Equal frequency ratio diagrams

Abstract

FIELD: geophysics.SUBSTANCE: invention relates to methods and systems for creating equal frequency ratio diagrams. Methods, systems, and a machine-readable medium are described for performing operations that include: spectral decomposition of seismic data related to a subsurface area of interest into a number of equal-frequency cubes; selecting a low-frequency cube and a high-frequency cube from a number of equal-frequency cubes; dividing the low-frequency cube by the high-frequency cube to create a frequency ratio cube for the subsurface area of interest; establishing a time-depth relationship in the subsurface area of interest; extracting an equal-frequency ratio diagram in the subsurface area of interest based on the time-depth relationship and the frequency ratio cube; and using the equal-frequency ratio diagram to identify a gas reservoir in the subsurface area of interest.EFFECT: increase in the accuracy and informativeness of the data obtained.14 cl, 5 dwg

Description

Statement of Priority

[0001] This application claims the benefit of U.S. Patent Application No. 17 / 655,925, filed March 22, 2022, which is incorporated herein by reference in its entirety. Field of the Invention

[0002] The present disclosure relates to methods and systems for generating equal frequency ratio diagrams.Background Art of the Present Invention

[0003] Many modern gas detection methods are based on seismic reflection amplitude analysis. However, reflection amplitude is affected by numerous variables, including lithology, porosity, and saturation characteristics of geological formations. Given the number of variables affecting reflection amplitude, it is difficult to accurately and reliably determine any one of these variables from reflection amplitudes, especially when it comes to liquid or gas content. Summary of the Invention

[0004] This document describes methods and systems, including computer-implemented methods, computer software products, and computer systems for determining the locations of gas-bearing intervals in subterranean reservoirs.The aspects of the subject matter described in this document may be implemented in methods that include: spectrally decomposing seismic data related to a subsurface region of interest into a number of equal frequency cubes; selecting a low frequency cube and a high frequency cube from the number of equal frequency cubes; dividing the low frequency cube by the high frequency cube to create a frequency ratio cube for the subsurface region of interest; establishing a time-depth relationship in the subsurface region of interest; obtaining an equal frequency ratio diagram in the subsurface region of interest based on the time-depth relationship and the frequency ratio cube; and using the equal frequency ratio diagram to identify an underground gas reservoir in the subsurface region of interest.

[0005] The previously described embodiment can be implemented using a computer, a non-volatile computer-readable storage medium that stores computer-readable instructions for implementing a method performed on the computer, and a computer system comprising a computer memory that interacts with a hardware processor designed to implement a method performed on the computer or instructions stored on a non-volatile computer-readable medium. These and other embodiments may optionally include one or more features.

[0006] According to some embodiments, establishing a time-depth relationship in a subsurface area of ​​interest includes: obtaining one or more well logs measured in one or more drilled wells near the subsurface area of ​​interest; and establishing a time-depth relationship in the subsurface area of ​​interest based on the one or more well logs.

[0007] According to some embodiments, one or more well logs comprise at least one of the following: an acoustic well log (AL), a vertical seismic profiling (VSP), or a seismic well log.

[0008] According to some embodiments, obtaining an equal frequency ratio diagram in a subsurface region under study based on a time-depth relationship and a frequency ratio cube includes: applying the time-depth relationship to establish a correspondence between depth information in the subsurface region under study and the frequency ratio cube; and obtaining an equal frequency ratio diagram from the frequency ratio cube in the subsurface region under study.

[0009] According to some embodiments, the seismic data is a three-dimensional cube of relative amplitude preserved (RAP) seismic data after pre-stack time migration (PSTM).

[0010] According to some embodiments, using an equal frequency ratio diagram to identify a gas-bearing formation in a subsurface area of ​​interest includes: identifying high amplitude-to-frequency ratio values ​​on the equal frequency ratio diagram; assigning the area associated with the high amplitude-to-frequency ratio to a subsurface gas reservoir.

[0011] According to some embodiments, classifying an area associated with a high amplitude-to-frequency ratio as a subsurface gas reservoir includes: determining whether the high amplitude-to-frequency ratio is greater than a threshold frequency ratio; and in response to determining that the high amplitude-to-frequency ratio is above the threshold frequency ratio, determining that the high amplitude-to-frequency ratio indicates a gas-bearing area.

[0012] According to some embodiments, the method 300 further includes: displaying an equal frequency ratio diagram in a graphical user interface (GUI) on a visualization device. This graphical representation of the diagram can be used to visually indicate locations that contain gas. According to some embodiments, this display can be used to determine the location of potential drilling sites or to determine the lateral extent of a reservoir formation. According to another example, the method 300 can further include drilling at one or more locations where gas is present. This step can include transmitting information indicating one or more locations to a drilling control unit (e.g., a computing device). Based on the received information, the control unit can control the drilling equipment to drill at one or more locations.

[0013] Specific embodiments of the subject matter described in this specification can be implemented to improve seismic methods for detecting gas reservoirs. The described methods and systems enable the creation of logs that facilitate reservoir interpretation and eliminate the need for additional geophysical instruments or additional costs. For example, the described methods and systems enable the creation of a virtual equal-frequency ratio log in an input seismic cube along a specified well trajectory. The virtual equal-frequency ratio log is created using various reliable and accurate data sources, such as sonic logs, seismic logs, and vertical seismic profiles. Thus, unlike existing solutions, the described methods and systems enable the creation of logs without the use of inaccurate velocity cubes.This allows for the creation of more accurate diagrams and more efficiently (for example, in less time and with less computing power) than existing solutions. Furthermore, the described methods and systems are effective because they enable correlations with the results of previously drilled wells, eliminating the need for geophysical instruments.

[0014] Furthermore, logs generated using the described methods and systems can be used to identify gas fluid types and / or gas-bearing intervals. These improved methods provide a more accurate representation of gas reservoir locations than currently achievable in practice. Furthermore, these improved methods improve the accuracy of drilling operations for gas production in the studied area. Furthermore, these improved methods allow for improved vertical and horizontal well placement to more accurately characterize the gas reservoir. Furthermore, these improved methods reduce the risk of drilling wells with high water saturations and optimize the drilling of gas production wells, thereby increasing the efficiency of financial, time, and effort.

