Reservoir water saturation evaluation method based on volume model, electronic equipment and storage medium
By using a volumetric model-based method to evaluate reservoir water saturation and calculating reservoir parameters using well logging curves and core analysis data, the problem of evaluating low-resistivity oil reservoirs in the absence of core data has been solved, and accurate evaluation of high clay content and low-resistivity oil reservoirs has been achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINA NAT PETROLEUM CORP
- Filing Date
- 2024-10-30
- Publication Date
- 2026-05-01
AI Technical Summary
Existing methods for evaluating the water saturation of low-resistivity oil reservoirs are difficult to use accurately when core experimental data is lacking and well logging series are incomplete. In particular, the applicability of the Alchian formula and the Waxman-Smits model is limited under complex geological conditions.
A volumetric model-based method for evaluating reservoir water saturation was adopted. By determining the resistivity of clay, the resistivity of formation water, and the porosity of the reservoir, reservoir parameters were calculated using well logging curves, sonic transit time, and neutron and density curves. A porosity calculation model was established by combining core analysis data to realize the calculation of reservoir water saturation.
It can accurately calculate reservoir water saturation without the need for core analysis data, and is applicable to oil-bearing reservoirs with high clay content and low resistivity, thus expanding its scope of application and improving the accuracy and comprehensiveness of the evaluation.
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Figure CN121952579A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of reservoir logging evaluation technology, specifically a reservoir water saturation evaluation method, electronic equipment, and storage medium based on a volumetric model. Background Technology
[0002] The existing methods for evaluating the water saturation of low-resistivity oil reservoirs mainly fall into the following two categories:
[0003] (1) Variable parameter Alzer formula. The specific approach includes analyzing the causes of low resistivity and adjusting the values of parameters m and n. For example, when the formation water salinity is high, the influence of salinity on RT, RO, and Rw values increases sequentially, and the values of m and n also increase slightly. As the pore structure becomes more complex, the value of m increases and the value of n decreases. As the clay content increases, the values of m and n decrease. The water saturation can be analyzed in conjunction with core samples to adjust the values of m and n and establish a saturation calculation model. Its applicable condition is that it is based on the analysis of the causes of low resistivity and combined with a large amount of water saturation data from core samples.
[0004] This method is suitable for environments with relatively simple pore structures, such as pure sandstone reservoirs. However, under complex geological conditions such as low-grade, low-saturation, and low-resistivity oil layers, the conductivity of reservoir rocks differs significantly from that of conventional reservoirs, with a clear non-Arche relationship. The Arche formula is difficult to use for accurate evaluation of water saturation.
[0005] (2) Waxman-Smits (WS model). Its theory posits that the parallel conductance of free electrolytes and clay cation exchange components in fully aqueous rocks constitutes the conductivity of the fully aqueous rock. Furthermore, it assumes that the contribution of free electrolytes and clay cation exchange conductance to the conductivity of sandstone is based on the geometric conductivity constant, thus deriving a conductivity model for argillaceous sandstone:
[0006]
[0007] For ease of understanding, it can be converted into an Alchian-like model:
[0008]
[0009] However, this method requires experimental data such as core analysis of water saturation. It is applicable to sandstone and mudstone reservoirs with high clay content and low mineralization, but not to low-resistivity oil reservoirs. Summary of the Invention
[0010] This invention provides a reservoir water saturation evaluation method, electronic device, and storage medium based on a volumetric model, which overcomes the shortcomings of the prior art. It can effectively solve the problem that existing low-resistivity oil reservoir water saturation evaluation methods cannot evaluate reservoir water saturation in scenarios where core experimental data is missing or well logging series are incomplete.
