COMPUTER-IMPLEMENTED METHOD AND SYSTEM FOR REMOVING LOW FREQUENCY AND LOW WAVENUMBER NOISES TO GENERATE AN ENHANCED IMAGE

Abstract

A method and a system for implementing the method are disclosed wherein the source wavelet, input parameter models, and seismic input data may be obtained from a non-flat surface, sometimes mild, or foothill topography as well as the shot and receiver lines might not necessarily be straight, and often curve to avoid obstacles on the land surface. In particular, the method and system disclosed, suppresses low wavenumber and low frequency noises, by balancing lateral and vertical amplitudes to produce an image of subsurface reflectors located within a survey area having higher lateral resolutions and wavenumbers, as well as higher high-cut frequencies, and lower low-cut frequencies in complex media, than could otherwise not be achieved by other methods commonly known in the art.

Claims

1. A computer-implemented, reverse time migration method, pre-programmed on a non-transitory computer readable device coupled to a memory resource configured to execute the computer-implemented, reverse time migration method using 3D Laplacian operator, a low-pass wavenumber filtering in 2D-lateral space directions, and a low-pass frequency filtering in 1D-time domain, for removing low frequency and low wavenumber noises to generate final stacked image in the 3D space directions x, y, and z of a survey region, the method comprising: retrieving a source wavelet, a set of input parameter models, and seismic data from receiving sensors of a survey region having space domain directions x, y, z by the non-transitory computer readable device using a telemetry device; storing the retrieved source wavelet, the set of input parameter models, and the seismic data from the survey region to the memory resource; retrieving the stored source wavelet, the set of input parameter models, and the seismic data from the memory resource by the non-transitory computer readable device; computing an integral algorithm by the non-transitory computer readable device using the retrieved source wavelet from the memory resource; generating a new source wavelet from the computed integral algorithm by the non-transitory computer readable device; storing the generated new source wavelet to the memory resource by the non-transitory computer readable device; setting a user-defined, cut-off effective frequency band, for the retrieved seismic data on the non-transitory computer readable device; storing the set user-defined, cut-off effective frequency band to the memory resource by the non-transitory computer readable device; retrieving the stored user-defined, cut-off effective frequency band, the stored new source wavelet, the input parameter models, and the seismic data, from the memory resource by the non-transitory computer readable memory device; computing a reverse time migration by the non-transitory computer readable device using the retrieved user-defined, cut-off effective frequency band, the retrieved new source wavelet, the retrieved input parameter models, and the retrieved seismic data; generating a raw and stacked image, in 3D-space domain directions x, y, z of the survey region by the non-transitory computer readable device from the computed reverse time migration; storing the generated raw and stacked image, in the 3D-space domain directions x, y, z of the survey region, to the memory resource by the non-transitory computer readable device; retrieving the stored raw and stacked image from the memory resource by the non-transitory computer readable device; computing a 3D Laplacian algorithm in wavenumber domains x, y, z and a 2D low-pass wavenumber filtering algorithm in lateral wavenumber domains x and y, by the non-transitory computer readable device using the retrieved raw and stacked image; generating a new image of the survey region, by the non-transitory computer readable device from the computed 3D Laplacian algorithm in the wavenumber domains x, y, z and the 2D low-pass wavenumber filtering algorithm in the lateral wavenumber domains x and y; storing the generated new image of the survey region, to the memory resource by the non-transitory computer readable device; retrieving the stored new image of the survey region, from the memory resource by the non-transitory computer readable device; converting the retrieved new image of the survey region, from a depth domain to a time domain, using the retrieved input parameter models, and an anti-aliasing filter in the time domain, by the non-transitory computer readable device; generating a depth to time converted image in the time domain of the survey region, by the non-transitory computer readable device; storing the generated depth to time converted image in the time domain of the survey region to the memory resource by the non-transitory computer readable device; retrieving the stored depth to time converted image in the time domain of the survey region from the memory resource, by the non-transitory computer readable resource; setting a maximum value of the retrieved user-defined, cut-off effective frequency band, equal to an expression f.sub.max by the non-transitory computer readable device; computing a low-pass frequency filtering of the retrieved depth to time converted image in the time domain of the survey region, using the maximum value of the user-defined, cut-off effective frequency band f.sub.max by the non-transitory computer readable device; generating a low-pass frequency filtered image in the time domain of the survey region, from the computed low-pass frequency filtering by the non-transitory computer readable device; storing the generated low-pass frequency filtered image in the time domain of the survey region, to the memory resource by the non-transitory computer readable device; retrieving the stored low-pass frequency filtered image in the time domain of the survey region from the memory resource, by the non-transitory computer readable device; converting the retrieved low-pass frequency filtered image in the time domain of the survey region from the time domain to the depth domain, using the retrieved input parameter models, and an anti-aliasing filter in space domain direction z of the survey region, by the non-transitory computer readable device; generating a final stacked image in the 3D space domain directions x, y, and z of the survey region, by the non-transitory computer readable device; storing the generated final stacked image in the 3D space directions x, y, and z of the survey region, to the memory resource, by the non-transitory computer readable device; and outputting the stored final sacked image in the 3D space directions x, y, and z of the survey region, to a display on a computer system device.

