Pore type reservoir classification method, system, equipment and medium

Abstract

The invention relates to a pore type reservoir classification method, system, equipment and medium, and belongs to the technical field of oil reservoir exploitation, the pore type reservoir classification method realizes the following two functions: the first function is to carry out quantitative comprehensive characterization on pore throat radius distribution, the second function is to carry out scale division on a pore throat space by taking the pore throat radius as a scale, and the third function is to carry out scale division on the pore throat space. And 3, classifying the reservoirs, and determining the pore throat space composition of each scale of the reservoirs of different types. According to the method, the homogeneity of the pore-type complex carbonate reservoir is comprehensively considered, the pore throat characteristics are quantitatively represented by the pore throat comprehensive radius Rc, large, medium and small pore throats are scientifically defined and defined through the pore throat comprehensive radius Rc and the permeability Perm, all samples are classified into a differential reservoir, a medium reservoir and a good reservoir by combining the pore throat comprehensive radius Rc, and the pore throat comprehensive radius Rc and the permeability Perm are combined. The objective and scientific reservoir classification is realized from the microscopic characteristics and physical characteristics of the reservoir.

Description

Technical Field

[0001] This disclosure belongs to the field of oil reservoir development technology, and in particular relates to a method, system, equipment and medium for classifying porous reservoirs. Background Technology

[0002] Oil and gas reservoirs, generally speaking, exhibit significant differences in porosity and permeability due to sedimentary, differential diagenetic, and tectonic processes, resulting in strong heterogeneity and a diverse range of reservoir rock types. Therefore, given this heterogeneity, it is necessary to classify reservoirs into several relatively homogeneous categories to improve geological understanding and support efficient oil and gas reservoir development. Domestic and international research can be broadly summarized into the following classification approaches: rock structure classification, porosity classification, physical property classification, nuclear magnetic resonance (NMR) response classification, and conventional logging response classification. However, in this field, the academic community has not yet developed a method for classifying specific oil and gas reservoirs by dividing their pore storage space at different scales and characterizing their microscopic heterogeneity. Therefore, it is necessary to provide a new method, system, device, and medium for classifying porous reservoirs to solve the above-mentioned technical problems.

[0003] Therefore, it is necessary to provide a new method, system, device, and medium for classifying porous reservoirs to solve the above-mentioned technical problems. Summary of the Invention

[0004] The purpose of this disclosure is to provide a method, system, device, and medium for classifying porous reservoirs in order to solve the above-mentioned problems.

[0005] This disclosure achieves the above objectives through the following technical solutions:

[0006] A method for classifying porous reservoirs includes the following steps:

[0007] Multiple rock samples were obtained from the porous reservoir to be classified;

[0008] Calculate the pore throat radius distribution of the rock sample;

[0009] A cumulative permeability contribution curve was plotted based on the pore throat radius distribution.

[0010] The comprehensive pore throat radius Rc of the rock sample is calculated based on the pore throat radius distribution and the cumulative permeability contribution curve.

[0011] The permeability Perm value of the rock sample is obtained, and the radius boundary points of small pores, medium pores, and large pores are defined based on the comprehensive pore throat radius Rc of the rock sample and the permeability Perm value.

[0012] The rock samples are classified based on the comprehensive pore throat radius Rc and the radius boundary point, and the reservoir space composition of different scales in different types of reservoirs is clarified.

[0013] As a further optimization of this disclosure, calculating the pore throat radius distribution of the rock sample includes:

[0014] Core testing was performed on the rock sample to obtain mercury intrusion porosimetry data;

[0015] Based on the aforementioned mercury intrusion porosimetry data, the pore throat radius distribution is calculated using the following formula:

[0016] PTR = 106.7 / Pc;

[0017] Where PTR represents the pore throat radius distribution and Pc represents the capillary pressure.