[0011] One of the technical solutions of this invention is achieved through the following measures: a reservoir water saturation evaluation method based on a volumetric model, comprising:
[0012] Determine the resistivity of clay, the resistivity of formation water, the clay content of the reservoir, and the porosity of the reservoir;
[0013] By substituting the resistivity of clay, the resistivity of formation water, the clay content of the reservoir, and the porosity of the reservoir into the response equation of the reservoir volume model, the relative volume of porosity occupied by formation water and the relative volume of porosity occupied by formation oil are obtained, and the water saturation of the reservoir is determined. The response equation of the reservoir volume model is determined according to the reservoir type.
[0014] The following are further optimizations and / or improvements to the above-mentioned technical solution:
[0015] The process of determining reservoir porosity as described above includes:
[0016] Reservoir porosity is calculated using sonic transit time logging curves, and the porosity calculation is combined with the Wyllie time-averaged equation based on lithology or clay content.
[0017] Reservoir porosity is calculated using neutron and density curves, regardless of whether the response is positive or negative.
[0018] The reservoir porosity was verified.
[0019] The above verification of reservoir porosity includes:
[0020] A porosity calculation model was established by combining core analysis data, and the reservoir porosity was obtained using the porosity calculation model. The porosity calculation model was established by obtaining density data and void analysis data from core analysis data and then using multiple linear regression.
[0021] Determine whether the reservoir porosity calculated using curves is consistent with the reservoir porosity obtained using a porosity calculation model;
[0022] If the response is no, the process of calculating reservoir porosity using curves is adjusted; if the response is yes, different porosity ranges are divided according to reservoir porosity, and reservoir types are classified according to the porosity ranges.
[0023] The above-mentioned neutron and density curves are used to calculate the reservoir clay content using the following formula:
[0024]
[0025] Among them, V SH The content of clay; φ N φ D Neutron porosity and density porosity of the target layer; φ Nshφ Dsh These represent the neutron porosity and density porosity of clay, respectively; ρb, ρma, ρsh, ρ f φ represents the density of the strata, rock skeleton, mudstone, and pore fluids. Nma Neutron porosity of the rock framework; φ Nf φ represents the neutron porosity of the porous fluid. Nma φ Nsh φ Nf These are the hydrogen content indices for the rock strata, mudstone, and fluids, respectively.
[0026] The resistivity of the clay and the resistivity of the formation water were obtained by analyzing the well logging curves.
[0027] The above also includes using well logging curves, reservoir porosity, reservoir water saturation, and oil testing data to select fluid identification parameters, establish fluid identification charts, and realize reservoir fluid interpretation.
[0028] The second technical solution of the present invention is achieved through the following measures: a reservoir water saturation evaluation method based on a volumetric model, comprising:
[0029] The basic analysis unit determines the resistivity of clay, the resistivity of formation water, the clay content of the reservoir, and the porosity of the reservoir.
[0030] The water saturation determination unit inputs the clay resistivity, formation water resistivity, reservoir clay content, and reservoir porosity into the reservoir volume model response equation to obtain the relative volume of porosity occupied by formation water and the relative volume of porosity occupied by formation oil, thereby determining the water saturation of the reservoir. The reservoir volume model response equation is determined according to the reservoir type.
[0031] The following are further optimizations and / or improvements to the above-mentioned technical solution:
[0032] The aforementioned basic analysis unit includes:
[0033] The first analysis module analyzes the logging curves to obtain the resistivity of clay and formation water.
[0034] The second analysis module uses neutron and density curves to calculate the reservoir clay content using the following formula:
[0035]
[0036] Among them, V SH The content of clay; φ N φ D Neutron porosity and density porosity of the target layer; φ Nsh φ Dsh These represent the neutron porosity and density porosity of clay, respectively; ρb, ρma, ρsh, ρ fφ represents the density of the strata, rock skeleton, mudstone, and pore fluids. Nma Neutron porosity of the rock framework; φ Nf φ represents the neutron porosity of the porous fluid. Nma φ Nsh φ Nf These are the hydrogen content indices for the rock strata framework, mudstone, and fluids, respectively.