2. The computer-implemented, reverse time migration method of claim 1, wherein the set of input parameter models from the step of retrieving the source wavelet, the set of input parameter models, and the seismic data from the survey region having the space domain directions x, y, z by the non-transitory computer readable device, further comprises a velocity model in the depth interval, and anisotropy parameter models in the depth interval generated using Tomography Inversion, or Full Waveform Inversion.

3. The computer-implemented, reverse time migration method of claim 1, wherein the non-transitory computer readable device is further attached to a computer system device, for outputting to a display or a printing device the steps of storing.

4. The computer-implemented, reverse time migration method of claim 1, wherein the step of computing the integral algorithm by the non-transitory computer readable device using the retrieved source wavelet from the memory resource further comprises an expression:
s′(t)=∫.sub.−∞.sup.ts(t′)dt′.

5. The computer-implemented, reverse time migration method of claim 1, wherein the step of setting the user-defined, cut-off effective frequency band for the retrieved seismic data on the non-transitory computer readable device, further comprises the user-defined, cut-off effective frequency band between the values of 0 Hz and 250 Hz.

6. The computer-implemented, reverse time migration method of claim 1, wherein the step of generating the raw and stacked image, in the 3D-space domain directions x, y, z of the survey region by the non-transitory computer readable device from the computed reverse time migration, further comprises an expression:
P(x,y,z).

7. The computer-implemented, reverse time migration method of claim 1, wherein the step of computing the 3D Laplacian algorithm in the wavenumber domains x, y, z and the 2D low-pass wavenumber filtering algorithm in the lateral wavenumber domains x and y, by the non-transitory computer readable device using the retrieved raw and stacked image, further comprises an expression:
FT[−ΔP(x,y,z)]=(k.sub.x.sup.2+k.sub.y.sup.2+k.sub.z.sup.2){tilde over (P)}(k.sub.x,k.sub.y,k.sub.z).

8. The computer-implemented, reverse time migration method of claim 1, wherein the step of converting the retrieved new image of the survey region, from the depth domain to the time domain, using the retrieved input parameter models, and the anti-aliasing filter in the time domain, further comprises an expression: $\mathrm{dt}\le \frac{1}{2f_{\max }}\left[\left[\text{;}\right]\right].$

9. The computer-implemented, reverse time migration method of claim 1, wherein the step of converting the retrieved low-pass frequency filtered image in the time domain of the survey region from the time domain to the depth domain, using the retrieved input parameter models, and the anti-aliasing filter in the space domain direction z of the survey region, further comprises an expression: $\mathrm{dz}\le \frac{v_{\min }}{4f_{\max }}.$

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The teachings of the present invention can be readily understood by considering the following description in conjunction with the accompanying drawings.

[0041] FIG. 1, is a schematic diagram showing a cross-sectional view of an illustrative environment with points of incidence of seismic sources, seismic receivers, a well location, a wellbore, the various transmission rays, and the various angles of incidence, according to certain embodiments of the present disclosure;

[0042] FIG. 2a and FIG. 2b, are a flow chart of the computer-implemented, reverse time migration method, using 3D Laplacian operator, a low-pass wavenumber filtering in 2D-lateral space directions, and a low-pass frequency filtering in 1D-time domain, for removing low frequency and low wavenumber noises to generate an enhanced image, according to certain embodiments of the present disclosure;

[0043] FIG. 3, is an electric diagram, in block form of a digital high-performance computing system programmed to perform the computer-implemented, reverse time migration method, using 3D Laplacian operator, a low-pass wavenumber filtering in 2D-lateral space directions, and a low-pass frequency filtering in 1D-time domain, for removing low frequency and low wavenumber noises to generate an enhanced image, according to certain embodiments of the present disclosure; and

[0044] FIG. 4, illustrates a graphic user interface of the computer-implemented, reverse time migration method, according to certain embodiments of the present disclosure.

