Method, device, storage medium and electronic device for determining resource space distribution

Abstract

The application discloses a method for determining resource space distribution, comprising the following steps: dividing a zone into multiple subdivision units; assigning success probability to the oil and gas trap integrity of each subdivision unit to obtain a trap probability map; assigning success probability to the target reservoir-forming element of each subdivision unit to obtain a target reservoir-forming element probability map; forming a geological risk unit superimposed map according to the trap probability map and the target reservoir-forming element probability map; obtaining the trap probability, the geological success rate and the area of each subdivision unit from the trap probability map and the geological risk unit superimposed map; determining the number of successful traps of the subdivision unit according to the total number of successful traps, the area, the trap probability and the geological success rate; determining the undiscovered resource scale of the subdivision unit according to the total number of successful traps, the number of successful traps and the undiscovered resource scale, so as to determine the resource space distribution of the zone according to the undiscovered resource scale of each subdivision unit.

Description

Technical Field

[0001] This invention relates to the field of petroleum exploration, and more specifically to a method, apparatus, storage medium, and electronic equipment for determining the spatial distribution of resources. Background Technology

[0002] To date, most exploration projects by domestic and foreign oil companies have focused primarily on calculating the resource volume of traps and assessing the risks of individual traps, with very little attention paid to calculating the planar distribution of undiscovered oil and gas resources in low-exploration basins in the frontier area.

[0003] Based on this, this application proposes a method for estimating the resource scale of basins with low exploration levels. This method is easy to implement and can conveniently and effectively determine the spatial distribution of undiscovered resources in specific oil and gas zones of the target basin. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method for determining the spatial distribution of resources, comprising the following steps:

[0005] Predict the total undiscovered resource size R and the total number of successful traps N within the predicted zone;

[0006] Based on the geological conditions of the zone, the zone is divided into several sub-units;

[0007] Assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map;

[0008] Assign success probability values ​​to the target hydrocarbon accumulation elements in each sub-unit to obtain a probability map of target hydrocarbon accumulation elements;

[0009] Based on the trap probability map and the target hydrocarbon accumulation element probability map, a geological risk unit overlay map representing the geological success rate is generated;

[0010] For each sub-unit, obtain the closure probability T of sub-unit k from the closure probability map. k Geological success rate G of subdivided unit k is obtained from the geological risk unit overlay map. k and the area A of the subdivided unit k ;

[0011] Based on the total number of successfully trapped structures N and the area A k The probability of trapping T k and geological success rate G k Determine the number of successful traps TS of subdivision unit k. k ;

[0012] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R determines the resource size R of subdivided unit k.k This allows for the determination of the spatial distribution of resources in the aforementioned zones based on the scale of resources to be discovered in each sub-unit.

[0013] Furthermore, the total undiscovered resource size within the aforementioned prediction zone includes: the total undiscovered resource size within the aforementioned zone predicted using the seventh approximation method, reservoir size sequence method, exploration efficiency trend method, or geological Pareto method.

[0014] Furthermore, the aforementioned target hydrocarbon accumulation elements include four hydrocarbon accumulation elements: source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions.

[0015] The above process assigns success probabilities to the target hydrocarbon accumulation elements in each sub-unit, resulting in a probability map of the target hydrocarbon accumulation elements, including:

[0016] Success probability values ​​were assigned to the four hydrocarbon accumulation elements corresponding to each subdivided unit to obtain the probability maps of source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions for the above-mentioned zones.

[0017] Furthermore, based on the trap probability map and the target hydrocarbon accumulation element probability map, a geological risk unit overlay map representing the geological success rate is formed, including:

[0018] By overlaying the probability maps of traps, source rocks, reservoirs, caprocks, and oil and gas migration, accumulation, and preservation conditions, a geological risk unit overlay map is formed.

[0019] Furthermore, by overlaying the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and hydrocarbon migration, accumulation, and preservation condition probability map, a geological risk unit overlay map is formed, including:

[0020] For each sub-unit, the success probabilities corresponding to the sub-unit in the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and oil and gas migration, accumulation, and preservation condition probability map are multiplied together, and then a geological risk unit overlay map is formed based on the product of the success probabilities corresponding to each sub-unit.

[0021] Furthermore, the product of the trapping probability and the area is determined according to the following expression:

[0022]

[0023] Where m is the total number of subdivision units within the aforementioned zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. j G is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit.

[0024] Furthermore, based on the total number N of successfully closed loops, the area A k The probability of trapping T k and geological success rate G k Determine the number of successful traps TS of subdivision unit k. k include:

[0025] Based on the total number of successful oil and gas traps N and their area A k The probability of trapping T k Geological success rate G k The number of successful traps TS in subdivision unit k is determined by multiplying the trapping probability area by the following expression. k :

[0026]

[0027] Where m is the total number of subdivision units within the aforementioned zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. j G is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit.

[0028] Furthermore, based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R determines the resource size R of subdivided unit k. k include:

[0029] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R, the resource size R of subdivision unit k is determined according to the following expression. k :

[0030]

[0031] The present invention also provides an apparatus for determining the spatial distribution of resources, comprising the following modules:

[0032] The prediction module is used to predict the total size of resources to be discovered R and the total number of successful traps N within the zone;

[0033] The partitioning module is used to divide the zone into multiple sub-units based on the geological conditions of the zone;

[0034] The first acquisition module is used to assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map;

[0035] The second acquisition module is used to assign success probability values ​​to the target hydrocarbon accumulation elements of each sub-unit to obtain a probability map of the target hydrocarbon accumulation elements.

[0036] The generation module is used to generate a geological risk unit overlay map representing the geological success rate based on the trap probability map and the target hydrocarbon accumulation element probability map.