[0037] The third analysis module, which determines reservoir porosity, includes:
[0038] Reservoir porosity is calculated using sonic transit time logging curves, and the porosity calculation is combined with the Wyllie time-averaged equation based on lithology or clay content.
[0039] Reservoir porosity is calculated using neutron and density curves, regardless of whether the response is positive or negative.
[0040] Verify reservoir porosity;
[0041] The verification module verifies reservoir porosity, including:
[0042] A porosity calculation model was established by combining core analysis data, and the reservoir porosity was obtained using the porosity calculation model. The porosity calculation model was established by obtaining density data and void analysis data from core analysis data and then using multiple linear regression.
[0043] Determine whether the reservoir porosity calculated using curves is consistent with the reservoir porosity obtained using a porosity calculation model;
[0044] If the response is no, the process of calculating reservoir porosity using curves is adjusted; if the response is yes, different porosity ranges are divided according to reservoir porosity, and reservoir types are classified according to the porosity ranges.
[0045] The above also includes a chart analysis unit, which uses logging curves, reservoir porosity, reservoir water saturation, and oil testing data to select fluid identification parameters, establish a fluid identification chart, and realize reservoir fluid interpretation.
[0046] The third technical solution of the present invention is achieved through the following measures: a storage medium storing a computer program that can be read by a computer, the computer program being configured to execute a reservoir water saturation evaluation method based on a volume model when running.
[0047] The fourth technical solution of the present invention is achieved through the following measures: an electronic device, including a processor and a memory, wherein the memory stores a computer program, which is loaded and executed by the processor to implement a reservoir water saturation evaluation method based on a volume model.
[0048] This invention eliminates the need for experimental data such as core analysis water saturation data, solving the problem that existing methods cannot evaluate reservoir water saturation in scenarios where core experimental data is missing or well logging series are incomplete. Based on well logging curves, sonic transit time curves, neutron and density curves, the water saturation of the reservoir can be calculated. Furthermore, the reservoir water saturation evaluation method based on the volume model provided by this invention is not only applicable to sandstone and mudstone reservoirs with high clay content and low mineralization, but also to low resistivity oil layers, making it widely applicable. Attached Figure Description
[0049] Appendix Figure 1 This is a schematic diagram of a reservoir water saturation evaluation method provided in one embodiment of the present invention.
[0050] Appendix Figure 2 This is a schematic flowchart of a resistivity determination method provided in one embodiment of the present invention.
[0051] Appendix Figure 3 This is a schematic flowchart of a reservoir porosity determination method provided in one embodiment of the present invention.
[0052] Appendix Figure 4 This is a schematic diagram of another reservoir water saturation evaluation method provided in an embodiment of the present invention.
[0053] Appendix Figure 5 This is a schematic flowchart of a fluid identification map creation method according to an embodiment of the present invention.
[0054] Appendix Figure 6 This is a schematic diagram of a reservoir water saturation evaluation device provided in one embodiment of the present invention.
[0055] Appendix Figure 7 This is a schematic diagram of another reservoir water saturation evaluation device provided in an embodiment of the present invention. Detailed Implementation
[0056] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.
[0057] The present invention will be further described below with reference to embodiments and accompanying drawings:
[0058] Example 1: As shown in the attached document Figure 1 As shown in the figure, this invention discloses a reservoir water saturation evaluation method based on a volumetric model, comprising:
[0059] Step S110: Determine the clay resistivity, formation water resistivity, reservoir clay content, and reservoir porosity.
[0060] As attached Figure 2As shown, the steps above for determining the resistivity of clay and formation water specifically include:
[0061] Step S1111: Obtain the logging curve and standardize it. The standardization process of the logging curve includes:
[0062] (1) Obtain the logging curve and perform data cleaning on the logging curve, including removing outliers and clusters and filling in missing values.
[0063] Well logging curves utilize the relationship between formation physical parameters and well depth. By measuring physical quantities such as electrical, acoustic, and nuclear quantities of different formations in the wellbore, a continuous curve is plotted to reflect the characteristics of formation lithology, physical properties, and oil-bearing properties.
