Oil and gas exploration method and device and storage medium

Abstract

The invention discloses an oil and gas exploration method and device and a storage medium. The method comprises the steps that trap distribution information in an oil-gas exploration area is acquired, and the trap distribution information comprises distribution sizes and distribution forms of different types of work area traps under the ground of the oil-gas exploration area; acquiring a surface microbial hydrocarbon detection result and a time-frequency electromagnetic data processing result of the oil-gas exploration area; comparing the trap distribution information, the surface microbial hydrocarbon detection result and the time-frequency electromagnetic data processing result to obtain a comparison result; and determining a target work area oil-gas-containing trap from the work area traps indicated by the trap distribution information according to a comparison result. The technical problem that the exploration accuracy is low due to the fact that only one oil and gas judgment method is adopted in an oil and gas exploration mode in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of geological exploration, and more particularly, to a method and apparatus for oil and gas exploration, and a storage medium. Background Art

[0002] Oil and gas resource exploration is a high-risk commercial activity. Due to the complexity of geological targets, the success rate of oil and gas exploration drilling in the current industry has been maintained at a relatively low level, and most drilling activities have failed because the target traps do not contain oil and gas. In the development process of oil and gas exploration technology, the exploration activities of oil and gas companies mainly rely on a set of exploration technology systems based on petroleum geology research and mainly using geophysical technologies such as seismic exploration methods and drilling. However, this technology system has technical defects such as low exploration success rate and inability to determine the oil and gas content of the target. A technology system that can further improve the success rate of oil and gas resource exploration has always been a requirement of the industry.

[0003] Currently, the main methods of oil and gas exploration include: 1) directly conducting drilling exploration based on the results of seismic exploration; 2) using hydrocarbon detection technology to judge whether the trap contains oil and gas. However, the cost of drilling exploration is too high, and hydrocarbon detection technology can only determine the abnormal characteristics on the surface layer. That is, the oil and gas exploration methods provided in the related technologies have the problem of low exploration accuracy.

[0004] In response to the above problems, no effective solution has been proposed yet. Summary of the Invention

[0005] Embodiments of this application provide a method and apparatus for oil and gas exploration, and a storage medium, so as to at least solve the technical problem of low exploration accuracy in the oil and gas exploration methods provided in the prior art.

[0006] According to one aspect of the embodiments of this application, a method for oil and gas exploration is provided, including: obtaining trap distribution information in an oil and gas exploration area, where the trap distribution information includes the distribution size and distribution form of different types of work area traps underground in the oil and gas exploration area; obtaining the surface microbial hydrocarbon detection results and time-frequency electromagnetic data processing results of the oil and gas exploration area; comparing the trap distribution information, the surface microbial hydrocarbon detection results, and the time-frequency electromagnetic data processing results to obtain a comparison result; and determining a target work area oil and gas-bearing trap from the work area traps indicated by the trap distribution information according to the comparison result.

[0007] According to another aspect of the embodiments of the present application, there is also provided an oil and gas exploration device, including: a first acquisition unit, configured to acquire trap distribution information within an oil and gas exploration area, where the trap distribution information includes the distribution size and distribution form of different types of work area traps underground in the oil and gas exploration area; a second acquisition unit, configured to acquire the surface microbial hydrocarbon detection result and the time-frequency electromagnetic data processing result of the oil and gas exploration area; a comparison unit, configured to compare the trap distribution information, the surface microbial hydrocarbon detection result, and the time-frequency electromagnetic data processing result to obtain a comparison result; and a determination unit, configured to determine a target work area hydrocarbon-bearing trap from the work area traps indicated by the trap distribution information according to the comparison result.

[0008] According to still another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium storing a computer program, where the computer program is configured to execute the above-mentioned oil and gas exploration method when running.