[0037] The third acquisition module is used to obtain the closure probability T of sub-unit k from the closure probability map for each sub-unit. k Geological success rate G of subdivided unit k is obtained from the geological risk unit overlay map. k and the area A of the subdivided unit k ;

[0038] The first calculation module is used to calculate the total number of successfully closed traps N and the area A. k The probability of trapping T k and geological success rate G k Determine the number of successful traps TS of subdivision unit k. k ;

[0039] The second calculation module is used to calculate the total number of successful traps N and the number of successful traps TS. k And the total undiscovered resource size R determines the resource size R of subdivided unit k. k This allows for the determination of the spatial distribution of resources in the aforementioned zones based on the scale of resources to be discovered in each sub-unit.

[0040] The present invention also provides a storage medium storing a program that, when executed by a processor, performs the method described in any of the preceding claims.

[0041] The present invention also provides an electronic device including a memory and a processor, wherein the memory stores a computer program that is executed by the processor to perform the methods described in any of the preceding claims.

[0042] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0043] By applying the method for determining the spatial distribution of resources provided by this invention, even with only basic geological conditions and total reserve size of the resource basin, the spatial distribution characteristics of reserves and traps within the basin, as well as the total undiscovered resource size of each sub-unit, can be quickly and conveniently predicted. This enables the determination of the spatial distribution of undiscovered oil and gas resources in the entire oil and gas basin evaluation zone. This method can quickly identify favorable target areas with limited exploration data, and preliminarily screen blocks worthy of further in-depth research and exploration, thus efficiently solving the problem of how to make investment decisions for low-exploration projects with limited data, which is beneficial to improving the efficiency of subsequent project decision-making. Furthermore, by using the method disclosed in this invention, while mitigating exploration risks, the needs of the company's investment portfolio optimization can be better met, providing a practical method for optimizing investment quality and efficiency. Attached Figure Description

[0044] The scope of this disclosure can be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings. The accompanying drawings are:

[0045] Figure 1 The diagram shows the overlay of basin geological risk units in EV2 software and the drilling results obtained by assuming a Monte Carlo simulation of an exploration well within it.

[0046] Figure 2 This shows the resource distribution of each block in the basin in the EV2 software;

[0047] Figure 3 A flowchart illustrating a method for determining the spatial distribution of resources provided in an embodiment of the present invention;

[0048] Figure 4 A flowchart illustrating a method for determining the spatial distribution of resources provided in an embodiment of the present invention;

[0049] Figure 5 A schematic diagram of a zone divided into subdivided units provided for an embodiment of the present invention;

[0050] Figure 6 A trap probability diagram provided for an embodiment of the present invention;

[0051] Figure 7 This is an overlay diagram of geological risk units provided in an embodiment of the present invention;

[0052] Figure 8 This is a bar chart showing the distribution of resource abundance in zones provided in an embodiment of the present invention. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the present invention clearer, the implementation method of the present invention will be described in detail below with reference to the accompanying drawings and embodiments, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0054] Currently, the following three types of software are used for evaluating trapped resources:

[0055] GeoX software can perform integrated Monte Carlo evaluation of trap resources, output, investment and economy. However, the software only uses trap resources as input parameters, and the risk of traps needs to be evaluated separately externally. Furthermore, it cannot evaluate zones in new areas where traps have not been identified.

[0056] Player software focuses on risk assessment of zones and traps, while its assessment of the amount of resources within a trap is relatively simplified.

[0057] EV2 software simulates whether each well can discover oil and gas and the scale of resources based on pre-designed drilling in each block and a pre-set probability distribution. It uses the Monte Carlo method to repeat the calculation multiple times (typically thousands of times), statistically analyzing the probability of successful resource discovery for each well, and obtaining an overlay map of basin geological risk units and simulated drilling results of hypothetical exploration wells (such as...). Figure 1 (As shown); based on the number of successful wells and the size of the discovered traps within each block, the potential resource size for each block is calculated, thereby indirectly revealing the spatial distribution of resource density (e.g., Figure 2 (As shown). Although this software can directly calculate the geospatial distribution density of discovered oil and gas resources, the Monte Carlo algorithm it uses is extremely complex: first, a batch of hypothetical wells and traps need to be manually deployed, and the calculations are repeated thousands of times according to the Monte Carlo principle. Then, the drilling results and the size of the discovered traps are randomly assigned to each exploration well based on parameters such as drilling success rate. Finally, the actual resource quantity discovered in the entire basin can only be obtained after all exploration wells have been drilled. Furthermore, this method is very expensive, and its implementation is even more complex.

[0058] It is evident that resource evaluation in low-exploration-level zones of the frontier area is currently very difficult, with issues such as high evaluation difficulty or high cost affecting evaluation accuracy and leading to high uncertainty in subsequent investment.

[0059] In view of this, the method for determining the spatial distribution of resources provided by this invention, even with only basic geological conditions and total reserve size of the resource basin, can quickly and conveniently predict the spatial distribution characteristics of reserves and traps within the basin, as well as the total undiscovered resource size of each sub-unit. This achieves the determination of the spatial distribution of undiscovered oil and gas resources in the entire oil and gas basin evaluation zone. This method can quickly identify favorable target areas with limited exploration data, and preliminarily screen blocks worthy of further in-depth research and exploration and development. This efficiently solves the problem of how to make investment decisions for low-exploration projects with limited data, and is conducive to improving the efficiency of subsequent project decision-making. Furthermore, the method disclosed in this invention, while mitigating exploration risks, can better meet the company's portfolio optimization needs, providing a practical method for optimizing investment quality and efficiency.

[0060] Example One

[0061] To address the aforementioned technical problems in the prior art, Embodiment 1 of the present invention provides a method for determining the spatial distribution of resources.

[0062] Figure 3 This is a flowchart illustrating a method for determining the spatial distribution of resources according to an embodiment of the present invention. Figure 3 As shown, the method for determining the spatial distribution of resources in this embodiment may include the following steps.

[0063] S110: The total size of resources to be discovered R and the total number of successful traps N within the predicted zone.

[0064] S120: Based on the geological conditions of the zone, the zone is divided into several sub-units.

[0065] S130: Assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map.