DETAILED DESCRIPTION OF THE INVENTION

[0045] Reference will now be made in detail, to several embodiments of the present disclosures, examples of which, are illustrated in the accompanying figures. It is noted that wherever practicable similar or like reference symbols may be used in the figures and may indicate similar or like functionality. The figures depict embodiments of the present disclosure, for purposes of illustration only. One skilled in the art will readily recognize from the following description that alternative embodiments of the structures, systems, and methods illustrated therein may be employed without departing from the principles of the disclosure described herein.

[0046] As legacy reverse time migration methods usually perform low-pass k-filtering directly in the depth z direction, and never use any information regarding velocity variations (they implicitly assume that all velocities are constant in all three spatial (x, y, z) directions), these methods are not capable of containing the image's frequency contents within the exact range of a user required frequency variable of fmax anywhere from shallow to deep. As such, these methods require the user to do endless “trial and see” empirical calculations to conclude a proper k-filtering high-cut parameter in z direction. In the end, this may cause that even a person having ordinary skills in the art, could end up damaging the image's spectrum. Thus, the relevancy of the innovative computer-implemented method herewith disclosed.

[0047] FIG. 1 a cross-sectional view of a portion of the earth over the survey region, 101, in which the preferred embodiment of the present invention is useful. It is important to note, that the survey region 101 of FIG. 1 is a land-based region represented as 102. Persons of ordinary skill in the art, will recognize that seismic survey regions produce detailed images of local geology in order to determine the location and size of possible hydrocarbon (oil and gas) reservoirs, and therefore a well location 103. In these survey regions, sound waves bounce off underground rock formations during blasts at various points of incidence 104, and the waves that reflect back to the surface are captured by seismic data recording sensors, 105, transmitted by data transmission systems, 305, wirelessly, 303, from said sensors, 105, then stored for later processing to a memory resource 304, and processed by a non-transitory computer readable device 306, that is controlled via a computer system device 307 of FIG. 3.

[0048] In FIG. 1, the cross-sectional view of a portion of the earth over the survey region is illustrates different types of earth formation, 102, 203, 204, which will comprise the seismic survey data in the present invention. In particular, persons having ordinary skill in the art will soon realize that the present example shows a common midpoint-style gather, where seismic data traces are sorted by surface geometry to approximate a single reflection point in the earth. In this example, data from several shots and receivers may be combined into a single image gather, or used individually depending upon the type of analysis to be performed. Although the present example may illustrate a flat reflector and a respective image gather class, other types or classes of image gathers known in the art maybe used, and its selection may depend upon the presence of various earth conditions or events.

[0049] Furthermore, as shown on FIG. 1, the seismic energy from the multiple points of incidence or sources 104, will be reflected from the interface between the different earth formations. These reflections will then be captured by multiple seismic data recording receiving sensors 105, each of which will be placed at different location offsets 110 from each other, and the well 103. Because all points of incidences 104, and all seismic data recording sensors 105 are placed at different offsets 110, the survey seismic data or traces, also known in the art as gathers, will be recorded at various angles of incidence represented by 108. The points of incidence 104 generate downward transmission rays 105, in the earth that are captured by their upward transmission reflection through the recording sensors 105. Well location 103, in this example, is illustrated with an existing drilled well attached to a wellbore, 109, along which multiple measurements are obtained using techniques known in the art. This wellbore 109, is used to obtain source information like wavelets, as well as well log data, that includes P-wave velocity, S-wave velocity, Density, among other seismic data. Other sensors, not depicted in FIG. 1, are placed within the survey region 101 to also capture horizons data information required for interpreters and persons of ordinary skilled in the art to perform various geophysical analysis. In the present example, the gathers will be sorted from field records in order to examine the dependence of amplitude, signal-to-noise, move-out, frequency content, phase, and other seismic attributes, on incidence angles 108, offset measurements 110, azimuth, and other geometric attributes that are important for data processing and imaging, and known by persons having ordinary skills in the art.

[0050] Although shots 104, are represented in FIG. 1 as a common-mid-point shot geometry, with shot lines mostly running horizontally, a person having ordinary skills in the art, would soon realize that said pattern could easily be represented in other ways, such as vertically, diagonally or a combination of the three which would in turn produce a different shot geometry. Nevertheless, because of operating conditions, uniform coverage of receiving sensors 105 for uniform acquisition of wavelets 203, input parameter models 204, and seismic data 205 as shown in FIG. 1, is usually not achievable over the entire survey area.