[0064] (2) Perform compaction correction and depth alignment on the logging curves;
[0065] Compaction correction is a crucial step in the well logging curve standardization process. During well logging, due to varying degrees of rock compaction, compaction correction aims to eliminate differences in logging responses from different wells within the same formation, ensuring comparability of logging data between different wells. Specifically, by selecting representative standard wells, a calibration curve is established between the logging curve and geological parameters. Then, logging data from other wells are calibrated against the corresponding geological parameters, thus achieving compaction correction.
[0066] Depth alignment is crucial for ensuring the consistency of logging data across depths, which is essential for subsequent geological interpretation and reservoir evaluation. Because depth deviations may occur during logging, depth alignment of logging curves is necessary to ensure accurate depth correspondence between logging data from different wells. Depth alignment is achieved by adjusting the depth scale of the logging curves, ensuring that logging data from all wells are compared and analyzed within the same depth range.
[0067] (3) Select key wells and standard layers.
[0068] (4) Correct the logging curve environment and check the consistency between wells.
[0069] Step S1112: Determine the resistivity of the clay and the resistivity of the formation water based on the resistivity curve in the standardized logging curve.
[0070] For example, look for water layers throughout the logging section (using the differences in conductivity of different rocks and minerals to distinguish formation properties). Once the water layer is found, the measured resistivity can be considered to be the resistivity of the formation water.
[0071] In the above steps, the reservoir clay content is calculated using the following formula based on neutron density curves:
[0072]
[0073] Among them, V SH The content of clay; φ N φ D Neutron porosity and density porosity of the target layer; φ Nsh φ Dsh These represent the neutron porosity and density porosity of clay, respectively; ρb, ρma, ρsh, ρ f φ represents the density of the strata, rock skeleton, mudstone, and pore fluids. Nma Neutron porosity of the rock framework; φ Nf φ represents the neutron porosity of the porous fluid. Nma φ Nsh φ Nf These are the hydrogen content indices for the rock strata, mudstone, and fluids, respectively.
[0074] As attached Figure 3 As shown, the process of determining reservoir porosity in the above steps includes:
[0075] Step S1121: Calculate reservoir porosity using sonic logging curves, and determine whether the porosity calculation meets the Wyllie time-averaged equation based on lithology or clay content.
[0076] In this step, the reservoir porosity is calculated using sonic transit time logging curves, as shown in the following formula:
[0077]
[0078] Where AC represents the acoustic transit time of the target layer, i.e., the logging value; AC ma For the acoustic transit time of the rock skeleton; AC ft This represents the acoustic time difference of the pore fluid.
[0079] In this step, it is determined whether the porosity calculation results satisfy the Wyllie time-averaged equation based on the lithology or clay content, where the Wyllie time-averaged equation is shown below:
[0080] Δt=(1-φ)Δt ma +φt f
[0081] Where Δt is the acoustic transit time of the target layer; φ is the reservoir porosity; Δt ma Acoustic transit time of rock strata; t f Pore fluid acoustic time difference.
[0082] Step S1122, in response to no, calculate reservoir porosity using neutron density curves.
[0083] Specifically, the calculation process for reservoir porosity using neutron and density curves is as follows:
[0084]
[0085] φ N =φ N
[0086]
[0087] Wherein, ρma, ρ b ρ f φ represents the density of the rock strata, formations, and pore fluids. N φ D Neutron porosity and density porosity of the target layer; φ N Read directly from the logging curve; φ is the reservoir porosity.
[0088] Step S1123: Verify the reservoir porosity.
[0089] Specifically, the process of verifying reservoir porosity includes:
[0090] (1) Establish a porosity calculation model by combining core analysis data, and use the porosity calculation model to obtain reservoir porosity. The porosity calculation model is obtained by obtaining density data and void analysis data from core analysis data and establishing it through multiple linear regression. This specific multiple linear regression process can be completed by existing software.