[0066] S140: Assign success probability values ​​to the target hydrocarbon accumulation elements in each sub-unit to obtain a probability map of the target hydrocarbon accumulation elements.

[0067] S150: Based on the trap probability map and the target hydrocarbon accumulation element probability map, a geological risk unit overlay map representing the geological success rate is formed.

[0068] S160: For each sub-unit, obtain the closure probability T of sub-unit k from the closure probability map. k Geological success rate G of subdivided unit k is obtained from the geological risk unit overlay map. k and the area A of the subdivided unit k .

[0069] S170: Based on the total number of successfully closed loops N and the area A k The probability of trapping T k and geological success rate G k Determine the number of successful traps TS of subdivision unit k. k .

[0070] S180: Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R determines the resource size R of subdivided unit k. k This allows for the determination of the spatial distribution of resources in the aforementioned zones based on the scale of resources to be discovered in each sub-unit.

[0071] In a specific implementation process, the total undiscovered resource size within the aforementioned prediction zone includes: predicting the total undiscovered resource size within the aforementioned zone based on the seventh approximation method, reservoir size sequence method, exploration efficiency trend method, or geological Pareto method.

[0072] Step S120 can specifically involve dividing the zone based on oil and gas geological conditions. The zone can be divided into multiple sub-units according to the range of parameters related to the oil and gas geological conditions. As a preferred example, the zone can be divided into numerous sub-units with relatively small areas.

[0073] In one implementation, step S130 may be to determine the success probability of each sub-unit based on the correspondence between oil and gas trap integrity and success probability obtained during historical exploration.

[0074] In one implementation, step S140 may assign a success probability value to the target hydrocarbon accumulation element based on the knowledge gained from zonal geological studies.

[0075] Specifically, the aforementioned target hydrocarbon accumulation elements can be selected based on the commonly used research approaches for basins with low exploration levels.

[0076] In one implementation, step S150 may involve overlaying the above-mentioned trap probability map and the target hydrocarbon accumulation element probability map to obtain the above-mentioned geological risk unit overlay map.

[0077] Specifically, step S170 may include:

[0078] Based on the total number of successful oil and gas traps N and their area A k The probability of trapping T k Geological success rate G k The number of successful traps TS in subdivision unit k is determined by multiplying the trapping probability area by the following expression. k :

[0079]

[0080] Where m is the total number of subdivision units within the aforementioned zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. j G is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit.

[0081] In one implementation, step S180 may include:

[0082] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R, the resource size R of subdivision unit k is determined according to the following expression. k :

[0083]

[0084] Based on this, the method for determining the spatial distribution of resources provided by this invention can quickly and conveniently predict the spatial distribution characteristics of reserves and traps within a resource basin, as well as the total undiscovered resource scale of each sub-unit, even when only the basic geological conditions and total reserve size of the resource basin are known. This enables the determination of the spatial distribution of undiscovered oil and gas resources in the entire oil and gas basin evaluation zone. This method can quickly identify favorable target areas with limited exploration data, and preliminarily screen blocks worthy of further in-depth research and exploration, thus efficiently solving the problem of how to make investment decisions for low-exploration projects with limited data, which is beneficial to improving the efficiency of subsequent project decision-making. Furthermore, the method disclosed in this invention, while mitigating exploration risks, can better meet the company's portfolio optimization needs, providing a practical method for optimizing investment quality and efficiency.

[0085] Example Two

[0086] To address the aforementioned technical problems in the prior art, Embodiment 2 of the present invention provides a method for determining the spatial distribution of resources.

[0087] Figure 4 This is a flowchart illustrating a method for determining the spatial distribution of resources according to an embodiment of the present invention. Figure 4 As shown, the method for determining the spatial distribution of resources in this embodiment may include the following steps.

[0088] S210: The total size of resources to be discovered R and the total number of successful traps N within the predicted zone.

[0089] S220: Based on the geological conditions of the zone, the zone is divided into several sub-units.

[0090] S230: Assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map.

[0091] S240: Assign success probability values ​​to the target hydrocarbon accumulation elements in each sub-unit to obtain a probability map of the target hydrocarbon accumulation elements.

[0092] S250: Overlay the probability maps of traps, source rocks, reservoirs, caprocks, and oil and gas migration, accumulation, and preservation conditions to form a geological risk unit overlay map.

[0093] S260: For each sub-unit, obtain the closure probability T of sub-unit k from the closure probability map. k Geological success rate G of subdivided unit k is obtained from CCRS map. k and the area A of the subdivided unit k .

[0094] S270: Based on the total number of successfully closed loops N, the area A k The probability of trapping T k Geological success rate G k The number of successful traps TS in subdivision unit k is determined by multiplying the trap probability area corresponding to the above-mentioned zones. k .

[0095] S280: Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R determines the resource size R of subdivided unit k. k This allows for the determination of the spatial distribution of resources in the aforementioned zones based on the scale of resources to be discovered in each sub-unit.

[0096] In a specific implementation process, the total undiscovered resource size within the aforementioned prediction zone includes: predicting the total undiscovered resource size within the aforementioned zone based on the seventh approximation method, reservoir size sequence method, exploration efficiency trend method, or geological Pareto method.

[0097] In a specific implementation process, the above-mentioned target hydrocarbon accumulation elements include four hydrocarbon accumulation elements: source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions.

[0098] The above process assigns success probabilities to the target hydrocarbon accumulation elements in each sub-unit, resulting in a probability map of the target hydrocarbon accumulation elements, including:

[0099] Success probability values ​​were assigned to the four hydrocarbon accumulation elements corresponding to each subdivided unit to obtain the probability maps of source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions for the above-mentioned zones.

[0100] It should be noted that in other embodiments, other hydrocarbon accumulation elements may be selected based on geological conditions.

[0101] In a specific implementation process, the probability maps of traps, source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions are overlaid to form a geological risk unit overlay map, including:

[0102] For each sub-unit, the success probabilities corresponding to the sub-unit in the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and oil and gas migration, accumulation, and preservation condition probability map are multiplied together, and then a geological risk unit overlay map is formed based on the product of the success probabilities corresponding to each sub-unit.