[0009] In the embodiments of the present application, after acquiring the trap distribution information within the oil and gas exploration area, the surface microbial hydrocarbon detection result of the oil and gas exploration area, and the processing result of the time-frequency electromagnetic data, the trap distribution information, the surface microbial hydrocarbon detection result, and the time-frequency electromagnetic data processing result are compared with each other to obtain a comparison result, and a target work area hydrocarbon-bearing trap is determined from the work area traps indicated by the trap distribution information according to the comparison result. That is to say, when conducting oil and gas exploration, the three pieces of information of the trap distribution information, the surface microbial hydrocarbon detection result, and the time-frequency electromagnetic data processing result are integrated, rather than relying only on one oil and gas judgment method, thereby achieving the technical effect of improving the accuracy of oil and gas exploration, and further solving the technical problem of relatively low exploration accuracy existing in the oil and gas exploration methods provided in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0011] Figure 1 is a schematic diagram of an optional oil and gas exploration method according to the embodiments of the present application;

[0012] Figure 2 is a schematic diagram of another optional oil and gas exploration method according to the embodiments of the present application;

[0013] Figure 3 is a schematic diagram of still another optional oil and gas exploration method according to the embodiments of the present application;

[0014] Figure 4It is a schematic diagram of another optional oil and gas exploration method according to an embodiment of the present application;

[0015] Figure 5 It is a schematic diagram of another optional oil and gas exploration method according to an embodiment of the present application;

[0016] Figure 6 It is a schematic diagram of another optional oil and gas exploration method according to an embodiment of the present application;

[0017] Figure 7 It is a schematic structural diagram of an optional oil and gas exploration device according to an embodiment of the present application. Detailed implementation manners

[0018] In order to enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0019] It should be noted that the terms "first", "second", etc. in the description and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily need to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0020] Optionally, as an optional implementation manner, as Figure 1 shown, the above-mentioned oil and gas exploration method includes:

[0021] S102. Obtain the trap distribution information in the oil and gas exploration area, where the trap distribution information includes the distribution size and distribution form of different types of work area traps underground in the oil and gas exploration area;

[0022] S104. Obtain the surface microbial hydrocarbon detection results and time-frequency electromagnetic data processing results of the oil and gas exploration area;

[0023] S106. Compare the trap distribution information, the surface microbial hydrocarbon detection results, and the time-frequency electromagnetic data processing results to obtain a comparison result.

[0024] S108. Determine the oil and gas-bearing traps in the target work area from the traps in the work area indicated by the trap distribution information according to the comparison result.

[0025] Optionally, in this embodiment, the oil and gas exploration method can be, but is not limited to, applied to the scenario of determining underground oil and gas resources. The oil and gas resources include various types such as conventional oil and gas reservoirs like petroleum and natural gas, and unconventional oil and gas resources like shale gas, natural gas hydrates, tight oil, and tight gas. The trap distribution information can be obtained through conventional geophysical methods such as seismic exploration methods and drilling techniques. The types of traps include various types such as structural traps, stratigraphic traps, and composite traps.

[0026] For further illustration, in the three-dimensional exploration of the Northwest A Oilfield exploration area, the trap types, shapes, sizes, depths, etc. of each horizon in this block, such as the Cretaceous formation and the Jurassic formation, can be obtained. For example, Figure 2 The figure shows a summary map of the trap distribution in the work area obtained by seismic exploration. It can be seen from the figure that there are a total of 3 favorable traps, all of which are structural traps. The area of Trap 1 is about 3 square kilometers, and the target horizon is the Cretaceous formation. The area of Trap 2 is about 11 square kilometers, and the target horizon is the Jurassic formation. The area of Trap 3 is about 5 square kilometers, and the target formation is also the Jurassic formation. For example, Figure 3 The figure shows a seismic profile element map of Trap 2 obtained by seismic exploration. The top line represents the surface, and the following represents the stratigraphic distribution obtained according to the exploration results. The ellipse in the figure represents the trap. Design the collection for the surface microbial hydrocarbon detection method and the time-frequency electromagnetic polarization rate method in the oil and gas exploration area, including collection tools, collection locations, collection samples, etc. Among them, the surface microbial hydrocarbon detection method requires collecting on-site samples, and the time-frequency electromagnetic polarization rate method requires collecting data. Detect and analyze the collected samples and process them using Surfer software to obtain the abnormal plane distribution map of microbial hydrocarbon detection and the broken line map of microbial hydrocarbon detection. Analyze and process the collected data using GMECS software to obtain the abnormal map of the polarization rate inversion horizon. Compare the above trap distribution information, surface microbial hydrocarbon detection results, and time-frequency electromagnetic data processing results to finally obtain the best oil and gas-bearing traps.