[0051] With regards to FIG. 2a and FIG. 2b, they illustrate a flow chart with an overview of the preferred embodiment of the invention. The retrieving phase 202 initiates the process and comprises obtaining and preparing data and information from the survey region. In particular, three different types of inputs are retrieved from the survey region which comprise: 1) a set of wavelets 203 originated from the energy generated at the points of incidence 104; 2) a set of input parameter models 204 further comprising a velocity model in depth interval, as well as an anisotropy parameter models in depth interval, both generated using Tomography Inversion, or Full Waveform Inversion. Persons skilled in the art would soon recognize that these models can an include epsilon model in depth interval, a delta model in depth interval, a dip angle model in depth interval, an azimuthal angle model in depth interval, among others; and 3) seismic data 205 obtained directly from the survey region 101 by the receiving sensors 105, which includes 2D and 3D subsurface structure data such as reflection, shear wave, and refraction. Said retrieving phase 202 is performed by the non-transitory computer readable device 306, and then stored at 206, to the memory resource 304 for later processing and analysis by the digital high-performance computing system of FIG. 3.

[0052] The non-transitory computer readable device 306, then receives a message hook to initiate the retrieval process 207 from the memory resource 304 of the data 203, 204, and 205. The non-transitory computer readable device 306, computes at 208 the pre-programmed algorithm of performing the integral computation over the source wavelet 203, using formula:

s′(t)=∫.sub.−∞.sup.ts(t′)dt′  (9)

[0053] This pre-migration processing step 208 is essential to guarantee an undistorted the migrated spectrum. This step is not for producing a true amplitude RTM angle gather, but rather related to the Laplacian application of the present embodiment. Upon completion of the algorithm computation, the non-transitory computer readable device 306 generates a new source wavelet at 209, that it is later sent to the memory resource 304 for storage at step 210. Upon successfully storing the new source wavelet 209, the memory resource 304 issues a message hook procedure to the non-transitory computer readable device 306, for the computer system 307 to display through a user-interface, on display 309, a message that indicates to the end user that the system computer, 307, is ready to receive the user-defined cut-off effective frequency band values. At such point, a user of the computer-implement method such as a person having ordinary skills in the art sets at 211 a cut-off effective frequency band value in the range of the effective frequency band of the input data 203, 204, and 205, using a combination of the computer system device inputs such as keyboard 310 and mouse 311. More precisely, said values range from 0 Hz to 250 Hz. Once said values are set, the use will confirm through a message dialog displayed on 309, which will send a message to the non-transitory computer readable device 306, to store at step 212 the set user-defined cut-off effective frequency band to the memory resource 304. The non-transitory computer readable device 306, then retrieves at 213 the set user-defined cut-off effective frequency band, the new source wavelet, the input parameters 204, and the seismic data 205 from the memory resource 304 and begins computing the reverse time migration algorithm at step 214. Upon processing the step of reverse time migration computation 214, the non-transitory computer readable device 306, generates at step 215 a raw and stacked image, in 3D-space domain directions x, y, z of the survey region. Said generated image is then stored at step 216 to the memory resource 304 by the non-transitory computer readable device 306. Upon successfully completing the storage 216, the memory resource 304 messages the non-transitory computer readable device 306 to initiate the retrieval 217 of the stored raw and stacked image from the memory resource 304 for computing a 3D Laplacian algorithm in wavenumber domains x, y, z and a 2D low-pass wavenumber filtering algorithm in lateral wavenumber domains x and y at step 218. The 3D Laplacian algorithm performed at step 218 is defined in programming language in space domain, where P(x, y, z) is the stacked image generated at step 215 comprising of the following formula:

[00006]$\begin{array}{cc}\Delta P\left(x,y,z\right)=\frac{{\partial }^{2}P}{\partial x^2}+\frac{{\partial }^{2}P}{\partial y^2}+\frac{{\partial }^{2}P}{\partial z^2}& \left(10\right)\end{array}$

[0054] Furthermore, at step 218 the algorithm is also programmed to compute the Fast Fourier Transform (FFT) FT[ΔP(x, y, z)] in wavenumber domain as well, using {tilde over (P)}(k.sub.x, k.sub.y, k.sub.z) instead, which is the Fourier transform of P(x, y, z); and k.sub.x, k.sub.y, k.sub.z are the wavenumbers in x, y, z direction, respectively; represented by the following formula:

FT[ΔP(x,y,z)]=−(k.sub.x.sup.2+k.sub.y.sup.2+k.sub.z.sup.2){tilde over (P)}(k.sub.x,k.sub.y,k.sub.z)  (11)

[0055] On the other hand, at step 218 the 2D low-pass wavenumber filtering algorithm in space domain (also referred to as k-filtering) is only done in lateral (x, y) directions, unlike other methods in the industry that do it in all directions. The non-transitory computer readable device 306 then at step 219 generates a new image of the survey region in wavenumber domains x, y, z and a 2D low-pass wavenumber filtering algorithm in lateral wavenumber domains x and y, and sends it to the memory resource 304 for storage at step 220. Upon successfully completing the step of storing the new image, the memory resource 304, signals the non-transitory computer readable device 306, to begin the retrieval process of the new image at step 221. With the image already retrieved, the non-transitory computer readable device 306, converts at step 222 the image from depth to time domain using an anti-aliasing operator to a sampling rate in time, and gives the high frequency seismic trace result which can be reached with the given sampling rate. This conversion step 222 takes the depth z direction, and converts it into the time domain using the velocity model from the input parameters 204, and expression:

[00007]$\begin{array}{cc}\mathrm{dt}\le \frac{1}{2f_{\max }}& \left(12\right)\end{array}$

[0056] The non-transitory computer readable device 306 then generates at step 223 the converted image in time domain for the depth z direction. The non-transitory computer readable device 306 then stores at step 224 the generated image with depth z direction converted to time domain to the memory resource 304. Upon successfully completing the step 224 of storing the converted image in time domain for the depth z direction, the memory resource 304, signals the non-transitory computer readable device 306, to begin the retrieval process of the converted image in time domain for the depth z direction at step 225. The non-transitory computer readable device 306, then signals to computer system device 307 to display on monitor 309 a programmed graphic user interface that indicates the user, typically a person having ordinary skills in the art, to confirm that the maximum value of the retrieved user-defined, cut-off effective frequency band previously mentioned as a number between the range of 0 Hz and 250 Hz, was set, and proceeds at step 226 to set the maximum value of the retrieved user-defined, cut-off effective frequency band equal to the expression f.sub.max. The non-transitory computer readable device 306, then initiates the computing a low-pass frequency filtering at step 227, using the set maximum value of the user-defined, cut-off effective frequency band f.sub.max of step 226. In this way, the computer-implemented method utilizes the velocity information, to exactly contain and keep intact, within the set range the image's frequency contents, all the way from the seismic image's shallow to its deepest part. As such, and during step 227 the non-transitory computer readable device 306, automatically realizes the frequency contents' adaptability to the velocity's vertical variations along depth z direction and generates a low-pass frequency filtered image in time domain of the survey region, from the computed low-pass frequency filtering at step 228. The non-transitory computer readable device 306 then stores at step 229 the generated low-pass frequency filtered image in time domain of the survey region to the memory resource 304, and upon successfully completing step 229 of storing the generated low-pass frequency filtered image in time domain of the survey region; the memory resource 304 signals the non-transitory computer readable device 306, to begin the retrieval process of the generated low-pass frequency filtered image in time domain of the survey region at step 230.

[0057] With the image already retrieved, the non-transitory computer readable device 306, converts at step 231 the image from time to depth domain using an anti-aliasing operator to the same sampling rate in time used at step 222, and gives the high frequency seismic trace result which can be reached with the given sampling rate. This conversion step 231 takes the depth z direction, and converts it back into the depth domain using the velocity model from the input parameters 204, and the expression:

[00008]$\begin{array}{cc}\mathrm{dz}\le \frac{v_{\min }}{4f_{\max }}& \left(13\right)\end{array}$

[0058] The non-transitory computer readable device 306 then generates at step 232 a final stacked image in in 3D space domain directions x, y, and z of the survey region. The non-transitory computer readable device 306 then stores at step 232 the final stacked image in in 3D space domain directions x, y, and z of the survey region to the memory resource 304. Upon successful storage of the final stacked image in in 3D space domain directions x, y, and z of the survey region, the memory resource 304 signal the non-transitory computer readable device 306 to display in computer system's 307 display monitor 309 an indication that the computer-implemented, reverse time migration method, using 3D Laplacian operator, a low-pass wavenumber filtering in 2D-lateral space directions, and a low-pass frequency filtering in 1D-time domain, for removing low frequency and low wavenumber noises to generate an enhanced image has been completed.