[0103] Specifically, step S270 may include:

[0104] Based on the total number of successful oil and gas traps N and their area A k The probability of trapping T k Geological success rate Gk The number of successful traps TS in subdivision unit k is determined by multiplying the trapping probability area by the following expression. k :

[0105]

[0106] In one implementation, step S280 may include:

[0107] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R, the resource size R of subdivision unit k is determined according to the following expression. k :

[0108]

[0109] Based on this, the method for determining the spatial distribution of resources provided by this invention can quickly and conveniently predict the spatial distribution characteristics of reserves and traps within a resource basin, as well as the total undiscovered resource scale of each sub-unit, even when only the basic geological conditions and total reserve size of the resource basin are known. This enables the determination of the spatial distribution of undiscovered oil and gas resources in the entire oil and gas basin evaluation zone. This method can quickly identify favorable target areas with limited exploration data, and preliminarily screen blocks worthy of further in-depth research and exploration, thus efficiently solving the problem of how to make investment decisions for low-exploration projects with limited data, which is beneficial to improving the efficiency of subsequent project decision-making. Furthermore, the method disclosed in this invention, while mitigating exploration risks, can better meet the company's portfolio optimization needs, providing a practical method for optimizing investment quality and efficiency.

[0110] Example Three

[0111] To address the aforementioned technical problems in the prior art, Embodiment 3 of the present invention provides an apparatus for determining the spatial distribution of resources, comprising the following modules:

[0112] The prediction module is used to predict the total size of resources to be discovered R and the total number of successful traps N within the zone;

[0113] The partitioning module is used to divide the zone into multiple sub-units based on the geological conditions of the zone;

[0114] The first acquisition module is used to assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map;

[0115] The second acquisition module is used to assign success probability values ​​to the target hydrocarbon accumulation elements of each sub-unit to obtain a probability map of the target hydrocarbon accumulation elements.

[0116] The generation module is used to generate a geological risk unit overlay map representing the geological success rate based on the trap probability map and the target hydrocarbon accumulation element probability map.

[0117] The third acquisition module is used to obtain the closure probability T of sub-unit k from the closure probability map for each sub-unit. k Geological success rate G of subdivided unit k is obtained from the geological risk unit overlay map. k and the area A of the subdivided unit k ;

[0118] The first calculation module is used to calculate the total number of successfully closed traps N and the area A. k The probability of trapping T k and geological success rate G k Determine the number of successful traps TS of subdivision unit k. k ;

[0119] The second calculation module is used to calculate the total number of successful traps N and the number of successful traps TS. k And the total undiscovered resource size R determines the resource size R of subdivided unit k. k This allows for the determination of the spatial distribution of resources in the aforementioned zones based on the scale of resources to be discovered in each sub-unit.

[0120] In a specific implementation, the prediction module predicts the total undiscovered resource size within the aforementioned zones based on the seventh approximation method, reservoir size sequence method, exploration efficiency trend method, or geological Pareto method.

[0121] In a specific implementation process, the target hydrocarbon accumulation elements may include four hydrocarbon accumulation elements: source rocks, reservoirs, caprocks, and conditions for hydrocarbon migration, accumulation, and preservation.

[0122] In a specific implementation process, the second acquisition module can be used to assign success probability values ​​to the four hydrocarbon accumulation elements corresponding to each subdivided unit, so as to obtain the source rock probability map, reservoir probability map, caprock probability map, and hydrocarbon migration, accumulation, and preservation condition probability map of the above-mentioned zone.

[0123] In a specific implementation process, the generation module can be used to overlay the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and oil and gas migration, accumulation, and preservation condition probability map to form a geological risk unit overlay map.

[0124] In a specific implementation, the generation module can be further used to multiply the success probabilities of each sub-unit in the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and oil and gas migration, accumulation, and preservation condition probability map, and then form a geological risk unit overlay map based on the product of the success probabilities of each sub-unit.

[0125] In a specific implementation process, the first calculation module can be based on the total number of successful oil and gas traps N and the area A. k The probability of trapping T k Geological success rate G k The number of successful traps TS in subdivision unit k is determined by multiplying the trapping probability area by the following expression. k :

[0126]

[0127] Where m is the total number of subdivision units within the aforementioned zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. j G is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit.

[0128] In a specific implementation, the second calculation module can determine the resource scale R of the subdivision unit k according to the following expression. k :

[0129]

[0130] Based on this, the device for determining the spatial distribution of resources provided by this invention can quickly and conveniently predict the spatial distribution characteristics of reserves and traps within a resource basin, as well as the total undiscovered resource scale of each sub-unit, even when only the basic geological conditions and total reserve size of the resource basin are known. This enables the determination of the spatial distribution of undiscovered oil and gas resources in the entire oil and gas basin evaluation zone. This device can quickly identify favorable target areas with limited exploration data, and preliminarily screen blocks worthy of further in-depth research and exploration, thus efficiently solving the problem of how to make investment decisions for low-exploration projects with limited data, which is beneficial to improving the efficiency of subsequent project decision-making. Furthermore, using the device disclosed in this invention, while mitigating exploration risks, it can better meet the company's portfolio optimization needs, providing a practical method for optimizing investment quality and efficiency.

[0131] Example Four

[0132] To address the aforementioned technical problems in the prior art, Embodiment 4 of the present invention provides a method for determining the spatial distribution of resources.