[0015] The accompanying drawings and description below provide detailed information on one or more embodiments of these systems and methods. Other features, objects, and advantages of these systems and methods will become apparent from the description, drawings, and claims. Brief Description of the Figures

[0016] Fig. 1 is a simplified flow chart of an example of a sequence of actions for directly detecting a gas reservoir according to some embodiments of the present invention.

[0017] Fig. 2 shows an example of diagrams generated for three wells according to some embodiments of the present invention.

[0018] Fig. 3 is a flow chart of an example of a method according to some embodiments of the present invention.

[0019] Fig. Fig. 4 shows an example of a seismic survey according to some embodiments of the present invention.

[0020] Fig. 5 is a block diagram of an example computer system that is used to provide computing functionality associated with the described algorithms, methods, functions, procedures, flows and processes according to some embodiments of the present disclosure.

[0021] The same reference numbers and designations in different figures indicate the same elements. Detailed disclosure of the present invention

[0022] The following is a detailed description of systems and methods for improving seismic gas detection methods, which allows one skilled in the art to make and use the described subject matter in connection with one or more specific embodiments. Various modifications, changes, and combinations of the described embodiments are possible; they will be obvious to those skilled in the art, and the stated general principles can be applied to other embodiments and applications within the scope of the present invention. Accordingly, the present disclosure is not limited to the described or illustrated embodiments and has a wide scope of application in accordance with the described principles and characteristics.

[0023] According to scattering theory, a gas-containing geological formation causes attenuation of the energy of seismic waves passing through it, especially the high-frequency components of these waves. As a result of the strong attenuation of high frequencies in a geological formation, areas underlying gas-containing geological formations reflect anomalously low frequencies. These low frequencies are called seismic shadows, and the areas where seismic shadows occur are called shadow zones. Due to their characteristic properties, seismic shadows are commonly used as direct indicators of hydrocarbons. For example, seismic shadows have been detected by identifying spectral differences in seismic data obtained above and below the shadow zone.

[0024] However, in some cases, due to variations in gas reservoir thickness, the gas does not attenuate the energy of seismic waves passing through the reservoir. In such cases, seismic shadows are not a reliable indicator of gas presence. Other limitations of using seismic shadows include the fact that loose sands and porous sandstone have frequency responses similar to seismic shadows. Furthermore, other types of formations, such as shallow gas accumulations and gas pipes, also have seismic shadows.

[0025] Recently, spectral decomposition has been used to decompose seismic data into a range of frequencies. This procedure produces frequency cubes of specific frequencies. The spectral decomposition result is influenced by many factors, including effective attenuation, fluid type, thickness, and stratigraphy of the studied interval. Among these, fluid type is one of the most important factors affecting the frequency response. For example, the presence of gas in the reservoir can affect different frequency ranges differently. Specifically, the response to the presence of gas has opposite effects on the high- and low-frequency cubes. In the studied interval containing gas in the reservoir, the high-frequency cube exhibits low amplitude, while at the same location in the interval, the low-frequency cube exhibits high amplitude. Furthermore, the presence of gas has different effects on the attenuation of high and low frequencies.The presence of gas does not increase the amplitude at low frequencies. However, the presence of gas attenuates the amplitude at high frequencies. Given the potential of frequency response for detecting gas intervals, it is desirable to develop solutions for detecting gas-bearing intervals based on frequency response.

[0026] This document describes methods and systems for locating gas-bearing intervals in subsurface reservoirs. According to one embodiment, the methods and systems enable the creation of a virtual equal frequency ratio diagram (EFR) that is used to locate hydrocarbons and characterize reservoirs in a field. As described below, the EFR is created using various reliable and accurate data sources, such as sonic logs, seismic logs, and vertical seismic profiles (VSPs). As described in more detail below, the EFR enables correlations to be obtained with results from previously drilled wells, eliminating the need for geophysical tools.

[0027] Fig. 1 shows a simplified flow chart of an example of a sequence 100 of actions for directly detecting a gas reservoir according to some embodiments. The example sequence 100 of actions allows for the creation of a virtual equal frequency ratio diagram, which can be used to detect hydrocarbons (e.g., gas) and characterize reservoir formations in a study area in a field. As described in more detail below, the sequence 100 of actions allows for the creation of an equal frequency ratio diagram using diagrams that are obtained in wells drilled in a reservoir formation. According to one example, the sequence 100 of actions can be performed using a computer system. Fig. 5 shows an example of a computer system.

[0028] The sequence of actions 100 begins with a step 102 of obtaining three-dimensional (3D) seismic data cubes. According to one example, the three-dimensional seismic data cube is obtained from a computing device that is different from the computing device executing the sequence of actions 100. According to one example, the three-dimensional seismic data cube is created using the same computing device or system that executes the sequence of actions 100. Fig. 4 shows an example of a seismic survey during which seismic data is created.

[0029] According to one example, a 3D seismic data cube is a 3D seismic data cube processed with relative amplitude preservation (RAP) after prestack time migration (PSTM) with noise and multiple suppression. The main goals of seismic data processing with amplitude preservation are: 1) widening the frequency spectrum, 2) preserving low frequencies and relative amplitudes, and 3) attenuating characteristic multiple spikes at the studied reservoir levels. These goals allow for the production of ideal seismic data for qualitative and quantitative stratigraphic interpretation, which includes representing the true reflectivity of the Earth, maintaining sufficient correlation with well data, and preserving the full frequency range.The seismic stratigraphic interpretation procedure used includes high-frequency mixed noise removal, low-frequency random noise suppression, surface multiple suppression, surface-consistent deconvolution, velocity analysis, 3D pre-stack time migration, integrated multiple suppression graph, and post-stack processing.