[0027] Through this embodiment, trap distribution information within the oil and gas exploration area is obtained, where the trap distribution information includes the distribution size and distribution pattern of different types of work area traps underground in the oil and gas exploration area; the surface microbial hydrocarbon detection results and time-frequency electromagnetic data processing results of the oil and gas exploration area are obtained; the trap distribution information, the surface microbial hydrocarbon detection results, and the time-frequency electromagnetic data processing results are compared with each other to obtain a comparison result; and target work area hydrocarbon-bearing traps are determined from the work area traps indicated by the trap distribution information according to the comparison result, achieving the effect of improving the accuracy of oil and gas exploration.

[0028] As an alternative solution, obtaining the surface microbial hydrocarbon detection results and time-frequency electromagnetic data processing results of the oil and gas exploration area includes:

[0029] S1. Detect and evaluate the surface microorganisms collected on-site in the oil and gas exploration area to obtain a microbial hydrocarbon detection anomaly plane distribution map and a microbial hydrocarbon detection broken line map;

[0030] S2. Process the time-frequency electromagnetic data to obtain a polarization rate inversion horizon anomaly map.

[0031] Optionally, in this embodiment, the microbial hydrocarbon detection anomaly plane distribution map represents the distribution of the anomaly areas detected by microbial hydrocarbon detection. The determination method of the anomaly areas is that the number of microorganisms in the anomaly areas is higher than that in the surrounding normal areas. The microbial hydrocarbon detection broken line map is used to represent the number of microorganisms detected at different geographical locations, where the abscissa represents different geographical locations and the ordinate represents the number of microorganisms. The polarization rate inversion horizon anomaly map is used to represent the magnitude of the polarization rate at different formation depths, where the abscissa represents the polarization rate, which is the superposition or average value of the polarization rates detected at the same depth at different acquisition points, and the ordinate represents the depth. The superposition processing is for easy observation. For example, when the value of the polarization rate is very small, the change difference of the polarization rates at different depths can be more clearly seen after superposition.

[0032] For further illustration, the number of butane-oxidizing bacteria in the soil samples collected on-site in the oil and gas exploration area is detected. The soil samples are collected three times at each acquisition point, and the average value or median of the number of butane-oxidizing bacteria collected from the three soil samples is used as the final number of butane-oxidizing bacteria at this acquisition point. The microbial hydrocarbon detection anomaly plane distribution map and the microbial hydrocarbon detection broken line map are generated from the above processing results using surfer software. Figure 4The figure shows the plane distribution map of the sampling points for surface microbial hydrocarbon detection and evaluation and the anomaly areas. It can be seen from the figure that there are three anomaly areas in this work area, namely Anomaly No. 1, Anomaly No. 2, and Anomaly No. 3. Each point in the figure represents a sampling point. As shown by Anomaly No. 1 in the figure, the sampling points in the innermost circle can represent that the detected microbial quantity is 100, the sampling points in the outermost circle can represent that the detected microbial quantity is 150, and the sampling points in other areas can represent that the detected microbial quantity is less than 100. By using the GMECS software to process the collected electromagnetic data, the inversion horizon anomaly map of the polarization rate can be obtained.

[0033] Through this embodiment, the surface microorganisms collected on-site in the oil and gas exploration area are detected and evaluated to obtain the plane distribution map of microbial hydrocarbon detection anomalies and the line graph of microbial hydrocarbon detection; the time-frequency electromagnetic data is processed to obtain the inversion horizon anomaly map of the polarization rate. The effect of judging the best oil and gas traps based on multiple methods is achieved.

[0034] As an optional solution, before detecting and evaluating the surface microorganisms collected on-site in the oil and gas exploration area to obtain the plane distribution map of microbial hydrocarbon detection anomalies, it further includes:

[0035] Collect the surface microorganisms in the oil and gas exploration area according to the preset collection density, where the preset collection density is related to the trap area of the oil and gas exploration area.