[0059] As it pertains to FIG. 3, it illustrates a functional block diagram of a digital high-performance computing system programmed to perform the computer-implemented, reverse time migration method, using 3D Laplacian operator, a low-pass wavenumber filtering in 2D-lateral space directions, and a low-pass frequency filtering in 1D-time domain, for removing low frequency and low wavenumber noises to generate an enhanced image, 301. The digital high-performance computing system, 301, further incorporates (wired and/or wirelessly) memory resources, 304, for storing data transmitted from the receiving sensors 105, transmitted wirelessly as represented by 303, using transmission systems, 305, as well as a non-transitory program computer readable device, 306, and a computer system device, 307.

[0060] The computer system device, 307, acts as a user interface to the non-transitory program computer readable device, 306; to input, set, select, and perform the operations of retrieving, computing, generating, invoking, determining, converting, and correcting functions (the message hook procedures). Said computer system device, 307, is connected to (wired and/or wirelessly) to the non-transitory program computer readable device 306. The computer system device, 307, further includes other devices like a central processing unit (CPU), 308, a display or monitor, 309, a keyboard, 310, a mouse, 311, and a printer, 312.

[0061] The digital high-performance computing system, 301, has firmware, a kernel and a software providing for the connection and interoperability of the multiple connected devices, like the memory resources for storing data, 304, the telemetry system 305, the non-transitory program computer readable memory device, 306, and the computer system device, 307. The digital high-performance computing system, 301, includes an operating system, a set of message hook procedures, and a system application.

[0062] Furthermore, because performance is the always important issue, the digital high-performance computing system device, 301, uses the non-transitory program computer readable memory device, 306 to ensure that the beam migration steps will not be bottlenecked by the digital high-performance computing system 301 I/O, or any network communications. In fact, Apache Hadoop distributed filesystem and proper data-compressions, as well as smart file caching according to the data will ensure that the computer-implemented method is only limited by the memory/cache speed and CPU computing power, and nothing else.

[0063] The operating system embedded within the digital high-performance computing system 301, may be a Microsoft “WINDOWS” operating system, OS/2 from IBM Corporation, UNIX, LINUX, Sun Microsystems, or Apple operating systems, as well as myriad embedded application operating systems, such as are available from Wind River, Inc.

[0064] The message hook procedures of digital high-performance computing system 301 may, for example, represent an operation or command of the memory resources, 304, the computer system device, 307, the non-transitory program computer device, 306, which may be currently executing a certain step, process, or subroutine from the computer-implemented, reverse time migration method, using 3D Laplacian operator, a low-pass wavenumber filtering in 2D-lateral space directions, and a low-pass frequency filtering in 1D-time domain, for removing low frequency and low wavenumber noises to generate an enhanced image.

[0065] The set of message hook procedures may be first initiated by an input from: the user, like the entering of user-defined values or parameters; the manipulation of the computer system device, 307; the processing of operations in the non-transitory program computer readable memory device storage, 306; or automatically once certain data has been stored or retrieved by either the memory resources, 304, or the non-transitory program computer readable memory device storage, 306. Based on any of these inputs, processes or manipulation events, the memory resources, 304, the non-transitory program computer readable memory storage device, 306, or the computer system device, 307; generate a data packet that is passed to the digital high-performance computing system, 301, which are indicative of the event that has occurred as well as the event that needs to occur. When digital high-performance computing system, 301, receives the data packet, it converts it into a message based on the event, and executes the required step of the computer-implement method. The computer-implement method includes a set of message hook lists that identifies the series of message hook procedures. When the operating system receives the message, it examines the message hook list to determine if any message hook procedures have registered themselves with the operating system. If at least one message hook procedure has registered itself with the operating system, the operating system passes the message to the registered message hook procedure that appears first on the list. The called message hook executes and returns a value that instructs the digital high-performance computing system, 301, to pass the message to the next registered message hook at either 304, 306 or 307. The digital high-performance computing system, 301, continues executing the operations until all registered message hooks have passed, which indicates the completion of the method by the identification of magnetic inference.

[0066] According the preferred embodiment of the present invention, certain hardware, and software descriptions were detailed, merely as example embodiments and are not to limit the structure of implementation of the disclosed embodiments. For example, although many internal, and external components of the receiving system apparatus of FIG. 3 have been described, those with ordinary skills in the art will appreciate that such components and their interconnection are well known. Additionally, certain aspects of the disclosed invention may be embodied in software that is executed using one or more, receiving systems, computers systems devices, or non-transitory computer readable memory devices. Program aspects of the technology may be thought of as “products” or “articles of manufacture” typically in the form of executable code and/or associated data that is carried on, or embodied in, a type of machine readable medium. Tangible non-transitory “storage” type media and devices include any or all memory or other storage for the computers, process or the like, or associated modules thereof such as various semiconductor memories, tape drives, disk drives, optical or magnetic disks, and the like which may provide storage at any time for the software programming.