[0091] Furthermore, core analysis data can be used to train a neural network model to obtain a porosity calculation model.
[0092] (2) Determine whether the reservoir porosity calculated using the curve is consistent with the reservoir porosity obtained using the porosity calculation model; here, it is to determine whether the reservoir porosity calculated using the sonic transit logging curve or the reservoir porosity calculated using the neutron and density curve is consistent with the reservoir porosity obtained using the porosity calculation model.
[0093] Furthermore, φ can be calculated using density curves. D φ calculated by neutron and density curve intersection N-D Comparison of φ D and φ N-D The curve is used to determine the reservoir porosity type and the development of secondary porosity. When judging whether the reservoir porosity calculated using the curve is consistent with the reservoir porosity obtained using the porosity calculation model, if the reservoir type is consistent with the results shown in the rock thin section, the porosity type is considered to be accurately determined.
[0094] (3) If the response is no, then adjust the process of calculating reservoir porosity using curves. If the response is yes, then divide the range of different porosities according to the reservoir porosity, and divide the reservoir type according to the range of porosity.
[0095] It should be noted that the process of adjusting the calculation of reservoir porosity using curves can be to correct the porosity of the clay, or to select the curve with the smallest error between the previous porosity calculation results and experimental data to calculate the reservoir porosity.
[0096] Step S120: Substitute the clay resistivity, formation water resistivity, reservoir clay content, and reservoir porosity into the reservoir volume model response equation to obtain the relative volume of porosity occupied by formation water and the relative volume of porosity occupied by formation oil, and determine the water saturation of the reservoir. The reservoir volume model response equation is determined according to the reservoir type.
[0097] The above reservoir volume model response equation is determined based on the reservoir type, which includes single-mineral reservoirs, dual-mineral reservoirs, multi-mineral reservoirs, single-mineral reservoirs with argillaceous material, dual-mineral reservoirs with argillaceous material, and multi-mineral reservoirs with argillaceous material. Specifically, the reservoir volume model is determined based on the reservoir type, and then the reservoir volume model response equation is obtained through conventional logging response equation derivation methods.
[0098] The derivation of the conventional well logging response equation is shown below:
[0099]
[0100] In the formula: min, f(v), m, A, V, and B are the extreme values of the response, the component correlation function, different components, the theoretical values of the logging response, the volume content of different components, and the curve logging values, respectively; V is the volume content matrix.
[0101] For example, for a reservoir type of single mineral plus clay, the corresponding reservoir volume model is shown below:
[0102] V sh +V ma +φ=1
[0103] The response equation for the reservoir volume model is shown below:
[0104]
[0105] Where Δt, ρ, φ N Rt and Ct represent the sonic transit time logging curve, density logging curve, neutron logging curve, resistivity curve, and conductivity curve, respectively; V, sh, ma, φ, f, w, and oil represent the relative volume, clay content, rock skeleton, porosity, pore fluid, formation water, and oil, respectively; and R represents resistivity.
[0106] This invention eliminates the need for experimental data such as core analysis water saturation data, solving the problem that existing methods cannot evaluate reservoir water saturation in scenarios where core experimental data is missing or well logging series are incomplete. Based on well logging curves, sonic transit time curves, neutron and density curves, the water saturation of the reservoir can be calculated. Furthermore, the reservoir water saturation evaluation method based on the volume model provided by this invention is not only applicable to sandstone and mudstone reservoirs with high clay content and low mineralization, but also to low resistivity oil layers, making it widely applicable.
[0107] Example 2: As shown in the attached document Figure 4 As shown in the figure, this invention discloses a reservoir water saturation evaluation method based on a volumetric model, comprising:
[0108] Step S210: Determine the clay resistivity, formation water resistivity, reservoir clay content, and reservoir porosity.