[0036] Optionally, in this embodiment, the preset collection density can be related to the trap area of the oil and gas exploration area. When the trap area is less than 5 square kilometers, the collection density is not greater than 330 meters; when the trap area is greater than 5 square kilometers, the collection density is not greater than 500 meters.

[0037] For further illustration, when the trap area is 5 square kilometers and the collection density is 330 meters, there are 9 sampling points per square kilometer, so there are 45 sampling points for a trap area of 5 square kilometers. When detecting surface microbial hydrocarbons, collect soil samples on the surface, with the collection depth being 20 cm - 40 cm, the collection amount being 200 g for each soil sample, and the collection tool being a shovel. The collection amount of samples inside the trap and outside the trap is 1:1 or 1:2. Cover all traps to be evaluated in the form of grid collection. The grid collection form is to collect in the form of point spacing. In addition, the linear collection form can also be adopted, that is, collect in a straight line without interval distance.

[0038] Through this embodiment, the surface microorganisms are collected in the oil and gas exploration area according to the preset collection density, where the preset collection density is related to the trap area of the oil and gas exploration area, so as to ensure that there are a certain number of sampling points in each trap.

[0039] As an alternative solution, the trap distribution information, the surface microbial hydrocarbon detection results, and the time-frequency electromagnetic data processing results are compared with each other, and the comparison results include:

[0040] S1. Overlay the work area trap distribution map indicated by the trap distribution information with the microbial hydrocarbon detection anomaly plane distribution map, so as to determine candidate work area traps from the work area traps indicated by the trap distribution information;

[0041] S2. Compare the seismic profile, the polarization rate inversion horizon anomaly map, and the microbial hydrocarbon detection line graph corresponding to the candidate work area traps to obtain the hydrocarbon anomaly position.

[0042] Optionally, in this embodiment, the work area trap distribution map and the work area microbial hydrocarbon detection anomaly plane distribution map are overlaid in the same coordinate system, and the traps that coincide with the microbial hydrocarbon detection anomaly area are determined as candidate work area traps. Since the microbial hydrocarbon detection obtains the surface microbial anomaly, in order to determine whether the surface microbial anomaly is caused by the horizon where the trap is located, the seismic profile, the polarization rate inversion horizon anomaly map, and the microbial hydrocarbon detection line graph corresponding to the work area trap are compared to determine whether there is a maximum polarization rate anomaly in the horizon where the trap is located under the surface anomaly position shown in the microbial hydrocarbon detection line graph.

[0043] Further, for example, as Figure 5 shown is the plane overlay summary map of the work area trap distribution in the microbial hydrocarbon detection anomaly area. It can be seen from the figure that anomaly No. 3 coincides with trap No. 2, anomaly No. 2 coincides with trap No. 1, and anomaly No. 1 does not coincide with trap No. 3. The overlapping area indicates that the number of microorganisms detected on the surface corresponding to the trap is abnormal. Then, trap No. 1 and trap No. 2 that coincide with the anomaly area are determined as candidate work area traps. Further, in order to further determine which underground horizon causes the surface microbial hydrocarbon detection anomaly corresponding to the trap, a longitudinal section can be made on the overlapping area of trap No. 2 and anomaly No. 3. For example, making a longitudinal section on trap No. 2 can obtain the seismic profile element map, the polarization rate inversion horizon anomaly map, and the corresponding surface microbial hydrocarbon detection line graph as shown in Figure 6 It can be seen from the figure that directly above the trap exactly corresponds to the surface microbial hydrocarbon detection anomaly. Since the abscissa of the polarization rate inversion horizon anomaly map represents the polarization rate and the ordinate represents the depth, it can be determined from the polarization rate inversion horizon anomaly map that there is a maximum polarization rate anomaly at the trap position. Then, it can be determined that the surface microbial hydrocarbon detection anomaly of trap No. 2 is caused by the horizon where trap No. 2 is located. That is to say, there is a maximum polarization rate anomaly at the position of trap No. 2, and the corresponding surface microbial hydrocarbon detection anomaly.