[0067] As it pertains to FIG. 4, it illustrates a graphic user interface of the computer-implemented, reverse time migration method as it is displayed on monitor 309 of the computer system 307 for various of the aforementioned parameters.

[0068] As used herein the term “survey region” refers to an area or volume of geologic interest, and may be associated with the geometry, attitude and arrangement of the area or volume at any measurement scale. A region may have characteristics such as folding, faulting, cooling, unloading, and/or fracturing that has occurred therein.

[0069] As used herein, the term “computing” encompasses a wide variety of actions, including calculating, determining, processing, deriving, investigation, look ups (e.g. looking up in a table, a database, or another data structure), ascertaining and the like. It may also include receiving (e.g. receiving information), accessing (e.g. accessing data in a memory) and the like. Also, “computing” may include resolving, selecting, choosing, establishing, and the like.

[0070] As used herein, “subsurface”, and “subterranean” means beneath the top surface of any mass of land at any elevation or over a range of elevations, whether above, below or at sea level, and/or beneath the floor surface of any mass of water, whether above, below or at sea level.

[0071] Unless specifically stated otherwise, terms such as “defining”, “creating”, “including”, “representing”, “pre-analyzing”, “pre-defining”, “choosing”, “building”, “assigning”, “creating”, “introducing”, “eliminating”, “re-meshing”, “integrating”, “discovering”, “performing”, “predicting”, “determining”, “inputting”, “outputting”, “identifying”, “analyzing”, “using”, “assigning”, “disturbing”, “increasing”, “adjusting”, “incorporating”, “simulating”, “decreasing”, “distributing”, “specifying”, “extracting”, “displaying”, “executing”, “implementing”, and “managing”, or the like, may refer to the action and processes of a retrieving system, or other electronic device, that transforms data represented as physical (electronic, magnetic, or optical) quantities within some electrical device's storage, like memory resources, or non-transitory computer readable memory, into other data similarly represented as physical quantities within the storage, or in transmission or display devices.

[0072] Embodiments disclosed herein also relate to computer-implemented system, used as part of the retrieving system for performing the operations herein. This system may be specially constructed for the required purposes, or it may comprise a general-purpose computer selectively activated or reconfigured by a computer program or code stored in the memory resources, or non-transitory computer readable memory. As such, the computer program or code may be stored or encoded in a computer readable medium or implemented over some type of transmission medium. A computer-readable medium includes any medium or mechanism for storing or transmitting information in a form readable by a machine, such as a computer (‘machine’ and ‘computer’ may be used synonymously herein). As a non-limiting example, a computer-readable medium may include a computer-readable storage medium (e.g., read only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices, etc.). A transmission medium may be twisted wire pairs, coaxial cable, optical fiber, or some other suitable wired or wireless transmission medium, for transmitting signals such as electrical, optical, acoustical, or other form of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.)).

[0073] A receiving system or sensor 105 as used herein, typically includes at least hardware capable of executing machine readable instructions, as well as the software for executing acts (typically machine-readable instructions) that produce a desired result. In addition, a retrieving system may include hybrids of hardware and software, as well as computer sub-systems.

[0074] Hardware generally includes at least processor-capable platforms, such as client-machines (also known as servers), and hand-held processing devices (for example smart phones, personal digital assistants (PDAs), or personal computing devices (PCDs)). Further, hardware may include any physical device that can store machine-readable instructions, such as memory or other data storage devices. Other forms of hardware include hardware sub-systems, including transfer devices such as modems, modem cards, ports, and port cards, for example.

[0075] Software includes any machine code stored in any memory medium, such as RAM or ROM, and machine code stored on other devices (such as non-transitory computer readable media like external hard drives, or flash memory, for example). Software may include source or object code, encompassing any set of instructions capable of being executed in a client machine, server machine, remote desktop, or terminal.

[0076] Combinations of software and hardware could also be used for providing enhanced functionality and performance for certain embodiments of the disclosed invention. One example is to directly manufacture software functions into a silicon chip. Accordingly, it should be understood that combinations of hardware and software are also included within the definition of a retrieving system and are thus envisioned by the invention as possible equivalent structures and equivalent methods.