[0018] As a further optimization of this disclosure, the cumulative permeability contribution curve plotted based on the pore throat radius distribution includes:

[0019] Based on the pore throat radius distribution, the cumulative permeability contribution curve is calculated using the permeability contribution rate calculation formula for different pore throats, as follows:

[0020] Kc=(Ri 2 *Si) / ∑(Ri 2 *Si)*100;

[0021] Where Kc represents the permeability contribution rate, Ri represents the pore throat radius corresponding to the i-th data point of the mercury intrusion porosimetry curve, and Si represents the increment of injected mercury corresponding to the i-th data point of the mercury intrusion porosimetry curve.

[0022] As a further optimization of this disclosure, the formula for calculating the comprehensive orifice throat radius Rc is as follows:

[0023] Rc = ∑Ci*Ri;

[0024] Where Ci represents the weight corresponding to the i-th peak of the pore throat distribution, and Ri represents the pore throat radius corresponding to the i-th data point of the mercury intrusion curve.

[0025] As a further optimization of this disclosure, the permeability Perm value of the rock sample is obtained, and the radius boundary points for small pores, mesopores, and macropores are defined based on the comprehensive pore throat radius Rc of the rock sample and the permeability Perm value, including:

[0026] Obtain the permeability (Perm) value of the rock sample;

[0027] Plot a scatter plot of the composite pore throat radius Rc and the permeability Perm value for each of the rock samples, establish the correlation between the composite pore throat radius Rc and the permeability Perm value, clarify the regions with different linear relationships, and define the radius boundary points of small pores, medium pores, and large pores.

[0028] As a further optimization of this disclosure, the rock samples are classified based on the comprehensive pore throat radius Rc and the radius boundary point, and the reservoir space composition of different types of reservoirs at different scales is clarified as follows:

[0029] The comprehensive pore throat radius Rc of each rock sample is used to define the radius boundary points of small pores, medium pores, and large pores. Each rock sample is classified into poor reservoirs, medium reservoirs, and good reservoirs, and the characteristics of mercury intrusion porosimetry curves are summarized.

[0030] By combining the radius boundaries of small, medium, and large pores, the composition of reservoir space at different scales in different types of reservoirs is clarified.

[0031] A porosity reservoir classification system, comprising:

[0032] The sample acquisition module is used to acquire multiple rock samples from porous reservoirs to be classified.

[0033] A pore throat radius distribution calculation module is used to calculate the pore throat radius distribution of the rock sample;

[0034] A plotting module is used to plot the cumulative permeability contribution curve based on the pore throat radius distribution;

[0035] The integrated pore throat radius calculation module is used to calculate the integrated pore throat radius Rc of the rock sample based on the pore throat radius distribution and the cumulative permeability contribution curve;

[0036] The radius demarcation module is used to obtain the permeability Perm value of the rock sample and to define the radius demarcation points of small pores, medium pores, and large pores based on the comprehensive pore throat radius Rc and the permeability Perm value of the rock sample.

[0037] The classification module is used to classify the rock samples based on the comprehensive pore throat radius Rc and the radius boundary point, and to clarify the reservoir space composition of different types of reservoirs at different scales.

[0038] An electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0039] Memory, used to store computer programs;

[0040] The processor is used to implement a porosity reservoir classification method when executing programs stored in memory.

[0041] A computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for classifying porous reservoirs.

[0042] The beneficial effects of this disclosure are as follows:

[0043] This disclosure targets porous complex carbonate reservoirs. Taking into account the homogeneity of carbonate reservoirs, it scientifically defines and categorizes large, medium, and small pore throats using the comprehensive pore throat radius Rc and permeability Perm. Combined with the comprehensive pore throat radius Rc, it classifies each sample into poor, medium, and good reservoirs. This achieves objective and scientific reservoir classification based on reservoir microscopic and physical characteristics, laying the foundation for geological modeling and reservoir porosity and permeability characterization, and supporting numerical simulation, reservoir management, and production prediction. Attached Figure Description

[0044] Figure 1 This is a flowchart of the method disclosed herein;

[0045] Figure 2 This is a schematic diagram illustrating the calculation of the comprehensive pore throat radius Rc for the multi-peak pore throat distribution in an embodiment of this disclosure;

[0046] Figure 3 This is a scatter plot of the combined pore throat radius Rc and permeability Perm in the embodiments of this disclosure, and a schematic diagram of the definition of pore throats of different scales.