[0109] Step S220: Substitute the clay resistivity, formation water resistivity, reservoir clay content, and reservoir porosity into the reservoir volume model response equation to obtain the relative volume of porosity occupied by formation water and the relative volume of porosity occupied by formation oil, and determine the water saturation of the reservoir. The reservoir volume model response equation is determined according to the reservoir type.
[0110] Step S230: Select fluid identification parameters using logging curves, reservoir porosity, reservoir water saturation, and oil testing data, and establish a fluid identification chart to realize reservoir fluid interpretation.
[0111] As attached Figure 5 As shown, step S230 specifically includes:
[0112] Step S231: Combining reservoir porosity and reservoir water saturation with well logging information (comprehensive calculation of multiple curves or calculation of a single curve), a series of parameter sets are obtained. These parameter sets include AC, Rt, So, Sw, Rwa, Rwa_sp, ΔGR, Φ, SSP, ΔSP, SP, and ASP. The calculation formulas for some parameters are shown below:
[0113] R wa =R t φ m
[0114]
[0115] Explanation: AC, Rt, So, Sw, Rwa, Rwa_sp, ΔGR, Φ, SSP, ΔSP, sp', and ASP represent the sonic transit time logging value, resistivity, oil saturation, water saturation, reconstructed apparent formation water resistivity, apparent formation water resistivity calculated from the spontaneous potential curve, relative spontaneous gamma value, porosity, static spontaneous potential, relative spontaneous potential, apparent spontaneous potential, and apparent spontaneous potential difference, respectively; mf represents mud filtrate; xo represents the flushing zone; and K value is obtained from the mud specific gravity.
[0116] Step S232 involves selecting fluid identification parameters from a set of parameters based on the oil test data, establishing a fluid identification chart, and realizing reservoir fluid interpretation. Here, based on the fluid identification chart, the lower saturation threshold is determined according to the oil test results of different blocks and layers, and it can effectively identify regional oil layers, oil-water co-containment layers, poor oil layers, and water layers.
[0117] Example 3: As shown in the attached document Figure 6 As shown in the figure, this invention discloses a reservoir water saturation evaluation method based on a volumetric model, comprising:
[0118] The basic analysis unit determines the resistivity of clay, the resistivity of formation water, the clay content of the reservoir, and the porosity of the reservoir.
[0119] The water saturation determination unit inputs the clay resistivity, formation water resistivity, reservoir clay content, and reservoir porosity into the reservoir volume model response equation to obtain the relative volume of porosity occupied by formation water and the relative volume of porosity occupied by formation oil, thereby determining the water saturation of the reservoir. The reservoir volume model response equation is determined according to the reservoir type.
[0120] The basic analysis unit includes:
[0121] The first analysis module analyzes the logging curves to obtain the resistivity of clay and formation water.
[0122] The second analysis module uses neutron and density curves to calculate the reservoir clay content using the following formula:
[0123]
[0124] Among them, V SH The content of clay; φ N φ D Neutron porosity and density porosity of the target layer; φ Nsh φ Dsh These represent the neutron porosity and density porosity of clay, respectively; ρb, ρma, ρsh, ρ f φ represents the density of the strata, rock skeleton, mudstone, and pore fluids. Nma Neutron porosity of the rock framework; φ Nfneutron porosity of porous fluid; v Nma φ Nsh φ Nf These are the hydrogen content indices for the rock strata framework, mudstone, and fluids, respectively.
[0125] The third analysis module, which determines reservoir porosity, includes:
[0126] Reservoir porosity is calculated using sonic transit time logging curves, and the porosity calculation is combined with the Wyllie time-averaged equation based on lithology or clay content.
[0127] Reservoir porosity is calculated using neutron and density curves, regardless of whether the response is positive or negative.
[0128] Verify reservoir porosity;
[0129] The verification module verifies reservoir porosity, including:
[0130] A porosity calculation model was established by combining core analysis data, and the reservoir porosity was obtained using the porosity calculation model. The porosity calculation model was established by obtaining density data and void analysis data from core analysis data and then using multiple linear regression.