[0133] The method for determining the spatial distribution of resources in this embodiment may include the following steps:

[0134] Predict the total undiscovered resource size R and the total number of successful traps N within the predicted zone;

[0135] Based on the geological conditions of the zone, the zone is divided into several sub-units;

[0136] Assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map;

[0137] Assign success probability values ​​to the target hydrocarbon accumulation elements in each sub-unit to obtain a probability map of target hydrocarbon accumulation elements;

[0138] Based on the trap probability map and the target hydrocarbon accumulation element probability map, a geological risk unit overlay map representing the geological success rate is generated;

[0139] For each sub-unit, obtain the closure probability T of sub-unit k from the closure probability map. k Geological success rate G of subdivided unit k is obtained from the geological risk unit overlay map. k and the area A of the subdivided unit k ;

[0140] Based on the total number of successfully closed loops N, the area A k The probability of trapping T k and geological success rate G k Determine the number of successful traps TS of subdivision unit k. k ;

[0141] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R determines the resource size R of subdivided unit k. k This allows for the determination of the spatial distribution of resources in the aforementioned zones based on the scale of resources to be discovered in each sub-unit.

[0142] In a specific implementation process, the total undiscovered resource size within the aforementioned prediction zone includes: predicting the total undiscovered resource size within the aforementioned zone based on the seventh approximation method, reservoir size sequence method, exploration efficiency trend method, or geological Pareto method.

[0143] In a specific implementation process, the above-mentioned target hydrocarbon accumulation elements include four hydrocarbon accumulation elements: source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions.

[0144] The above process assigns success probabilities to the target hydrocarbon accumulation elements in each sub-unit, resulting in a probability map of the target hydrocarbon accumulation elements, including:

[0145] Success probability values ​​were assigned to the four hydrocarbon accumulation elements corresponding to each subdivided unit to obtain the probability maps of source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions for the above-mentioned zones.

[0146] In a specific implementation process, based on the trap probability map and the target hydrocarbon accumulation element probability map, a geological risk unit overlay map representing the geological success rate is generated, including:

[0147] By overlaying the probability maps of traps, source rocks, reservoirs, caprocks, and oil and gas migration, accumulation, and preservation conditions, a geological risk unit overlay map is formed.

[0148] In a specific implementation process, the probability maps of traps, source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions are overlaid to form a geological risk unit overlay map, including:

[0149] For each sub-unit, the success probabilities corresponding to the sub-unit in the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and oil and gas migration, accumulation, and preservation condition probability map are multiplied together, and then a geological risk unit overlay map is formed based on the product of the success probabilities corresponding to each sub-unit.

[0150] Specifically, the product of the trapping probability and the area is determined according to the following expression:

[0151]

[0152] Where m is the total number of subdivision units within the aforementioned zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. j G is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit.

[0153] Specifically, based on the total number N of successfully closed loops, the area A k The probability of trapping T k Geological success rate G k The number of successful traps TS in subdivision unit k is determined by multiplying the trap probability area corresponding to the above-mentioned zones. k include:

[0154] Based on the total number of successful oil and gas traps N and their area A k The probability of trapping T k Geological success rate G k The number of successful traps TS in subdivision unit k is determined by multiplying the trapping probability area by the following expression. k :

[0155]

[0156] Where m is the total number of subdivision units within the aforementioned zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. jG is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit.

[0157] Specifically, based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R determines the resource size R of subdivided unit k. k include:

[0158] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R, the resource size R of subdivision unit k is determined according to the following expression. k :

[0159]

[0160] The following example, using a specific block in Brazil, illustrates the method for determining the spatial distribution of resources disclosed in this invention.

[0161] A basin with an area of ​​approximately 7300 km² 2 The water depth varies considerably, ranging from shallow continental shelf to 2300m deep, and the basin is relatively unexplored, with virtually no offshore drilling. However, there is some existing exploration potential within the basin, including two-dimensional and three-dimensional seismic data.

[0162] This embodiment employs a seven-step approximation method to predict the total undiscovered resource size R and the total number of successful traps N within a given zone. The seven-step approximation method consists of the following steps: dividing the work area, preparing geological background research data, studying the probability distribution model of the number of oil and gas traps and the probability distribution model of the resource size of a single oil and gas trap, setting risk parameters and other probability parameters, and using the Monte Carlo method to calculate the total undiscovered oil and gas resource size. The total undiscovered resource size R is obtained through Monte Carlo calculation; the total number of successful traps N is determined by analogy with the discovered resource sizes of other similar maturely explored oil and gas zones based on oil and gas geological conditions. Through analysis and calculation, the median probability distribution of the undiscovered resource size in this geological stratum within the target zone is found to be 3328 million barrels of oil and gas equivalent, and the median probability distribution of the number of undiscovered traps is 51. For simplicity, this embodiment uses the median of the total undiscovered resource size R and the total number of successful traps N as the determined values ​​for both.

[0163] Based on basic hydrocarbon geological conditions and 2D reflection seismic interpretation of stratigraphy and structural features, the basin is divided into 38 sub-units (e.g., Figure 5 (As shown). Specifically, the zone is divided into multiple sub-units based on its geological conditions. These sub-units may vary in size but should be numerous enough. For example, based on experience, the area of ​​a typical geological basin is between 5,000 and 20,000 km². 2Therefore, dividing the zone into 30-50 sub-units can better characterize the spatial variation of any geological parameter within the zone. The method of subdividing these sub-units can be adjusted according to actual geological conditions. By assigning success probability values ​​to the hydrocarbon trap integrity and four other target hydrocarbon accumulation elements (source rock, reservoir, caprock, hydrocarbon migration and accumulation, and preservation conditions) of each sub-unit, trap probability maps (such as...) are obtained. Figure 6 As shown), the probability maps include source rock probability maps, reservoir probability maps, caprock probability maps, and probability maps of hydrocarbon migration, accumulation, and preservation conditions. These maps are then overlaid to form a geological risk unit overlay map (e.g., ...). Figure 7 (As shown). "Overlay" means that for each subdivided unit, the success probability of that subdivided unit in the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and oil and gas migration, accumulation, and preservation condition probability map are multiplied together.

[0164] However, the total undiscovered resource size R and the total number of successful traps N only provide the resource size of the entire zone and cannot determine the spatial distribution characteristics of the resources within the zone. Therefore, it is necessary to combine the trap probability map and the geological risk unit overlay map to determine the spatial distribution characteristics of the resources in the aforementioned zone.