[0077] Computer-readable mediums or memory resources include passive data storage, such as a random-access memory (RAM) as well as semi-permanent data storage such as external hard drives, and external databases, for example. In addition, an embodiment of the invention may be embodied in the RAM of a computer to transform a standard computer into a new specific computing machine.

[0078] Data structures are defined organizations of data that may enable an embodiment of the invention. For example, a data structure may provide an organization of data, or an organization of executable code. Data signals could be carried across non-transitory transmission mediums and stored and transported across various data structures, and, thus, may be used to transport an embodiment of the invention.

[0079] The system computer may be designed to work on any specific architecture. For example, the system may be executed on a high-performance computing system, which typically comprise the aggregation of multiple single computers, physically connected, or connected over local area networks, client-server networks, wide area networks, internets, hand-held and other portable and wireless devices, and networks.

[0080] An “output device” includes the direct act that causes generating, as well as any indirect act that facilitates generation. Indirect acts include providing software to a user, maintaining a website through which a user is enabled to affect a display, hyperlinking to such a website, or cooperating or partnering with an entity who performs such direct or indirect acts. Thus, a user may operate alone or in cooperation with a third-party vendor to enable the reference signal to be generated on a display device. A display device may be included as an output device, and shall be suitable for displaying the required information, such as without limitation a CRT monitor, an LCD monitor, a plasma device, a flat panel device, or printer. The display device may include a device which has been calibrated through the use of any conventional software intended to be used in evaluating, correcting, and/or improving display results (e.g., a color monitor that has been adjusted using monitor calibration software). Rather than (or in addition to) displaying the reference image on a display device, a method, consistent with the invention, may include providing a reference image to a subject. “Providing a reference image” may include creating or distributing the reference image to the subject by physical, telephonic, or electronic delivery, providing access over a network to the reference, or creating or distributing software to the subject configured to run on the subject's workstation or computer including the reference image. In one example, providing of the reference image could involve enabling the subject to obtain the reference image in hard copy form via a printer. For example, information, software, and/or instructions could be transmitted (e.g., electronically or physically via a data storage device or hard copy) and/or otherwise made available (e.g., via a network) in order to facilitate the subject using a printer to print a hard copy form of reference image. In such an example, the printer may be a printer which has been calibrated through the use of any conventional software intended to be used in evaluating, correcting, and/or improving printing results (e.g., a color printer that has been adjusted using color correction software).

[0081] A database, or multiple databases may comprise any standard or proprietary database software, such as Oracle, Microsoft Access, SyBase, or DBase II, for example. The database may have fields, records, data, and other database elements that may be associated through database specific software. Additionally, data may be mapped. Mapping is the process of associating one data entry with another data entry. For example, the data contained in the location of a character file can be mapped to a field in a second table. The physical location of the database is not limiting, and the database may be distributed. For example, the database may exist remotely from the server, and run on a separate platform. Further, the database may be accessible across a local network, a wireless network of the Internet.

[0082] Furthermore, modules, features, attributes, methodologies, and other aspects can be implemented as software, hardware, firmware, or any combination thereof. Wherever a component of the invention is implemented as software, the component can be implemented as a standalone program, as part of a larger program, as a plurality of separate programs, as a statically or dynamically linked library, as a kernel loadable module, as a device driver, and/or in every and any other way known now or in the future to those of skill in the art of computer programming. Additionally, the invention is not limited to implementation in any specific operating system or environment.

[0083] Various terms as used herein are defined below. To the extent a term used in a claim is not defined below, it should be given the broadest possible definition persons in the pertinent art have given that term as reflected in at least one printed publication or issued patent.

[0084] As used herein, “and/or” placed between a first entity and a second entity means one of (1) the first entity, (2) the second entity, and (3) the first entity and the second entity. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined

[0085] Additionally, the flowcharts and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the Figures. For examples, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowcharts illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified hardware functions or acts, or combinations of special purpose hardware and computer instructions.

[0086] While in the foregoing specification this disclosure has been described in relation to certain preferred embodiments thereof, and many details have been set forth for purpose of illustration, the invention is not to be unduly limited to the foregoing which has been set forth for illustrative purposes. On the contrary, a wide variety of modifications and alternative embodiments will be apparent to a person skilled in the art, without departing from the true scope of the invention, as defined in the claims set forth below. Additionally, it should be appreciated that structural features or method steps shown or described in any one embodiment herein can be used in other embodiments as well.