[0030] At step 104, the sequence of actions 100 includes creating a number of spectral decomposition cubes with equal frequencies. Generally, each seismic trace in a three-dimensional seismic data cube contains a wide range of combined frequencies. According to one embodiment, a number of equal frequency cubes can be created by decomposing, decomposing, or dividing the three-dimensional seismic data cube into several wavelets of a base frequency range, and sorting the wavelets into groups of seismic frequencies. According to one example, equal frequency cubes in the range of 10 to 40 Hz are created in 10 Hz increments. Other frequency ranges are also possible. The selected frequency range can depend on wide- or narrow-band amplitude variations in the subsurface reservoir at the locations being studied.For example, if the reservoirs being studied are at shallower depths, then a frequency range of 30-60 Hz is appropriate, since shallow reservoirs contain higher frequencies than deep reservoirs.

[0031] At step 106, the sequence of actions 100 includes selecting a low-frequency equal-frequency cube from one of the equal-frequency spectral decomposition cubes. For example, the selected low-frequency cube is a cube in which the frequency amplitudes at gas reservoir locations are much higher than the frequency amplitudes at liquid-saturated reservoir locations (e.g., in a water-saturated well). Furthermore, the selected low-frequency cube is a cube in which the frequency amplitudes in the shadow zones beneath the gas reservoirs are more attenuated than the frequency amplitudes in the shadow zones beneath the liquid-saturated reservoirs. According to one example, the selected low-frequency equal-frequency cube is a cube with a frequency of 10 Hz. Other frequencies are also possible. The selected frequency may depend on the frequency amplitude variations at the studied subsurface reservoir locations.

[0032] At step 108, the sequence of actions 100 includes selecting a high-frequency cube from among the spectral decomposition cubes with equal frequencies. For example, the selected high-frequency cube is a cube in which the frequency amplitudes at gas reservoir locations are very low. Furthermore, the selected high-frequency cube is a cube in which the frequency amplitudes in the shadow zones beneath the gas reservoirs are higher than the frequency amplitudes in the shadow zones beneath the gas reservoirs in the low-equal-frequency cube. According to one example, the selected high-equal-frequency cube is a cube with a frequency of 40 Hz. Other frequencies are also possible. The selected frequency may depend on changes in the frequency amplitude at the studied locations of the subsurface reservoir.

[0033] At step 110, the sequence of 100 actions involves creating a relationship cube. According to one example, the relationship cube is created by dividing the cube of low equal frequencies by the cube of high equal frequencies.

[0034] At step 112, the sequence of actions 100 includes establishing a time-depth relationship for the reservoir in the wells being studied. According to one example, one or more high-fidelity well logs (e.g., depth-referenced seismic logs) from previously drilled wells in the subsurface reservoir are used to establish the time-depth relationship. High-fidelity well logs may include sonic logs, seismic logs, and vertical seismic profiling (VSP) logs. More specifically, data from existing wells is used to establish a relationship between well depths (i.e., depth-domain data) and seismic data (i.e., time-domain data). According to one example, seismic velocities are scaled based on seismic logs and / or such logs so that geological locations and seismic horizons coincide in depth.

[0035] At step 114, the sequence of actions 100 includes using the seismic equal frequency ratio attribute cube and the time-depth relationship to create a virtual equal frequency ratio diagram. According to one example, the time-depth relationship is used to associate a given well or a given study area (located in the depth domain) with the equal frequency ratio cube (located in the time domain). Then, a frequency ratio diagram is extracted along the trajectory of the given well. The resulting diagram is a virtual equal frequency ratio diagram. More specifically, the time-depth relationship information is used to determine the portion of the frequency ratio cube associated with the given well. This portion of the frequency ratio cube is then extracted as a virtual equal frequency ratio diagram.

[0036] According to some embodiments, a virtual equal frequency ratio diagram is used to detect hydrocarbons and characterize reservoir formations in a field. According to one example, a graphical representation (e.g., a curve) of the virtual equal frequency ratio diagram may be displayed during and after drilling in a graphical user interface on the user's device along with other calculated diagrams. The value of the virtual equal frequency ratio diagram may be used to detect gas. According to one example, values ​​in the equal frequency ratio diagram in the reservoir being studied that are above a threshold value indicate gas detection. The threshold value may be determined based on previously known values ​​associated with production wells, or may be manually set by the user.

[0037] Fig. 2 shows an example of logs 200 generated for three wells according to some embodiments. These three wells are a well with high water saturation, a well with gas in tight reservoirs, and a producing well. According to one example, one or more logs in Fig. 2 are generated using the sequence of actions 100 shown in Fig. 1. These logs are used to verify the results of the sequence of actions 100. It was said above that the gas producing well demonstrated high (i.e., above the threshold) values ​​in the equal frequency ratio log in the studied reservoir formation. On the other hand, both the well with high water saturation and the well with gas in tight reservoirs demonstrated low values ​​(e.g., below the threshold) in the equal frequency ratio log in the reservoir formation interval.The results of the 100-step sequence showed a significant correlation between the actual well results and the generated equal frequency ratio diagram.

[0038] First, let us consider the logs 202 of the producing well, which show that as the well enters the reservoir interval, the values ​​or amplitudes of the virtual log 204 of the equal frequency ratio increase. This increase can be interpreted as a result of the presence of gaseous fluid in the reservoir. As can be seen from Fig. 2, in the reservoir interval, the values ​​​​on the resistivity log (RL) 214 also increase. This once again confirms the relationship between the virtual log 204 of the equal frequency ratio and the presence of gas in the reservoir. The discrepancy between the neutron log (NL) 206 and the gamma-gamma density log (GGD) 208 is another indication of the presence of gas in the reservoir.

[0039] In contrast, the 210 logs for the well with high water saturation clearly show that the virtual 212 equal frequency ratio values ​​remain unchanged as the reservoir interval is entered. This finding further confirms the drop in resistivity at the top of the reservoir. At the base of the reservoir interval, the resistivity values ​​increase, and the neutron log and gamma-gamma density log diverge. This may indicate the presence of some gas saturation, as a slight increase in the virtual 212 equal frequency ratio values ​​is also visible at the base of the reservoir.

[0040] Let's examine the 220 logs for a gas well in tight reservoirs. Although the resistivity value appears high, the virtual 222 equal frequency ratio log values ​​in the reservoir interval are low. This confirms the feasibility of using equal frequency ratio logs to identify gas wells in tight reservoirs.