[0165] Suppose that there are m subdivisions in the geological risk unit overlay map, and for any unit j, its area is A. j The geological success rate obtained from the geological risk unit overlay map is G. j The trapping probability obtained from the trapping probability diagram is T. j If the overall exploration success rate of the zone is x, then:

[0166] The total number of traps in the study zone (including successful traps with oil and gas injection and failed traps without oil and gas injection) is N / x;

[0167] The total number of loops in subdivision unit j is:

[0168] The number of successfully trapped loops is:

[0169] According to the definition of a successful trap, the sum of all successful traps is N:

[0170]

[0171] Rearranging Equation 3, we get:

[0172]

[0173] Substituting equation 2 back into its original form (4), we obtain:

[0174] The number of successfully closed loops in any subdivision unit k is:

[0175]

[0176] The number of successful traps TS for any unit can be calculated using Formula 5. k

[0177] (4) Estimate the scale of undiscovered resources in each unit based on the number of traps in each unit.

[0178] The total undiscovered resource size R is calculated from step (1). R can be a probability distribution or a constant value. The resource size of a single trap is R / N. The resource size of any unit k is represented by R. k If we express this, then we have:

[0179]

[0180] The resource scale of any unit k can be obtained from Formula 6.

[0181] In another implementation, the resource size of any unit k can also be expressed as:

[0182]

[0183] The calculation results are shown in Table 1. Figure 8 This is a bar chart describing the resource abundance distribution of each sub-unit, drawn based on Table 1.

[0184] Table 1 - Resource Scale and Abundance of Each Sub-unit

[0185]

[0186]

[0187] The resource abundance of each sub-unit can be expressed as the quotient of the resource size of that sub-unit and the area of ​​that sub-unit.

[0188] Although units 9 and 13 in the geological risk unit overlay map have the highest geological success rates, their areas are also correspondingly large. Therefore, the geological risk unit overlay map cannot directly reflect the resource abundance of these units; that is, it is impossible to intuitively determine the resource abundance of units 9 and 13 from the original geological risk unit overlay map. Similarly, units 34-38 have smaller areas, and although their success rates are higher, it is still impossible to directly determine from the geological risk unit overlay map whether the resource scale of units 34-38 is large enough or the resource abundance is high enough. Furthermore, since the geological success rates of units 17-21 vary, it is also impossible to intuitively determine whether the resource abundance of units 17-21 is high. However, through Table 1 and... Figure 8By combining the method for determining the spatial distribution of resources disclosed in this invention, it is possible to quickly determine that the potential future exploration potential of a basin lies in the areas with the highest resource abundance, namely units 8, 9, 13, 17-21, and 34-38, which will serve as key areas for the next step of investment.

[0189] Based on this, the method for determining the spatial distribution of resources provided by this invention can quickly and conveniently predict the spatial distribution characteristics of reserves and traps within a resource basin, as well as the total undiscovered resource scale of each sub-unit, even when only the basic geological conditions and total reserve size of the resource basin are known. This enables the determination of the spatial distribution of undiscovered oil and gas resources in the entire oil and gas basin evaluation zone. This method can quickly identify favorable target areas with limited exploration data, and preliminarily screen blocks worthy of further in-depth research and exploration, thus efficiently solving the problem of how to make investment decisions for low-exploration projects with limited data, which is beneficial to improving the efficiency of subsequent project decision-making. Furthermore, the method disclosed in this invention, while mitigating exploration risks, can better meet the company's portfolio optimization needs, providing a practical method for optimizing investment quality and efficiency.

[0190] Example Five

[0191] The aforementioned storage media can be flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, server, app store, etc.

[0192] When the computer program stored on the storage medium is executed by the processor, it can perform the following method steps:

[0193] Predict the total undiscovered resource size R and the total number of successful traps N within the predicted zone;

[0194] Based on the geological conditions of the zone, the zone is divided into several sub-units;

[0195] Assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map;

[0196] Assign success probability values ​​to the target hydrocarbon accumulation elements in each sub-unit to obtain a probability map of target hydrocarbon accumulation elements;

[0197] Based on the trap probability map and the target hydrocarbon accumulation element probability map, a geological risk unit overlay map representing the geological success rate is generated;

[0198] For each sub-unit, obtain the closure probability T of sub-unit k from the closure probability map. k Geological success rate G of subdivided unit k is obtained from the geological risk unit overlay map. k and the area A of the subdivided unit k ;

[0199] Based on the total number of successfully closed loops N, the area A k The probability of trapping T k and geological success rate G k Determine the number of successful traps TS of subdivision unit k. k ;

[0200] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R determines the resource size R of subdivided unit k. k This allows for the determination of the spatial distribution of resources in the aforementioned zones based on the scale of resources to be discovered in each sub-unit.

[0201] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0202] The total undiscovered resource size in the above-mentioned zones can be predicted using the seventh approximation method, reservoir size sequence method, exploration efficiency trend method, or geological Pareto method.

[0203] Specifically, the aforementioned target hydrocarbon accumulation elements include four elements: source rocks, reservoirs, caprocks, and conditions for hydrocarbon migration, accumulation, and preservation.

[0204] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0205] Success probability values ​​were assigned to the four hydrocarbon accumulation elements corresponding to each subdivided unit to obtain the probability maps of source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions for the above-mentioned zones.

[0206] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0207] By overlaying the probability maps of traps, source rocks, reservoirs, caprocks, and oil and gas migration, accumulation, and preservation conditions, a geological risk unit overlay map is formed.

[0208] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0209] For each sub-unit, the success probabilities corresponding to the sub-unit in the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and oil and gas migration, accumulation, and preservation condition probability map are multiplied together, and then a geological risk unit overlay map is formed based on the product of the success probabilities corresponding to each sub-unit.

[0210] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0211] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0212] Based on the total number of successful oil and gas traps N and their area A k The probability of trapping T k Geological success rate G k The number of successful traps TS in subdivision unit k is determined by multiplying the trapping probability area by the following expression. k :

[0213]

[0214] Where m is the total number of subdivision units within the aforementioned zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. j G is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit.