[0131] Determine whether the reservoir porosity calculated using curves is consistent with the reservoir porosity obtained using a porosity calculation model;
[0132] If the response is no, the process of calculating reservoir porosity using curves is adjusted; if the response is yes, different porosity ranges are divided according to reservoir porosity, and reservoir types are classified according to the porosity ranges.
[0133] Example 4: As shown in the appendix Figure 7 As shown in the figure, this invention discloses a reservoir water saturation evaluation method based on a volumetric model, comprising:
[0134] The basic analysis unit determines the resistivity of clay, the resistivity of formation water, the clay content of the reservoir, and the porosity of the reservoir.
[0135] The water saturation determination unit inputs the clay resistivity, formation water resistivity, reservoir clay content, and reservoir porosity into the reservoir volume model response equation to obtain the relative volume of porosity occupied by formation water and the relative volume of porosity occupied by formation oil, thereby determining the water saturation of the reservoir. The reservoir volume model response equation is determined according to the reservoir type.
[0136] The chart analysis unit uses well logging curves, reservoir porosity, reservoir water saturation, and oil testing data to select fluid identification parameters, establish a fluid identification chart, and realize reservoir fluid interpretation.
[0137] Example 5: This embodiment of the invention discloses a storage medium storing a computer program that can be read by a computer. The computer program is configured to execute a reservoir water saturation evaluation method based on a volume model when it runs.
[0138] The aforementioned storage media may include, but are not limited to, USB flash drives, read-only memory, portable hard drives, magnetic disks, optical disks, and other media capable of storing computer programs.
[0139] Example 6: This embodiment of the invention discloses an electronic device, including a processor and a memory. The memory stores a computer program, which is loaded and executed by the processor to implement a reservoir water saturation evaluation method based on a volume model.
[0140] The processor described above can be a central processing unit (CPU), a general-purpose processor, a digital signal processor (DSP), an ASIC, an FPGA, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. It can also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc. The memory can include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory, portable hard drives, magnetic disks, or optical disks.
[0141] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.
[0142] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0143] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0144] The above technical features constitute the preferred embodiment of the present invention, which has strong adaptability and optimal implementation effect. Unnecessary technical features can be added or removed according to actual needs to meet the requirements of different situations.
Claims
1. A method for evaluating reservoir water saturation based on a volumetric model, characterized in that, include: Determine the resistivity of clay, the resistivity of formation water, the clay content of the reservoir, and the porosity of the reservoir; By substituting the resistivity of clay, the resistivity of formation water, the clay content of the reservoir, and the porosity of the reservoir into the response equation of the reservoir volume model, the relative volume of porosity occupied by formation water and the relative volume of porosity occupied by formation oil are obtained, and the water saturation of the reservoir is determined. The response equation of the reservoir volume model is determined according to the reservoir type.
2. The reservoir water saturation evaluation method based on a volumetric model according to claim 1, characterized in that, The process of determining reservoir porosity includes: Reservoir porosity is calculated using sonic transit time logging curves, and the porosity calculation is combined with the Wyllie time-averaged equation based on lithology or clay content. Reservoir porosity is calculated using neutron and density curves, regardless of whether the response is positive or negative. The reservoir porosity was verified.
3. The reservoir water saturation evaluation method based on a volumetric model according to claim 2, characterized in that, The verification of reservoir porosity includes: A porosity calculation model was established by combining core analysis data, and the reservoir porosity was obtained using the porosity calculation model. The porosity calculation model was established by obtaining density data and void analysis data from core analysis data and then using multiple linear regression. Determine whether the reservoir porosity calculated using curves is consistent with the reservoir porosity obtained using a porosity calculation model; If the response is no, the process of calculating reservoir porosity using curves is adjusted; if the response is yes, different porosity ranges are divided according to reservoir porosity, and reservoir types are classified according to the porosity ranges.