[0041] These examples demonstrate that there is a significant correlation between actual well results and equal frequency ratio logs. Thus, the sequence of actions 100 shown in Fig. 1 enables fluid detection in the studied wells. According to some embodiments, equal frequency ratio logs can be used to evaluate the studied stratigraphic intervals within gas-containing reservoirs. Evaluation of the studied stratigraphic intervals allows for improved placement of vertical and horizontal wells to more accurately characterize the gas reservoir characteristics with a more reliable and accurate establishment of the time-depth relationship for the drilled wells. This allows for a reduction in the risk of drilling wells with high water saturations and the optimal drilling of gas producing wells to optimize costs, effort, and time.

[0042] Fig. 3 shows a flow chart of an example of a method 300 according to some embodiments. For clarity in the following description, the method 300 is generally described in the context of other figures of the present description. Thus, the method 300 can be performed using the computer system shown in Fig. 5. However, it should be understood that, depending on the particular case, the method 300 can be implemented, for example, using any suitable system, environment, software, hardware, or a combination of systems, environments, software, hardware. According to some embodiments, the various steps of the method 300 can be performed in parallel, in combination, in cycles, or in any order.

[0043] The method 300 begins with step 302, which includes decomposing seismic data related to the studied subsurface region into a number of equal frequency cubes.

[0044] At step 304, the method 300 includes selecting a low-frequency cube and a high-frequency cube from a number of cubes of equal frequencies.

[0045] At step 306, the method 300 includes dividing the low-frequency cube by the high-frequency cube to create a frequency ratio cube for the subsurface region being studied.

[0046] At step 308, the method 300 includes establishing a time-depth relationship in the subsurface region being studied.

[0047] At step 310, the method 300 includes obtaining a diagram of the ratio of equal frequencies in the studied area of ​​the subsurface, based on the time-depth dependence and the cube of the frequency ratio.

[0048] At step 312, the method 300 includes using an equal frequency ratio diagram to identify an underground gas reservoir in a subsurface area being studied.

[0049] The example method 300 shown in Fig. 3 may be modified or rearranged to include additional steps, fewer steps, or different steps (not shown in Fig. 3), which may be performed in the order shown or in a different order.

[0050] According to some embodiments, establishing a time-depth relationship in a subsurface area of ​​interest includes: obtaining one or more well logs measured in one or more drilled wells near the subsurface area of ​​interest; and establishing a time-depth relationship in the subsurface area of ​​interest based on the one or more well logs.

[0051] According to some embodiments, one or more well logs comprise at least one of the following: an acoustic well log (AL), a vertical seismic profiling (VSP), or a seismic well log.

[0052] According to some embodiments, obtaining an equal frequency ratio diagram in a subsurface region under study based on a time-depth relationship and a frequency ratio cube includes: applying the time-depth relationship to establish a correspondence between depth information in the subsurface region under study and the frequency ratio cube; and obtaining an equal frequency ratio diagram from the frequency ratio cube in the subsurface region under study.

[0053] According to some embodiments, the seismic data is a three-dimensional cube of relative amplitude preserved (RAP) processed seismic data after pre-stack time migration (PSTM).

[0054] According to some embodiments, using an equal frequency ratio diagram to identify a gas-bearing formation in a subsurface area of ​​interest includes: identifying high amplitude-to-frequency ratio values ​​on the equal frequency ratio diagram; assigning the area associated with the high amplitude-to-frequency ratio to a subsurface gas reservoir.

[0055] According to some embodiments, classifying an area associated with a high amplitude-to-frequency ratio as a subsurface gas reservoir includes: determining whether the high amplitude-to-frequency ratio is greater than a threshold frequency ratio; and in response to determining that the high amplitude-to-frequency ratio is above the threshold frequency ratio, determining that the high amplitude-to-frequency ratio indicates a gas-bearing area.

[0056] According to some embodiments, the method 300 further includes: displaying an equal frequency ratio diagram in a graphical user interface (GUI) on a visualization device. This graphical representation of the diagram can be used to visually indicate locations that contain gas. According to some embodiments, this display can be used to determine the location of potential drilling sites or to determine the lateral extent of a reservoir formation. According to another example, the method 300 can further include drilling at one or more locations where gas is present. This step can include transmitting information indicating one or more locations to a drilling control unit (e.g., a computing device). Based on the received information, the control unit can control the drilling equipment to drill at one or more locations.

[0057] According to some embodiments, one or more steps shown in Fig. 3 may be repeated once or multiple times, for example, until a termination condition is reached. According to some embodiments, one or more individual steps shown in Fig. 3 may be performed as several individual steps, or one or more groups of steps shown in Fig. 3 may be combined and performed in a single step. According to some embodiments, one or more steps shown in Fig. 3 may also be excluded from the example method 300.

[0058] Fig. 4 shows an example of a seismic survey according to some embodiments of the present disclosure. According to one embodiment, a seismic survey is performed to map features in the subsurface of the earth, such as facies and faults in a subsurface rock formation 400. Seismic data generated as a result of the seismic survey can be used as input data for the equal frequency workflow described herein. The subsurface rock formation 400 contains an impermeable caprock layer 402 at the surface. The facies underlying the impermeable caprock 402 contain a sandstone layer 404, a limestone layer 406, and a sand layer 408. A fault line 410 passes through the sandstone layer 404 and the limestone layer 406.

[0059] A seismic source 412 (e.g., a seismic vibrator or an explosion) generates seismic waves 414 that propagate in the ground. The velocity of these seismic waves depends on the properties of the medium through which the seismic wave passes, such as density, porosity, and saturation. Different geological bodies or layers in the ground are distinguishable because these layers have different properties and, consequently, different characteristic seismic velocities. For example, in a subsurface rock layer 400, the velocity of seismic waves passing through the subsurface rock layer 400 will be different in a sandstone layer 404, a limestone layer 406, and a sand layer 408. When seismic waves 414 approach the interfaces between geological bodies or layers that have different velocities, the interface reflects some of the seismic wave energy and refracts some of the seismic wave energy. Such boundaries are sometimes called horizons.