[0215] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0216] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R, the resource size R of subdivision unit k is determined according to the following expression. k :

[0217]

[0218] Based on this, by applying the storage medium provided by this invention for determining the spatial distribution of resources, even with only basic geological conditions and total reserve size of the resource basin, the spatial distribution characteristics of reserves and traps within the basin, as well as the total undiscovered resource size of each sub-unit, can be quickly and conveniently predicted. This enables the determination of the spatial distribution of undiscovered oil and gas resources in the entire oil and gas basin evaluation zone. This storage medium can quickly identify favorable target areas with limited exploration data, initially screening blocks worthy of further in-depth research and exploration, thus efficiently solving the problem of how to make investment decisions for low-exploration projects with limited data, and improving the efficiency of subsequent project decision-making. Furthermore, using the storage medium disclosed in this invention, while mitigating exploration risks, can better meet the company's portfolio optimization needs, providing a practical method for optimizing investment quality and efficiency.

[0219] Example Six

[0220] This embodiment provides an electronic device including a memory and a processor. The memory stores a computer program, which, when executed by the processor, performs the method for determining resource space distribution as described in any of Embodiments 1 to 4. It is understood that the electronic device may also include multimedia components, input / output (I / O) interfaces, and communication components.

[0221] The processor is used to execute all or part of the steps in the method for determining resource spatial distribution characteristics as described in Examples 1 to 4. The memory is used to store various types of data, which may include, for example, instructions for any application or method in the electronic device, as well as application-related data.

[0222] The processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic components, and is used to execute the method for determining resource space distribution in the above embodiments.

[0223] Memory can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0224] The multimedia component may include a screen, which may be a touchscreen, and an audio component for outputting and / or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory or transmitted via a communication component. The audio component also includes at least one speaker for outputting audio signals.

[0225] I / O interfaces provide interfaces between the processor and other interface modules, such as keyboards, mice, and buttons. These buttons can be virtual or physical.

[0226] Communication components are used for wired or wireless communication between the electronic device and other devices. Wireless communication includes, for example, Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or one or more combinations thereof. Therefore, the corresponding communication component may include: a Wi-Fi module, a Bluetooth module, or an NFC module.

[0227] When the above computer program is executed by the processor, it can perform the following method steps:

[0228] Predict the total undiscovered resource size R and the total number of successful traps N within the predicted zone;

[0229] Based on the geological conditions of the zone, the zone is divided into several sub-units;

[0230] Assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map;

[0231] Assign success probability values ​​to the target hydrocarbon accumulation elements in each sub-unit to obtain a probability map of target hydrocarbon accumulation elements;

[0232] Based on the trap probability map and the target hydrocarbon accumulation element probability map, a geological risk unit overlay map representing the geological success rate is generated;

[0233] For each sub-unit, obtain the closure probability T of sub-unit k from the closure probability map. k Geological success rate G of subdivided unit k is obtained from the geological risk unit overlay map. k and the area A of the subdivided unit k ;

[0234] Based on the total number of successfully closed loops N, the area A k The probability of trapping T k and geological success rate G k Determine the number of successful traps TS of subdivision unit k. k ;

[0235] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R determines the resource size R of subdivided unit k. k This allows for the determination of the spatial distribution of resources in the aforementioned zones based on the scale of resources to be discovered in each sub-unit.

[0236] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0237] The total undiscovered resource size in the above-mentioned zones can be predicted using the seventh approximation method, reservoir size sequence method, exploration efficiency trend method, or geological Pareto method.

[0238] Specifically, the aforementioned target hydrocarbon accumulation elements include four elements: source rocks, reservoirs, caprocks, and conditions for hydrocarbon migration, accumulation, and preservation.

[0239] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0240] Success probability values ​​were assigned to the four hydrocarbon accumulation elements corresponding to each subdivided unit to obtain the probability maps of source rocks, reservoirs, caprocks, and hydrocarbon migration, accumulation, and preservation conditions for the above-mentioned zones.

[0241] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0242] By overlaying the probability maps of traps, source rocks, reservoirs, caprocks, and oil and gas migration, accumulation, and preservation conditions, a geological risk unit overlay map is formed.

[0243] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0244] For each sub-unit, the success probabilities corresponding to the sub-unit in the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and oil and gas migration, accumulation, and preservation condition probability map are multiplied together, and then a geological risk unit overlay map is formed based on the product of the success probabilities corresponding to each sub-unit.

[0245] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0246] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0247] Based on the total number of successful oil and gas traps N and their area A k The probability of trapping T k Geological success rate G k The number of successful traps TS in subdivision unit k is determined by multiplying the trapping probability area by the following expression. k :

[0248]

[0249] Where m is the total number of subdivision units within the aforementioned zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. j G is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit.

[0250] Furthermore, when the above computer program is executed by the processor, it can also implement the following method steps:

[0251] Based on the total number of successful traps N and the number of successful traps TS k And the total undiscovered resource size R, the resource size R of subdivision unit k is determined according to the following expression. k :

[0252]

[0253] Based on this, the present invention provides an electronic device for determining the spatial distribution of resources. Even with only basic geological conditions and total reserves of the resource basin where the project is located, a simple and intuitive process can predict the spatial distribution characteristics of reserves and traps within the basin, as well as the scale of undiscovered resources in each sub-unit. This enables the determination of the spatial distribution of undiscovered oil and gas resources in the entire oil and gas basin evaluation zone. Using the process of this invention, the spatial distribution characteristics of reserves and traps within the basin, as well as the scale of undiscovered resources in each sub-unit, can be predicted. This electronic device can quickly identify favorable target areas with limited exploration data, initially screening blocks worthy of further in-depth research and exploration, thus efficiently solving the problem of how to make investment decisions for low-exploration projects with limited data, effectively improving the efficiency of project decision-making. Using the electronic device disclosed in this invention, while mitigating exploration risks, it can better meet the company's portfolio optimization needs, providing a practical method and means to optimize investment quality and efficiency.