[0047] Figure 4 This is a schematic diagram of the mercury intrusion curve characteristics of different types of reservoirs in the embodiments of this disclosure. After rotation, the left, middle and right sides are respectively: poor reservoir, medium reservoir and good reservoir.

[0048] Figure 5 This is a schematic diagram of the reservoir space composition of different types of reservoirs and different scales in the embodiments of this disclosure. After rotation, the left, middle and right sides are: poor reservoir, medium reservoir and good reservoir.

[0049] Figure 6 This is a system structure block diagram of an embodiment of this disclosure;

[0050] Figure 7 This is a block diagram of the device structure in an embodiment of this disclosure. Detailed Implementation

[0051] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0052] like Figure 1 As shown, a method for classifying porous reservoirs includes the following steps:

[0053] Multiple rock samples were obtained from the porous reservoir to be classified;

[0054] Calculate the pore throat radius distribution of the rock sample;

[0055] A cumulative permeability contribution curve was plotted based on the pore throat radius distribution.

[0056] The comprehensive pore throat radius Rc of the rock sample is calculated based on the pore throat radius distribution and the cumulative permeability contribution curve.

[0057] The permeability Perm value of the rock sample is obtained, and the radius boundary points of small pores, medium pores, and large pores are defined based on the comprehensive pore throat radius Rc of the rock sample and the permeability Perm value.

[0058] The rock samples are classified based on the comprehensive pore throat radius Rc and the radius boundary point, and the reservoir space composition of different scales in different types of reservoirs is clarified.

[0059] The calculation of the pore throat radius distribution of the rock sample includes:

[0060] Core testing was performed on the rock sample to obtain mercury intrusion porosimetry data;

[0061] Based on the aforementioned mercury intrusion porosimetry data, the pore throat radius distribution is calculated according to the pore throat radius calculation formula, such as... Figure 2 The blue line, the formula is as follows:

[0062] PTR = 106.7 / Pc;

[0063] Where PTR represents the pore throat radius distribution and Pc represents the capillary pressure.

[0064] The cumulative permeability contribution curve plotted based on the pore throat radius distribution includes:

[0065] Based on the aforementioned pore throat radius distribution, and combined with the permeability contribution rate calculation formula for different pore throats, the cumulative permeability contribution curve is calculated, as follows: Figure 2 The orange line, the formula is as follows:

[0066] Kc=(Ri 2 *Si) / ∑(Ri 2 *Si)*100;

[0067] Where Kc represents the permeability contribution rate, Ri represents the pore throat radius corresponding to the i-th data point of the mercury intrusion porosimetry curve, and Si represents the increment of injected mercury corresponding to the i-th data point of the mercury intrusion porosimetry curve.

[0068] The formula for calculating the comprehensive pore throat radius Rc of a single-peak (or multi-peak) pore throat distribution is as follows:

[0069] Rc = ∑Ci*Ri;

[0070] Where Ci represents the weight corresponding to the i-th peak of the pore throat distribution, and Ri represents the pore throat radius corresponding to the i-th data point of the mercury intrusion curve.

[0071] The permeability Perm value of the rock sample is obtained. Based on the comprehensive pore throat radius Rc of the rock sample and the permeability Perm value, the radius boundary points for small pores, mesopores, and macropores are defined, including:

[0072] Obtain the permeability (Perm) value of the rock sample;

[0073] Scatter plots were generated for the composite pore throat radius Rc and the permeability Perm value of each of the aforementioned rock samples. The correlation between the composite pore throat radius Rc and the permeability Perm value was established, different linear relationship regions were identified, and the radius boundaries for small, medium, and large pores were defined. Figure 3 As shown in the table below, the throat radius values ​​for storage spaces of different scales are defined:

[0074] Table 1. Defining the Throat Radius Values ​​of Storage Spaces at Different Scales

[0075] Scale type small hole central hole Large hole Scale (micrometers) Rc<0.1 0.1<Rc<2.2 Rc>2.2

[0076] The rock samples are classified based on their comprehensive pore throat radius Rc and the radius boundary point, and the reservoir space composition of different types of reservoirs at different scales is clarified, including:

[0077] The comprehensive pore throat radius Rc of each rock sample was used to define the boundary points between small, medium, and large pore radii. The rock samples were then classified into poor, medium, and good reservoirs. The characteristics of mercury injection curves were summarized, such as... Figure 4 As shown;

[0078] By combining the radius boundaries of small, medium, and large pores, the composition of reservoir space at different scales in different types of reservoirs is clarified, such as... Figure 5 As shown.

[0079] like Figure 6 As shown, embodiments of this disclosure provide a porosity reservoir classification system, including:

[0080] The sample acquisition module is used to acquire multiple rock samples from porous reservoirs to be classified.

[0081] A pore throat radius distribution calculation module is used to calculate the pore throat radius distribution of the rock sample;

[0082] A plotting module is used to plot the cumulative permeability contribution curve based on the pore throat radius distribution;

[0083] The integrated pore throat radius calculation module is used to calculate the integrated pore throat radius Rc of the rock sample based on the pore throat radius distribution and the cumulative permeability contribution curve;

[0084] The radius demarcation module is used to obtain the permeability Perm value of the rock sample and to define the radius demarcation points of small pores, medium pores, and large pores based on the comprehensive pore throat radius Rc and the permeability Perm value of the rock sample.

[0085] The classification module is used to classify the rock samples based on the comprehensive pore throat radius Rc and the radius boundary point, and to clarify the reservoir space composition of different types of reservoirs at different scales.

[0086] The implementation process of the functions and roles of each module in the above system is detailed in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0087] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The system embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this disclosure according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0088] In the above embodiments, any number of modules can be combined into one module, or any one module can be split into multiple modules. Alternatively, at least some functionality of one or more modules can be combined with at least some functionality of other modules and implemented in one module. At least one of the modules can be at least partially implemented as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or any other reasonable method of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three methods. Alternatively, at least one of the modules can be at least partially implemented as a computer program module that, when run, performs a corresponding function.

[0089] See Figure 7 The electronic device provided in the embodiments of this disclosure includes a processor 1110, a communication interface 1120, a memory 1130 and a communication bus 1140, wherein the processor 1110, the communication interface 1120 and the memory 1130 communicate with each other through the communication bus 1140.

[0090] Memory 1130 is used to store computer programs;

[0091] When the processor 1110 executes the program stored in the memory 1130, it implements the porosity reservoir classification method shown below.

[0092] The aforementioned communication bus 1140 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus 1140 can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, it is represented by only one thick line in the figure, but this does not indicate that there is only one bus or one type of bus.

[0093] The communication interface 1120 is used for communication between the above-mentioned electronic device and other devices.

[0094] The memory 1130 may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory 1130 may also be at least one storage device located remotely from the aforementioned processor 1110.

[0095] The processor 1110 mentioned above can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0096] Embodiments of this disclosure also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the porosity reservoir classification method described above.

[0097] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments; or it may exist independently and not assembled into the device / apparatus. The computer-readable storage medium carries one or more programs that, when executed, implement the porosity reservoir classification method according to embodiments of this disclosure.

[0098] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0099] The embodiments described above are merely examples of several implementations of this disclosure, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent disclosure. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this disclosure, and these modifications and improvements all fall within the protection scope of this disclosure.

Claims

1. A method for classifying porous reservoirs, characterized in that, Includes the following steps: Multiple rock samples were obtained from the porous reservoir to be classified; Calculate the pore throat radius distribution of the rock sample; A cumulative permeability contribution curve was plotted based on the pore throat radius distribution. The comprehensive pore throat radius Rc of the rock sample is calculated based on the pore throat radius distribution and the cumulative permeability contribution curve. The permeability Perm value of the rock sample is obtained, and the radius boundary points of small pores, medium pores, and large pores are defined based on the comprehensive pore throat radius Rc of the rock sample and the permeability Perm value. The rock samples are classified based on the comprehensive pore throat radius Rc and the radius boundary point, and the reservoir space composition of different scales in different types of reservoirs is clarified.