[0060] The sensor or sensors 416 receive seismic waves 414. Although the sensor or sensors 416 are shown as a single component in Fig. 4, they typically represent a line or group of sensors 416 that generate an output signal in response to the received seismic waves, including waves reflected from horizons in the underground rock mass 400. The sensors 416 may be geophone receivers that generate electrical output signals that are transmitted as input data, for example, to the computer 418 of the mobile seismic station 420. Based on the input data, the computer 418 can generate seismic data at output, for example, a graph of the double traveltime of seismic waves.

[0061] The control room 422 may be operatively connected to the mobile seismic station 420 and other data acquisition systems and drilling sites. The control room 422 may house computer equipment for receiving, storing, processing and / or analyzing data coming from the mobile seismic station 420 and other data acquisition systems and drilling sites. Thus, the computer systems 424 in the control room 422 may be designed for analysis, modeling, control, optimization, or may perform tasks of managing field operations associated with the development and production of resources, such as oil and gas, from the underground formation 400. According to another embodiment, the computer systems 424 may be located in locations other than the control room 422.Some computer systems have data manipulation and analysis capabilities, such as interpreting seismic data or borehole resistivity logs to identify subsurface geological surfaces, or modeling, planning, and optimizing wellsite system operations.

[0062] According to some embodiments, the results generated by the computer system 424 can be displayed for user viewing using local or remote monitors or other display devices. One approach to analyzing seismic data is to associate this data with portions of a seismic cube representing the subsurface rock mass 400. This seismic cube can also display the results of seismic data analysis associated with the seismic survey.

[0063] Fig. 5 shows a block diagram of an example of a computer system 500 used to provide computing functionality associated with the described algorithms, methods, functions, procedures, flows and processes according to some embodiments of the present disclosure. The depicted computer 502 denotes any computing device, such as a server, a desktop computer, a laptop / notebook, a wireless access point, a smartphone, a personal digital device, a tablet computing device or one or more processors in these devices, including physical instances, virtual instances or both. The computer 502 may include input devices, such as keypads, keyboards and touch screens, that can receive information from a user. The computer 502 may also include output devices that can transmit information related to the operation of the computer 502.This information may contain digital data, visual data, audio information, or a combination of these. The information may be presented in a graphical user interface (UI) (or GUI).

[0064] Computer 502 may act as a client, a network component, a server, a database, a persistent data store, or a component of a computer system for implementing the subject matter described in this disclosure. The depicted computer 502 is in a dial-up connection with network 530. According to some embodiments, one or more components of computer 502 may be designed to operate in various environments, including cloud-based computing environments, local environments, global environments, and combinations of environments.

[0065] At a high level, computer 502 is a computing device that is used to receive, transmit, process, store, and manage data and information related to the described subject matter. According to some embodiments, computer 502 may also comprise or be in dial-up connection with an application server, mail server, web server, caching server, streaming server, or a combination of servers.

[0066] Computer 502 may receive requests over network 530 from a client application (e.g., running on another computer 502). Computer 502 may respond to the received requests by processing the received requests using computer applications. Requests may also be sent to computer 502 by internal users (e.g., from a command console), external (or third) parties, automated applications, modules, people, systems, and computers.

[0067] Each of the components of the computer 502 can communicate using the system bus 503. According to some embodiments, any or all of the components of the computer 502, including software or hardware components, can interact with each other or with the interface 504 (or a combination thereof) via the system bus 503. For interaction, an application programming interface (API) 512, a service layer 513, or a combination of API 512 and service layer 513 can be used. API 512 may contain specifications for programs, data structures, and object classes. API 512 may be independent or dependent on a programming language. API 512 may refer to a complete interface, a single function, or a set of application programming interfaces.

[0068] The service layer 513 can provide software services to the computer 502 and other components (whether depicted or not) that are in a dial-up connection with the computer 502. The functionality of the computer 502 can be available to all service users using this service layer. Software services, such as those provided by the service layer 513, can provide reusable, specific functionality through a specific interface. Thus, the interface can be software written in JAVA, C++, or a language that provides data in the Extensible Markup Language (XML) format.Although depicted as an integrated component of computer 502, in other embodiments, API 512 or service layer 513 may be stand-alone components with respect to other components of computer 502 and other components in dial-up connection with computer 502. Furthermore, any or all portions of API 512 or service layer 513 may be implemented as child or submodules of another software module, enterprise application, or hardware module, without departing from the scope of the present invention.

[0069] The computer 502 comprises an interface 504. Although one interface 504 is shown in Fig. 5, two or more interfaces 504 may be used according to specific needs, requirements, or specific embodiments of the computer 502 and the described functionality. The computer 502 may use the interface 504 to exchange data with other systems that are connected to the network 530 (whether or not shown) in a distributed environment. Typically, the interface 504 may comprise or may be implemented using logic programmed in software or hardware (or a combination of software and hardware) that is used to exchange data with the network 530. More specifically, the interface 504 may comprise software that supports one or more data exchange protocols associated with data exchange.As such, the network 530 or interface hardware may be employed to transmit physical signals within and outside the depicted computer 502.

[0070] The computer 502 includes a processor 505. Although one processor 505 is shown in Fig. 5, two or more processors 505 may be used according to specific needs, requirements, or specific embodiments of the computer 502 and the described functionality. Typically, the processor 505 may execute instructions and may operate on data to perform operations of the computer 502, including operations using algorithms, methods, functions, processes, flows, and procedures as described in this disclosure.

[0071] The computer 502 also comprises a database 506 that can store data for the computer 502 and other components connected to the network 530 (whether or not shown). Thus, the database 506 can be an in-memory database, a standard database, or a database that stores data according to the present disclosure. According to some embodiments, the database 506 can be a combination of two or more different types of databases (for example, a hybrid in-memory database and a standard database) according to the specific needs, requirements, or specific embodiments of the computer 502 and the described functionality. Although in FIG.5 depicts one database 506, according to specific needs, requirements, or specific embodiments of the computer 502 and the described functionality, two or more databases (of the same type, different types, or a combination of types) may be used. Although the database 506 is shown as an internal component of the computer 502, in other embodiments the database 506 may be external to the computer 502.