[0044] In this embodiment, the trap distribution map of the work area indicated by the trap distribution information is superimposed on the microbial hydrocarbon detection abnormal plane distribution map to determine candidate work area traps from the work area traps indicated by the trap distribution information; the seismic profile, the polarization rate inversion horizon anomaly map, and the microbial hydrocarbon detection broken line map corresponding to the candidate work area traps are compared to obtain the hydrocarbon anomaly position, achieving the effect of comprehensively using multiple methods to judge the best oil and gas traps and improving the exploration accuracy of the best oil and gas traps.

[0045] As an alternative solution, determining the target work area oil and gas-bearing trap from the work area traps indicated by the trap distribution information according to the comparison result includes:

[0046] Based on the hydrocarbon anomaly position, the target oil and gas-bearing trap is determined from the candidate work area traps.

[0047] Optionally, in this embodiment, if the hydrocarbon anomaly position is in the candidate work area trap, the candidate work area trap is determined as the final target trap; if the hydrocarbon anomaly position is not in the candidate work area trap, the candidate work area trap is not the final target trap.

[0048] For further illustration, as analyzed above, performing a longitudinal section on the candidate work area traps No. 1 and No. 2 can obtain the corresponding seismic profile elements map and the corresponding surface microbial hydrocarbon detection broken line map. Through the polarization rate inversion horizon anomaly map, it can be determined that the polarization rate maximum value of the horizon where trap No. 2 is located is also abnormal, indicating that the microbial hydrocarbon detection anomaly above the surface corresponding to trap No. 2 is caused by the horizon where trap No. 2 is located. Therefore, trap No. 2 is determined as the best oil and gas-bearing trap. The polarization rate of the horizon where trap No. 1 is located is not found to be abnormal. Although there is a microbial hydrocarbon detection anomaly above the surface corresponding to trap No. 1, it is not caused by the horizon where trap No. 1 is located, but by the abnormal polarization rate maximum value of other horizons. That is to say, although there is a microbial hydrocarbon detection anomaly above the surface corresponding to trap No. 1, the polarization rate maximum value at the location of trap No. 1 is not abnormal. Therefore, trap No. 1 is not the best oil and gas-bearing trap. Based on the above analysis, it can be seen that the trap with both surface microbial anomaly and abnormal polarization rate maximum value is judged as the best oil and gas trap, and then the best oil and gas trap is explored.

[0049] In this embodiment, based on the hydrocarbon anomaly position, the target oil and gas-bearing trap is determined from the candidate work area traps, achieving the effect of improving the accuracy of oil and gas exploration.

[0050] Optionally, as an alternative implementation manner, the above method is explained by the following steps for overall illustration:

[0051] Three-dimensional exploration is carried out in the exploration block of Oilfield A in the northwest. It is determined that there are three favorable traps in this block, all of which are structural traps. Refer to Figure 2As shown in the synoptic diagram of trap distribution in the work area, the area of Trap No. 1 is approximately 3 square kilometers, and the target horizon is the Cretaceous strata. The area of Trap No. 2 is approximately 11 square kilometers, and the target horizon is the Jurassic strata. The area of Trap No. 3 is approximately 5 square kilometers, and the target horizon is also the Jurassic strata. For the above three traps, surface microbial hydrocarbon detection and evaluation sample collection were carried out. The sampling point spacing was 330 meters, the collected samples were soil samples, the collection amount for each sample was 200 g, the collection depth was 20 cm - 40 cm, and the collection tool was a spade. At the same time, electromagnetic data were collected every 330 meters. The above electromagnetic data could be conductivity. The quantity ratio of soil sample collection and electromagnetic data collection inside and outside the trap was 1:1, that is, the same number of samples were collected inside the trap as outside the trap. The number of soil sample collections was 3 times, and the number of electromagnetic data collections was 100 times, that is, 100 conductivity measurement results could be obtained at each collection point. After the collection was completed, hydrocarbon-oxidizing bacteria detection was carried out on the soil samples. The detection index was butane-oxidizing bacteria, and 3 detection results of the number of butane-oxidizing bacteria could be obtained at each collection point. After averaging the 3 detection results of the number of butane-oxidizing bacteria, the final number of butane-oxidizing bacteria corresponding to each collection point could be obtained. Then, a microbial hydrocarbon detection anomaly plane distribution map was generated using Surfer software as Figure 4 shown. A total of three anomaly areas were determined in the figure, namely Anomaly No. 1, Anomaly No. 2, and Anomaly No. 3. At the same time, a microbial hydrocarbon detection line graph would also be obtained. The GMECS software was used to perform superposition processing on the 100 electromagnetic data collected, and a polarization rate inversion horizon anomaly map was generated using the software. Figure 2 Overlaying the synoptic diagram of trap distribution in the work area and Figure 3 the microbial hydrocarbon detection anomaly plane distribution map could obtain Figure 4 . It can be seen from Figure 5 that Trap No. 1 corresponds to Anomaly No. 2 on the plane, Trap No. 2 corresponds to Anomaly No. 3, there is no anomaly in the area where Trap No. 3 is located, and it is also detected that there is no trap development in the area corresponding to Anomaly No. 1. Therefore, Trap No. 1 and Trap No. 2 are taken as the geological targets for further priority evaluation. When the trap results are obtained through seismic exploration as above, the corresponding seismic profile element diagrams will also be obtained, which are used to describe the distribution of each horizon from the surface to the underground and the position of the trap underground. As Figure 6 shown are the seismic profile element diagram of Trap No. 2, the polarization rate inversion horizon anomaly map, and the corresponding microbial hydrocarbon detection line graph on the surface. There is a microbial hydrocarbon detection anomaly on the surface directly above Trap No. 2. At the same time, through the polarization rate inversion horizon anomaly map, a maximum polarization rate anomaly can be obtained in the Jurassic trap strata corresponding to Trap No. 2. However, no polarization rate anomaly is found in the horizon where Trap No. 1 with Anomaly No. 2 is developed through the polarization rate inversion horizon anomaly map. Therefore, Trap No. 2 with simultaneous anomalies in surface microbial hydrocarbon detection and polarization rate is determined as the trap with the most oil and gas potential, and it is recommended to deploy drilling well positions at the high part of this trap.

[0052] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0053] According to another aspect of the embodiments of the present application, there is also provided an exploration device for implementing the above-mentioned oil and gas exploration. As Figure 7 shown, the device includes:

[0054] A first acquisition unit 702, configured to acquire trap distribution information within an oil and gas exploration area, where the trap distribution information includes the distribution size and distribution form of different types of work area traps underground in the oil and gas exploration area;

[0055] A second acquisition unit 704, configured to acquire the detection results of surface microbial hydrocarbons and the processing results of time-frequency electromagnetic data in the oil and gas exploration area;

[0056] A comparison unit 706, configured to compare the trap distribution information, the detection results of surface microbial hydrocarbons, and the processing results of time-frequency electromagnetic data to obtain a comparison result;

[0057] A determination unit 708, configured to determine a target work area hydrocarbon-bearing trap from the work area traps indicated by the trap distribution information according to the comparison result.

[0058] Optionally, in this embodiment, the oil and gas exploration method can be but is not limited to being applied to the scenario of determining underground oil and gas resources. The oil and gas resources include conventional oil and gas reservoirs such as petroleum and natural gas, and unconventional oil and gas resources such as shale gas, natural gas hydrates, tight oil, and tight gas, etc. The trap distribution information can be obtained by conventional geophysical methods such as seismic exploration methods and drilling techniques. The types of traps include structural traps, stratigraphic traps, and composite traps, etc.

[0059] The embodiments in this solution can be but are not limited to referring to the above method embodiments, and no limitation is made thereto in this embodiment.