[0254] While the embodiments disclosed in this invention are as described above, the above content is merely for the purpose of facilitating understanding of this invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for determining the spatial distribution of resources, characterized in that, Includes the following steps: Predict the total undiscovered resource size R and the total number of successful traps N within the predicted zone; Based on the geological conditions of the zone, the zone is divided into multiple sub-units; Assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map; Assign a success probability value to the target hydrocarbon accumulation element of each sub-unit to obtain a target hydrocarbon accumulation element probability map; Based on the trap probability map and the target hydrocarbon accumulation element probability map, a geological risk unit overlay map representing the geological success rate is formed; For each sub-unit, the closure probability T of sub-unit k is obtained from the closure probability map. k The geological success rate G of the subdivided unit k is obtained from the overlay map of the geological risk units. k and the area A of the subdivided unit k ; Based on the total number of successfully enclosed traps N and the area A k The trapping probability T k and the geological success rate G k Determine the number of successful traps TS of the subdivision unit k. k ; Based on the total number of successful traps N and the number of successful traps TS k The total undiscovered resource size R determines the resource size R of the subdivision unit k. k Thus, the spatial distribution of resources in the zone is determined based on the scale of resources to be discovered in each sub-unit; Wherein, the total number of successfully closed loops N and the area A are... k The trapping probability T k and the geological success rate G k Determine the number of successful traps TS of the subdivision unit k. k include: Based on the total number of successfully trapped structures N and the area A k The trapping probability T k The geological success rate G k The number of successful traps TS of subdivision unit k is determined by multiplying the trapping probability area by the following expression. k : ， Where m is the total number of subdivision units within the zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. j G is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit; Wherein, the product of the closure probability area is .

2. The method according to claim 1, characterized in that, The total undiscovered resource size within the prediction zone includes: The total undiscovered resource size within the zone is predicted using the seventh approximation method, reservoir size sequence method, exploration efficiency trend method, or geological Pareto method.

3. The method according to claim 1, characterized in that, The target hydrocarbon accumulation elements include four elements: source rocks, reservoirs, caprocks, and conditions for hydrocarbon migration, accumulation, and preservation. Assign a success probability value to the target hydrocarbon accumulation elements in each sub-unit to obtain a target hydrocarbon accumulation element probability map, including: Success probability values ​​are assigned to the four hydrocarbon accumulation elements corresponding to each subdivided unit to obtain the source rock probability map, reservoir probability map, caprock probability map, and hydrocarbon migration, accumulation, and preservation condition probability map of the zone.

4. The method according to claim 3, characterized in that, Based on the trap probability map and the target hydrocarbon accumulation element probability map, a geological risk unit overlay map representing the geological success rate is formed, including: The probability maps of traps, source rocks, reservoirs, caprocks, and oil and gas migration, accumulation, and preservation conditions are overlaid to form the geological risk unit overlay map.

5. The method according to claim 4, characterized in that, The process of overlaying the trap probability map, source rock probability map, reservoir probability map, caprock probability map, and oil and gas migration, accumulation, and preservation condition probability map to form the geological risk unit overlay map includes: For each subdivided unit, the success probabilities corresponding to the subdivided unit in the trap probability map, the source rock probability map, the reservoir probability map, the caprock probability map, and the oil and gas migration, accumulation, and preservation condition probability map are multiplied together to form a geological risk unit overlay map based on the product of the success probabilities corresponding to each subdivided unit.

6. The method according to claim 1, characterized in that, The number of successful traps is based on the total number of successful traps N and the number of successful traps TS. k The total undiscovered resource size R determines the resource size R of the subdivision unit k. k include: Based on the total number of successful traps N and the number of successful traps TS k The total undiscovered resource size R is determined according to the following expression, which is used to determine the resource size R of the subdivision unit k. k : 。 7. An apparatus for determining the spatial distribution of resources, characterized in that, Includes the following modules: The prediction module is used to predict the total size of resources to be discovered R and the total number of successful traps N within the zone; The partitioning module is used to divide the zone into multiple sub-units based on the geological conditions of the zone; The first acquisition module is used to assign a success probability value to the oil and gas trap integrity of each sub-unit to obtain a trap probability map; The second acquisition module is used to assign a success probability value to the target hydrocarbon accumulation elements of each sub-unit to obtain a target hydrocarbon accumulation element probability map. The generation module is used to generate a geological risk unit overlay map representing the geological success rate based on the trap probability map and the target hydrocarbon accumulation element probability map. The third acquisition module is used to acquire the closure probability T of sub-unit k from the closure probability map for each sub-unit. k The geological success rate G of the subdivided unit k is obtained from the overlay map of the geological risk units. k and the area A of the subdivided unit k ; The first calculation module is used to calculate based on the total number of successfully closed loops N and the area A. k The trapping probability T k and the geological success rate G k Determine the number of successful traps TS of the subdivision unit k. k ; The second calculation module is used to calculate based on the total number of successful traps N and the number of successful traps TS. k The total undiscovered resource size R determines the resource size R of the subdivision unit k. k Thus, the spatial distribution of resources in the zone is determined based on the scale of resources to be discovered in each sub-unit; The first calculation module is also used for: Based on the total number of successfully trapped structures N and the area A k The trapping probability T k The geological success rate G k The number of successful traps TS of subdivision unit k is determined by multiplying the trapping probability area by the following expression. k : ， Where m is the total number of subdivision units within the zone, j = 1, k, ..., m, T j Let A be the trapping probability of the j-th subdivision unit. j G is the area of ​​the j-th subdivision unit. j Let be the geological success rate of the j-th subdivision unit; Wherein, the product of the closure probability area is .

8. A storage medium, characterized in that, The storage medium stores a program, which, when executed by a processor, performs the method described in any one of claims 1 to 6.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program that is executed by the processor to perform the method as described in any one of claims 1 to 6.

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