[0072] The computer 502 also includes a storage device 507 that may contain data for the computer 502 or a combination of components connected to the network 530 (whether or not shown). The storage device 507 may store any data according to the present disclosure. According to some embodiments, the storage device 507 may be a combination of two or more storage devices of different types (for example, a combination of semiconductor and magnetic storage devices) according to the specific needs, requirements, or specific embodiments of the computer 502 and the described functionality. Although in FIG.5 shows one storage device 507, according to specific needs, requirements or specific embodiments of the computer 502 and the described functionalities, two or more storage devices 507 (of the same type, different types or a combination of types) may be used. Although the storage device 507 is shown as an internal component of the computer 502, in other embodiments the storage device 507 may be external to the computer 502.

[0073] Application 508 may be an algorithmic software core that provides functionality according to specific needs, requirements, or specific embodiments of computer 502 and the described functionality. Thus, application 508 may act as one or more components, modules, or applications. In addition, although one application 508 is depicted, application 508 may be implemented as multiple applications 508 on computer 502. Furthermore, although application 508 is shown as internal to computer 502, in other embodiments application 508 may be external to computer 502.

[0074] Computer 502 may also include a power source 514. Power source 514 may include a battery pack or a non-rechargeable battery, which may or may not be user-replaceable. According to some embodiments, power source 514 may include power conversion and control circuitry, including recharging, backup, and power management functionality. According to some embodiments, power source 514 may include a power connector so that computer 502 can be connected to a power outlet or power source, for example, to power computer 502 or recharge a battery.

[0075] The number of computers 502, connected to the computer system containing the computer 502, or external to it, may be any, with each computer 502 communicating via the network 530. Furthermore, the terms "client," "user," and other suitable terms may be used interchangeably as necessary within the scope of the present disclosure. Furthermore, the present disclosure contemplates that the computer 502 may be used by multiple users, and that one user may use several computers 502.

[0076] The implementations of the subject matter of the invention and the functional operations described in this document may be implemented in the form of digital electronic circuits, in tangible computer software or hardware, in computer hardware, including the structures disclosed in this description of the invention and their structural equivalents, or in the form of combinations of one or more of the listed embodiments. Software implementations of the described subject matter of the invention may be implemented in the form of one or more computer programs. Each computer program may comprise one or more computer program instruction modules that are encoded on a real, non-transitory computer-readable storage medium for storage on a computer for the purpose of execution on a device for processing data or controlling its operation.According to another embodiment or additionally, program instructions may be encoded in a propagated artificially generated signal. For example, the signal may be an automatically generated electrical, optical, or electromagnetic signal generated to encode information for transmission to a suitable receiving device for execution by a data processing device. The computer storage device may be a machine-readable storage device, a machine-readable storage medium, a random or sequential access storage device, or a combination of computer storage devices.

[0077] The terms "data processing device," "computer," and "electronic computing device" (or equivalents as understood by those skilled in the art) refer to hardware for processing data. Thus, a data processing device may include all types of devices, devices, and combinations of devices for processing data, including, for example, a programmable processor, a computer, or more processors or computers. The device may also include a special-purpose logic circuit, including, for example, a central processing unit (CPU), a field-programmable gate array (FPGA), or an application-specific integrated circuit (ASIC).According to some embodiments, a data processing device or special-purpose logic circuit (or a combination of a data processing device or special-purpose logic circuit) may be a software or hardware device (or a combination of software and hardware). If necessary, the device may contain code that defines an execution environment for computer programs, such as code that represents processor firmware, a protocol suite, a database management system, an operating system, or a combination of execution environments. The present disclosure contemplates the use of data processing devices with or without standard operating systems, such as LINUX, UNIX, WINDOWS, MAC OS, ANDROID, or IOS.

[0078] A computer program, which may also be referred to or described as a program, software, software application, module, program unit, script, or code, may be written in any programming language. Programming languages ​​may include, for example, compiled languages, interpreted languages, declarative languages, or procedural languages. Programs may be implemented in a computing environment in any form, including as independent programs, modules, components, subroutines, or segments. A computer program may, but does not necessarily, correspond to a file in a file system. A program may be stored in a portion of a file that contains other programs or data, such as in one or more scripts stored in a markup language document, in a separate file specific to the program, or in several interconnected files that store one or more modules, subroutines, or code fragments.A computer program may be deployed for execution on one or more computers, located, for example, at a single site or distributed across multiple sites interconnected by a data network. Although portions of the programs illustrated in various figures may be shown as separate modules that implement various features and functionality through various objects, methods, or procedures, the programs may contain multiple submodules, third-party services, components, and libraries. Conversely, the features and functionality of various components may be combined into separate components as needed. Threshold values ​​used for computer decision making may be determined statically, dynamically, or both.

[0079] The methods, procedures, or logic flows described in this document may be implemented on one or more programmable computers executing one or more computer programs to implement functions by manipulating input data and generating output data. The methods, procedures, or logic flows may also be implemented using or in the form of a special-purpose logic circuit, such as a central processing unit, a programmable logic integrated circuit, or a special-purpose logic circuit.

[0080] Computers suitable for executing computer programs may be based on one or more general-purpose or special-purpose microprocessors and other types of central processing units. A central processing unit for executing instructions and one or more storage devices for storing instructions and data constitute elements of a computer. Typically, the central processing unit may receive instructions and data from a storage device and write data to it. The computer may also include or be operatively connected to one or more storage devices for storing data. In some embodiments, the computer may receive data from or transfer data to storage devices, including, for example, magnetic, magneto-optical, or optical disks.In addition, the computer may be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive.