[0060] Through this embodiment, trap distribution information within the oil and gas exploration area is obtained, where the trap distribution information includes the distribution size and distribution pattern of different types of work area traps underground in the oil and gas exploration area; the surface microbial hydrocarbon detection results and time-frequency electromagnetic data processing results of the oil and gas exploration area are obtained; the trap distribution information, the surface microbial hydrocarbon detection results, and the time-frequency electromagnetic data processing results are compared with each other to obtain a comparison result; and target work area hydrocarbon-bearing traps are determined from the work area traps indicated by the trap distribution information according to the comparison result, achieving the effect of improving the accuracy of oil and gas exploration.

[0061] As an alternative solution, the second obtaining unit 704 includes:

[0062] A detection module, configured to detect and evaluate surface microorganisms collected on-site in the oil and gas exploration area to obtain an abnormal plane distribution map of microbial hydrocarbon detection and a broken line graph of microbial hydrocarbon detection;

[0063] A processing module, configured to process the time-frequency electromagnetic data to obtain an abnormal map of polarization rate inversion horizons.

[0064] The embodiments in this solution may, but are not limited to, refer to the above method embodiments, and no limitation is made thereto in this embodiment.

[0065] As an alternative solution, the above device further includes:

[0066] A collection module, configured to collect surface microorganisms in the oil and gas exploration area according to a preset collection density, where the preset collection density is related to the trap area of the oil and gas exploration area.

[0067] The embodiments in this solution may, but are not limited to, refer to the above method embodiments, and no limitation is made thereto in this embodiment.

[0068] As an alternative solution, the comparison unit 706 includes:

[0069] An overlay module, configured to overlay the work area trap distribution map indicated by the trap distribution information with the abnormal plane distribution map of microbial hydrocarbon detection to determine candidate work area traps from the work area traps indicated by the trap distribution information;

[0070] A comparison module, configured to compare the seismic profile, the abnormal map of polarization rate inversion horizons, and the broken line graph of microbial hydrocarbon detection corresponding to the candidate work area traps to obtain hydrocarbon anomaly positions.

[0071] The embodiments in this solution may, but are not limited to, refer to the above method embodiments, and no limitation is made thereto in this embodiment.

[0072] As an alternative solution, the determination unit 708 includes:

[0073] A determination module, configured to determine a target hydrocarbon-bearing trap from candidate work area traps based on the location of hydrocarbon anomalies.

[0074] The embodiments in this solution can, but are not limited to, be implemented with reference to the above method embodiments, and no limitations are made in this regard in this embodiment.

[0075] According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium storing a computer program, where the computer program is configured to execute the steps in any one of the above method embodiments when running.

[0076] Optionally, in this embodiment, the above computer-readable storage medium may be configured to store a computer program for executing the following steps:

[0077] S1, for obtaining trap distribution information within an oil and gas exploration area, where the trap distribution information includes the distribution size and distribution form of different types of work area traps underground in the oil and gas exploration area;

[0078] S2, for obtaining the surface microbial hydrocarbon detection results and time-frequency electromagnetic data processing results of the oil and gas exploration area;

[0079] S3, for comparing the trap distribution information, the surface microbial hydrocarbon detection results, and the time-frequency electromagnetic data processing results to obtain a comparison result;

[0080] S4, for determining a target work area hydrocarbon-bearing trap from the work area traps indicated by the trap distribution information according to the comparison result.

[0081] Optionally, in this embodiment, those of ordinary skill in the art can understand that all or part of the steps in the above various methods can be completed by a program instructing the relevant hardware of the terminal device, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc.

[0082] The above serial numbers of the embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0083] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above computer-readable storage media. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing one or more computer devices (which can be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in various embodiments of this application.

[0084] In the above embodiments of this application, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0085] In the several embodiments provided by this application, it should be understood that the disclosed client can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the units or modules can be in electrical or other forms.

[0086] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, the functional units in each embodiment of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0088] The above are only the preferred embodiments of this application. It should be noted that for those of ordinary skill in the art, without departing from the principle of this application, several improvements and refinements can still be made, and these improvements and refinements should also be regarded as the protection scope of this application.

