 1996-07-25 DE DE69624362T patent/DE69624362T2/en not_active Expired - Fee Related
- 1996-07-25 JP JP9507753A patent/JPH11510281A/en active Pending
- 1996-07-25 WO PCT/US1996/012261 patent/WO1997005558A1/en active IP Right Grant
- 1996-07-25 CA CA002222721A patent/CA2222721C/en not_active Expired - Fee Related
- 1996-07-25 DE DE0842482T patent/DE842482T1/en active Pending
- 1996-07-25 AU AU65996/96A patent/AU706652B2/en not_active Ceased
- 1996-07-27 MY MYPI96003103A patent/MY132159A/en unknown
-
1998
- 1998-01-22 NO NO980292A patent/NO980292L/en not_active Application Discontinuation
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5198979A (en) * | 1989-09-26 | 1993-03-30 | Shell Oil Company | Seismic migration of multiprocessor computer |
US5349527A (en) * | 1991-12-20 | 1994-09-20 | Schlumberger Technology Corporation | Method of seismic time migration using a massively parallel computer |
Non-Patent Citations (1)
Title |
---|
See also references of EP0842482A4 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2000019371A1 (en) * | 1998-09-25 | 2000-04-06 | Drummond Brian L | A method and apparatus for performing image processing on seismic data |
US6885946B1 (en) | 1998-09-25 | 2005-04-26 | Complex Data Technologies | Method and apparatus for performing image process of seismic data |
Also Published As
Publication number | Publication date |
---|---|
DE69624362T2 (en) | 2003-06-12 |
EP0842482A1 (en) | 1998-05-20 |
AU6599696A (en) | 1997-02-26 |
EP0842482A4 (en) | 1998-10-07 |
NO980292L (en) | 1998-03-30 |
DE842482T1 (en) | 1999-04-22 |
CA2222721A1 (en) | 1997-02-13 |
MY132159A (en) | 2007-09-28 |
JPH11510281A (en) | 1999-09-07 |
AU706652B2 (en) | 1999-06-17 |
CA2222721C (en) | 2000-05-09 |
NO980292D0 (en) | 1998-01-22 |
US5991695A (en) | 1999-11-23 |
DE69624362D1 (en) | 2002-11-21 |
EP0842482B1 (en) | 2002-10-16 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US5991695A (en) | Method for determining seismic data traveltime fields on a massively parallel computer | |
US5995904A (en) | Method for frequency domain seismic data processing on a massively parallel computer | |
US5657223A (en) | Method for seismic data processing using depth slice decomposition | |
US20040162677A1 (en) | Method and system for distributed tomographic velocity analysis using dense p-maps | |
US7095678B2 (en) | Method for seismic imaging in geologically complex formations | |
AU676110B2 (en) | Method for seismic processing on a multiprocrssor computer | |
US5504678A (en) | Method for seismic data processing using depth slice decomposition | |
AU707757B2 (en) | Method for frequency domain seismic data processing on a massively parallel computer | |
US5987387A (en) | Method of dip moveout analysis on a massively parallel computer | |
AU705347B2 (en) | Method of dip moveout analysis on a massively parallel computer | |
Akbar | Three-dimensional prestack plane-wave Kirchhoff depth migration in laterally varying media | |
Kao et al. | Massively parallel computing of 3-D prestack depth migration using phase-screen propagators | |
Phadke et al. | Parallel distributed seismic imaging algorithms on PARAM 10000 | |
Tulchinsky et al. | Application of SCIT supercomputers to develop and execute parallel geophysical programs | |
Phadke et al. | PVM implementation of higher order finite difference seismic modelling algorithms in a distributed computing environment | |
Matarese | 3-D Traveltime Modeling With Application To Seismic Imaging And Tomography |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A1 Designated state(s): AU CA JP NO SG US |
|
AL | Designated countries for regional patents |
Kind code of ref document: A1 Designated state(s): AT BE CH DE DK ES FI FR GB GR IE IT LU MC NL PT SE |
|
DFPE | Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101) | ||
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
ENP | Entry into the national phase |
Ref document number: 2222721 Country of ref document: CA Ref country code: CA Ref document number: 2222721 Kind code of ref document: A Format of ref document f/p: F |
|
WWE | Wipo information: entry into national phase |
Ref document number: 1996925504 Country of ref document: EP |
|
ENP | Entry into the national phase |
Ref country code: JP Ref document number: 1997 507753 Kind code of ref document: A Format of ref document f/p: F |
|
WWE | Wipo information: entry into national phase |
Ref document number: 09117529 Country of ref document: US |
|
WWP | Wipo information: published in national office |
Ref document number: 1996925504 Country of ref document: EP |
|
WWG | Wipo information: grant in national office |
Ref document number: 1996925504 Country of ref document: EP |