2. The method for classifying porous reservoirs according to claim 1, characterized in that, The calculation of the pore throat radius distribution of the rock sample includes: Core testing was performed on the rock sample to obtain mercury intrusion porosimetry data; Based on the aforementioned mercury intrusion porosimetry data, the pore throat radius distribution is calculated using the following formula: PTR = 106.7 / Pc; Where PTR represents the pore throat radius distribution and Pc represents the capillary pressure.

3. The method for classifying porous reservoirs according to claim 1, characterized in that, The cumulative permeability contribution curve plotted based on the pore throat radius distribution includes: Based on the pore throat radius distribution, the cumulative permeability contribution curve is calculated using the permeability contribution rate calculation formula for different pore throats, as follows: Kc=(Ri 2 *Si) / ∑(Ri 2 *Si)*100; Where Kc represents the permeability contribution rate, Ri represents the pore throat radius corresponding to the i-th data point of the mercury intrusion porosimetry curve, and Si represents the increment of injected mercury corresponding to the i-th data point of the mercury intrusion porosimetry curve.

4. The method for classifying porous reservoirs according to claim 1, characterized in that, The formula for calculating the combined throat radius Rc is as follows: Rc = ∑Ci*Ri; Where Ci represents the weight corresponding to the i-th peak of the pore throat distribution, and Ri represents the pore throat radius corresponding to the i-th data point of the mercury intrusion curve.

5. The method for classifying porous reservoirs according to claim 1, characterized in that, The permeability Perm value of the rock sample is obtained. Based on the comprehensive pore throat radius Rc of the rock sample and the permeability Perm value, the radius boundary points for small pores, mesopores, and macropores are defined, including: Obtain the permeability (Perm) value of the rock sample; Plot a scatter plot of the composite pore throat radius Rc and the permeability Perm value for each of the rock samples, establish the correlation between the composite pore throat radius Rc and the permeability Perm value, clarify the regions with different linear relationships, and define the radius boundary points of small pores, medium pores, and large pores.

6. The method for classifying porous reservoirs according to claim 1, characterized in that, The rock samples are classified based on their comprehensive pore throat radius Rc and the radius boundary point, and the reservoir space composition of different types of reservoirs at different scales is clarified, including: The comprehensive pore throat radius Rc of each rock sample is used to define the radius boundary points of small pores, medium pores, and large pores. Each rock sample is classified into poor reservoirs, medium reservoirs, and good reservoirs, and the characteristics of mercury intrusion porosimetry curves are summarized. By combining the radius boundaries of small, medium, and large pores, the composition of reservoir space at different scales in different types of reservoirs is clarified.

7. A porosity-type reservoir classification system, characterized in that, include: The sample acquisition module is used to acquire multiple rock samples from porous reservoirs to be classified. A pore throat radius distribution calculation module is used to calculate the pore throat radius distribution of the rock sample; A plotting module is used to plot the cumulative permeability contribution curve based on the pore throat radius distribution; The integrated pore throat radius calculation module is used to calculate the integrated pore throat radius Rc of the rock sample based on the pore throat radius distribution and the cumulative permeability contribution curve; The radius demarcation module is used to obtain the permeability Perm value of the rock sample and to define the radius demarcation points of small pores, medium pores, and large pores based on the comprehensive pore throat radius Rc and the permeability Perm value of the rock sample. The classification module is used to classify the rock samples based on the comprehensive pore throat radius Rc and the radius boundary point, and to clarify the reservoir space composition of different types of reservoirs at different scales.

8. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in a memory, implements the porosity reservoir classification method according to any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the porosity reservoir classification method according to any one of claims 1-6.

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