Claims

1. An oil and gas exploration method, characterized in that, it includes: Obtaining trap distribution information within the oil and gas exploration area, wherein the trap distribution information includes the distribution size and distribution form of different types of work area traps underground in the oil and gas exploration area; Obtaining the surface microbial hydrocarbon detection results and time-frequency electromagnetic data processing results of the oil and gas exploration area; Comparing the trap distribution information, the surface microbial hydrocarbon detection results, and the time-frequency electromagnetic data processing results to obtain a comparison result; Determining target work area hydrocarbon-bearing traps from the work area traps indicated by the trap distribution information according to the comparison result.

2. The method according to claim 1, characterized in that, The obtaining the surface microbial hydrocarbon detection results and time-frequency electromagnetic data processing results of the oil and gas exploration area includes: Detecting and evaluating surface microorganisms collected on-site in the oil and gas exploration area to obtain a microbial hydrocarbon detection abnormal plane distribution map and a microbial hydrocarbon detection broken line map; Processing the time-frequency electromagnetic data to obtain a polarization rate inversion horizon abnormal map.

3. The method according to claim 2, characterized in that, Before detecting and evaluating surface microorganisms collected on-site in the oil and gas exploration area to obtain a microbial hydrocarbon detection abnormal plane distribution map, it further includes: Collecting the surface microorganisms in the oil and gas exploration area according to a preset collection density, wherein the preset collection density is related to the trap area of the oil and gas exploration area.

4. The method according to claim 2, characterized in that, The comparing the trap distribution information, the surface microbial hydrocarbon detection results, and the time-frequency electromagnetic data processing results to obtain a comparison result includes: Overlaying the work area trap distribution map indicated by the trap distribution information with the microbial hydrocarbon detection abnormal plane distribution map to determine candidate work area traps from the work area traps indicated by the trap distribution information; Comparing the seismic profile corresponding to the candidate work area traps, the polarization rate inversion horizon abnormal map, and the microbial hydrocarbon detection broken line map to obtain the hydrocarbon anomaly position.

5. The method according to claim 4, characterized in that, Determining target work area hydrocarbon-bearing traps from the work area traps indicated by the trap distribution information according to the comparison result includes: Determining the target hydrocarbon-bearing traps from the candidate work area traps based on the hydrocarbon anomaly position.

6. An oil and gas exploration device, characterized in that, it includes: A first obtaining unit for obtaining trap distribution information within the oil and gas exploration area, wherein the trap distribution information includes the distribution size and distribution form of different types of work area traps underground in the oil and gas exploration area; A second obtaining unit for obtaining the surface microbial hydrocarbon detection results and time-frequency electromagnetic data processing results of the oil and gas exploration area; A comparison unit for comparing the trap distribution information, the surface microbial hydrocarbon detection results, and the time-frequency electromagnetic data processing results to obtain a comparison result; A determination unit, configured to determine a target oil and gas-bearing trap in the work area traps indicated by the trap distribution information according to the comparison result.

7. The apparatus according to claim 6, wherein, the second acquisition unit includes: a detection module, configured to detect and evaluate surface microorganisms collected on site in the oil and gas exploration area, so as to obtain a microbial hydrocarbon detection abnormal plane distribution map and a microbial hydrocarbon detection broken line map; a processing module, configured to process the time-frequency electromagnetic data to obtain a polarization rate inversion horizon abnormal map.

8. The apparatus according to claim 7, wherein, the apparatus further includes: a collection module, configured to collect the surface microorganisms in the oil and gas exploration area according to a preset collection density, wherein the preset collection density is related to the trap area of the oil and gas exploration area.

9. The apparatus according to claim 7, wherein, the comparison unit includes: a superimposing module, configured to superimpose the work area trap distribution map indicated by the trap distribution information and the microbial hydrocarbon detection abnormal plane distribution map, so as to determine candidate work area traps from the work area traps indicated by the trap distribution information; a comparison module, configured to compare the seismic profile corresponding to the candidate work area trap, the polarization rate inversion horizon abnormal map, and the microbial hydrocarbon detection broken line map to obtain the hydrocarbon anomaly position.

10. A computer-readable storage medium, wherein, the computer-readable storage medium includes a stored program, wherein the program, when run by a processor, executes the method described in any one of claims 1 to 5.

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