[0081] Machine-readable media (for carrying or long-term storage of information, as the case may be) suitable for storing computer program instructions may comprise all kinds of non-volatile / volatile memory media and storage devices and devices with destruction or retention of information when the power is disconnected. Machine-readable media may comprise, for example, semiconductor memories such as random access memory (RAM), read-only memory (ROM), parametric random access memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), erasable programmable read-only memory (EPROM), electronically erasable read-only memory (EEPROM), and flash memory devices. Machine-readable media may also comprise, for example, magnetic devices such as tapes, cartridges, cassettes, and built-in / removable disks.Machine-readable media may also include magneto-optical disks and optical storage devices and technologies, including, for example, digital video discs (DVD), CD-ROM, DVD+ / -R, DVD-RAM, DVD-ROM, HD-DVD, and Blu-ray. Memory may store various objects or data, including caches, classes, object structures, applications, modules, data backups, jobs, web pages, web page templates, data structures, database tables, repositories, and dynamic information. Types of objects and data stored in memory may include parameters, variables, algorithms, instructions, rules, constraints, and references. Memory may also contain protocols, policies, security or access data, and report files. The processor and storage device may be supplemented by or include specialized integrated circuits.

[0082] Embodiments of the subject matter described in this disclosure may be implemented on a computer having a display device for providing interaction with a user, including displaying information to the user (and receiving input from the user). Types of display devices may include, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), a light-emitting diode (LED), and a plasma monitor. Display devices may include a keyboard and a pointing device, such as a mouse, trackball, or trackpad. User input to the computer may be provided through the use of a touch screen, such as a pressure-sensitive surface of a tablet computer, or a multi-touch screen that uses capacitive or electrical sensing.Other devices may be used to provide user interaction, including receiving user feedback, such as sensory feedback (including visual feedback, auditory feedback, or haptic feedback). User input may be received in the form of acoustic, speech, or tactile input. Furthermore, the computer may interact with the user by sending and receiving documents from the device the user is using. For example, the computer may send web pages to the web browser on the user's client device in response to requests received from the web browser.

[0083] The term "graphical user interface" or GUI may be used in the singular or plural to describe one or more graphical user interfaces and each display device of a particular graphical user interface. Thus, a graphical user interface may be any graphical user interface, including, but not limited to, a web browser, touch screen, or command-line interface (CLI), that processes information and effectively presents the results of the information processing to the user. Typically, a graphical user interface may contain a number of user interface (UI) elements, some or all of which are related to a web browser, such as interactive fields, drop-down lists, and buttons. These and other UI elements may be related to or represent web browser functionality.

[0084] Embodiments of the subject matter described in this specification may be implemented in a computing system that includes an internal component, such as a data server, or that includes a middleware component, such as an application server. Furthermore, the computing system may include a preprocessor subsystem, such as a client computer with a graphical user interface or a web browser, or both, through which a user can interact with the computer. The components of the system may be interconnected using any type or medium of wired or wireless digital data exchange (or a combination of data exchange types) in a data exchange network.Examples of data networks include a local area network (LAN), a radio access network (RAN), a wide area network (MAN), a wide area network (WAN), wireless maximum access technology (WIMAX), a wireless local area network (WLAN) (e.g., using 802.11 a / b / g / n or 802.20 protocols or a combination of protocols), all or part of the Internet, or any other data communication systems or systems in one or more locations (or a combination of data networks). The network may exchange data between network addresses, such as with Internet Protocol (IP) packets, Frame Relay Protocol (FRP), Asynchronous Transfer Mode (ATM) cells, voice, video, data, or a combination of data communication types.

[0085] A computing system may contain client and server components. The client and server are typically located remotely and typically communicate via a data network. The client and server communicate through computer programs running on the respective computers, which establish a client-server relationship.

[0086] Clustered file systems can be any type of file system, accessible and updatable from multiple servers. Locking or consistency tracking may not be required, as file system locking can be performed at the application level. Furthermore, Unicode data files can be different from data files in other encodings.

[0087] Although the present specification contains many specific implementation details, these should not be construed as limitations on the scope of what can be claimed as the invention, but as descriptions of features characteristic of specific embodiments. Specific features described in the present specification in connection with individual embodiments may also be implemented together in a single embodiment. Conversely, various features described in connection with a single embodiment may also be implemented in several embodiments individually or in any suitable subcombination.Furthermore, although the features described above may be described as acting in certain combinations and even initially claimed as such, one or more features from the claimed combination may in some cases be removed from the combination and the claimed combination may be used in a subcombination or some variation of a subcombination.

[0088] Specific embodiments of the subject matter of the invention are described. Other embodiments, modifications, and combinations of the described embodiments are within the scope of the following claims, as will be apparent to those skilled in the art. Although operations are presented in a specific order in the drawings or in the claims, this should not be understood as a requirement that such operations be performed in the specific order shown or sequentially, or that all illustrated operations (some operations may be optional) be performed to achieve the desired results. In certain circumstances, multitasking or parallel processing (or a combination of multitasking and parallel processing) may be advantageous, and may be performed as needed.

[0089] Furthermore, the separation or combination of various modules and components of the system in the embodiments described above should not be understood as a requirement for such separation or combination in all embodiments, and it should be understood that the described software components and systems may generally be combined into a separate software product or combined into a package of several software products.

[0090] Thus, the previously described exemplary embodiments do not define or limit the present disclosure. Other changes, substitutions, and modifications are also possible without departing from the spirit and scope of the present disclosure.

[0091] Furthermore, any claimed embodiment is considered applicable to at least a method implemented on a computer; a non-transitory storage medium that stores machine-readable instructions for implementing the method executed on a computer; and a computer system comprising a computer memory that interacts with a hardware processor designed to implement the method executed on a computer or instructions stored on a machine-readable non-transitory storage medium.

Claims

1. A seismic exploration method for identifying underground gas deposits in the subsurface area being studied, including: spectral decomposition of seismic data related to the subsurface area under study into a plurality of equal frequency cubes, wherein the seismic data is a three-dimensional cube of relative amplitude-preserving (RAP) seismic data after pre-stack time migration (PSTM); selection of a low-frequency cube and a high-frequency cube from a number of cubes of equal frequencies; dividing the low frequency cube by a high frequency cube to create a frequency ratio cube for the subsurface region being studied, wherein dividing the low frequency cube by the high frequency cube includes dividing the low frequency seismic data values ​​of the low frequency cube by the high frequency seismic data values ​​of the high frequency cube; establishing the time-depth relationship in the subsurface area being studied; obtaining a diagram of the ratio of equal frequencies in the studied area of ​​the subsurface, based on the time-depth dependence and the cube of the frequency ratio, whereby obtaining a diagram of the ratio of equal frequencies includes: applying the time-depth relationship to establish a correspondence between the depth information in the subsurface area under study and the frequency ratio cube; and obtaining a diagram of the ratio of equal frequencies from the cube of the ratio of frequencies in the studied subsurface area; and the application of the equal frequency ratio diagram to identify underground gas deposits in the subsurface area under study.