4. The reservoir water saturation evaluation method based on a volumetric model according to claim 1, 2, or 3, characterized in that, The reservoir clay content is calculated using the following formula based on neutron density curves: Among them, V SH The content of clay; φ N φ D Neutron porosity and density porosity of the target layer; φ Nsh φ Dsh These represent the neutron porosity and density porosity of clay, respectively; ρb, ρma, ρsh, ρ f φ represents the density of the strata, rock skeleton, mudstone, and pore fluids. Nma Neutron porosity of the rock framework; φ Nf φ represents the neutron porosity of the porous fluid. Nma φ Nsh φ Nf These are the hydrogen content indices for the rock strata, mudstone, and fluids, respectively.
5. The reservoir water saturation evaluation method based on a volumetric model according to claim 1, 2, or 3, characterized in that, The resistivity of the clay and the resistivity of the formation water were obtained by analyzing the well logging curves.
6. The reservoir water saturation evaluation method based on a volumetric model according to any one of claims 1 to 4, characterized in that, It also includes using well logging curves, reservoir porosity, reservoir water saturation, and oil testing data to select fluid identification parameters, establish fluid identification charts, and realize reservoir fluid interpretation.
7. A reservoir water saturation evaluation method based on a volumetric model, applying the method described in any one of claims 1 to 6, characterized in that, include: The basic analysis unit determines the resistivity of clay, the resistivity of formation water, the clay content of the reservoir, and the porosity of the reservoir. The water saturation determination unit inputs the clay resistivity, formation water resistivity, reservoir clay content, and reservoir porosity into the reservoir volume model response equation to obtain the relative volume of porosity occupied by formation water and the relative volume of porosity occupied by formation oil, thereby determining the water saturation of the reservoir. The reservoir volume model response equation is determined according to the reservoir type.
8. The reservoir water saturation evaluation device based on a volumetric model according to claim 7, characterized in that, The basic analysis unit includes: The first analysis module analyzes the logging curves to obtain the resistivity of clay and formation water. The second analysis module uses neutron and density curves to calculate the reservoir clay content using the following formula: Among them, V SH The content of clay; φ N φ D Neutron porosity and density porosity of the target layer; φ Nsh φ Dsh These represent the neutron porosity and density porosity of clay, respectively; ρb, ρma, ρsh, ρ f φ represents the density of the strata, rock skeleton, mudstone, and pore fluids. Nma Neutron porosity of the rock framework; φ Nf φ represents the neutron porosity of the porous fluid. Nma φ Nsh φ Nf These are the hydrogen content indices for the rock strata framework, mudstone, and fluids, respectively. The third analysis module, which determines reservoir porosity, includes: Reservoir porosity is calculated using sonic transit time logging curves, and the porosity calculation is combined with the Wyllie time-averaged equation based on lithology or clay content. Reservoir porosity is calculated using neutron and density curves, regardless of whether the response is positive or negative. Verify reservoir porosity; The verification module verifies reservoir porosity, including: A porosity calculation model was established by combining core analysis data, and the reservoir porosity was obtained using the porosity calculation model. The porosity calculation model was established by obtaining density data and void analysis data from core analysis data and then using multiple linear regression. Determine whether the reservoir porosity calculated using curves is consistent with the reservoir porosity obtained using a porosity calculation model; If the response is no, then the process of calculating reservoir porosity using curves is adjusted; if the response is yes, then different porosity ranges are divided according to reservoir porosity, and reservoir types are divided according to the porosity range. or / and, It also includes a chart analysis unit, which uses logging curves, reservoir porosity, reservoir water saturation, and oil testing data to select fluid identification parameters, establish a fluid identification chart, and realize reservoir fluid interpretation.
9. A storage medium, characterized in that, The storage medium stores a computer program that can be read by a computer, and the computer program is configured to execute the reservoir water saturation evaluation method based on the volume model as described in any one of claims 1 to 5 when it is run.
10. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program, which is loaded and executed by the processor to implement the reservoir water saturation evaluation method based on a volume model as described in any one of claims 1 to 5.