2. The seismic exploration method according to paragraph 1, in which the establishment of the time-depth relationship in the subsurface area being studied includes: obtaining one or more well logs measured in one or more wells drilled near the subsurface area being studied; establishing the time-depth relationship in the subsurface area being studied based on one or more well logs.

3. The seismic exploration method according to claim 2, wherein one or more logging diagrams comprise at least one of: acoustic logging, vertical seismic profiling, or seismic logging.

4. The seismic exploration method according to paragraph 1, in which the use of an equal frequency ratio diagram to identify an underground gas deposit in the subsurface area being studied includes: identification of a high amplitude-to-frequency ratio on an equal-frequency ratio diagram; and attributing the region associated with a high amplitude-to-frequency ratio to an underground gas deposit.

5. The seismic exploration method according to paragraph 4, wherein the assignment of the region associated with a high amplitude-to-frequency ratio to an underground gas reservoir includes: determining whether the high amplitude-to-frequency ratio is greater than the threshold frequency ratio; and in response to a determination that a high amplitude-to-frequency ratio is above a threshold frequency ratio, a determination that a high amplitude-to-frequency ratio indicates a gas-bearing region.

6. The seismic exploration method according to paragraph 1, additionally including: displaying the equal frequency ratio diagram in a graphical user interface (GUI) on a visualization device.

7. A machine-readable medium for long-term storage of information, connected to one or more processors, on which commands are stored, when executed by one or more processors, one or more processors perform operations for identifying an underground gas deposit in the studied area of ​​the subsurface, including: spectral decomposition of seismic data related to the subsurface area under study into a plurality of equal frequency cubes, wherein the seismic data is a three-dimensional cube of relative amplitude-preserving (RAP) seismic data after pre-stack time migration (PSTM); selection of a low-frequency cube and a high-frequency cube from a number of cubes of equal frequencies; dividing the low frequency cube by a high frequency cube to create a frequency ratio cube for the subsurface region being studied, wherein dividing the low frequency cube by the high frequency cube includes dividing the low frequency seismic data values ​​of the low frequency cube by the high frequency seismic data values ​​of the high frequency cube; establishing the time-depth relationship in the subsurface area being studied; obtaining a diagram of the ratio of equal frequencies in the studied area of ​​the subsurface, based on the time-depth dependence and the cube of the frequency ratio, whereby obtaining a diagram of the ratio of equal frequencies includes: applying the time-depth relationship to establish a correspondence between the depth information in the subsurface area under study and the frequency ratio cube; and obtaining a diagram of the ratio of equal frequencies from the cube of the ratio of frequencies in the studied subsurface region; and Application of the equal frequency ratio diagram to identify underground gas deposits in the subsurface area under study.

8. A machine-readable medium for long-term storage of information according to paragraph 7, on which the establishment of the time-depth relationship in the studied subsurface area includes: obtaining one or more well logs measured in one or more wells drilled near the subsurface area being studied; establishing the time-depth relationship in the subsurface area being studied based on one or more well logs.

9. A machine-readable medium for long-term storage of information according to paragraph 8, on which one or more well logging diagrams represent at least one of the following diagrams: acoustic logging, vertical seismic profiling or seismic logging.

10. A machine-readable medium for long-term storage of information according to paragraph 7, in which the use of an equal frequency ratio diagram for identifying an underground gas deposit in the subsurface area being studied includes: identification of a high amplitude-to-frequency ratio on the equal-frequency ratio diagram; and Attribution of the region associated with a high amplitude-to-frequency ratio to an underground gas deposit.

11. A machine-readable medium for long-term storage of information according to paragraph 10, wherein the assignment of the region associated with a high amplitude-to-frequency ratio to an underground gas deposit includes: determining whether the high amplitude-to-frequency ratio is greater than the threshold frequency ratio; and in response to a determination that a high amplitude-to-frequency ratio is above a threshold frequency ratio, a determination that a high amplitude-to-frequency ratio indicates a gas-bearing region.

12. A seismic exploration system for identifying underground gas deposits in the subsurface area being studied, which contains: one or more processors designed to perform operations including: spectral decomposition of seismic data related to the subsurface area under study into a plurality of equal frequency cubes, wherein the seismic data is a three-dimensional cube of relative amplitude-preserving (RAP) seismic data after pre-stack time migration (PSTM); selection of a low-frequency cube and a high-frequency cube from a number of cubes of equal frequencies; dividing the low frequency cube by a high frequency cube to create a frequency ratio cube for the subsurface region being studied, wherein dividing the low frequency cube by the high frequency cube includes dividing the low frequency seismic data values ​​of the low frequency cube by the high frequency seismic data values ​​of the high frequency cube; establishing the time-depth relationship in the subsurface area being studied; obtaining a diagram of the ratio of equal frequencies in the studied area of ​​the subsurface, based on the time-depth dependence and the cube of the frequency ratio, whereby obtaining a diagram of the ratio of equal frequencies includes: applying the time-depth relationship to establish a correspondence between the depth information in the subsurface area under study and the frequency ratio cube; and obtaining a diagram of the ratio of equal frequencies from the cube of the ratio of frequencies in the studied subsurface region; and Application of the equal frequency ratio diagram to identify underground gas deposits in the subsurface area under study.

13. The seismic exploration system according to paragraph 12, in which the establishment of the time-depth relationship in the subsurface area being studied includes: obtaining one or more well logs measured in one or more wells drilled near the subsurface area being studied; establishing the time-depth relationship in the subsurface area being studied based on one or more well logs.

14. The seismic exploration system of claim 13, wherein the one or more well logs comprise at least one of an acoustic well log, a vertical seismic profiling log, or a seismic well log.

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