A water drive natural potential response master factor quantitative evaluation method based on unit potential gradient and elastic coefficient

Abstract

The application discloses a water drive natural potential response master control factor quantitative evaluation method based on unit potential gradient and elastic coefficient, and belongs to the technical field of oil and gas field development dynamic monitoring and porous medium seepage electric response. The method collects water drive potential response signals and electrode effective spacing under different parameter levels; relies on a water drive pre-stage steady potential correction signal, extracts a potential maximum change amplitude, and obtains a unit potential gradient through spatial normalization. A logarithmic fitting relationship between influencing factors and the unit potential gradient is established, the absolute value of the fitting slope is set as the master control elastic coefficient, and the control strength of each factor on the potential response is quantified and sorted. The application can quantitatively evaluate the influence degree of reservoirs, fluids and injection parameters, and provides a basis for water drive potential monitoring and key influencing factor identification.

Description

Technical Field

[0001] This invention belongs to the field of dynamic monitoring of oil and gas field development and the field of seepage electric response technology of porous media, specifically involving a quantitative evaluation method for the main controlling factors of water drive spontaneous potential response based on unit potential gradient and elastic coefficient. Background Technology

[0002] Water drive is a widely used method for enhancing oil recovery during oilfield development. By injecting water into the reservoir, formation pressure can be maintained or restored, and crude oil can be displaced and migrated to production wells. However, in actual water drive development, due to reservoir heterogeneity, differences in oil and water fluid properties, and variations in injection parameters, the injected water may advance rapidly along high-permeability channels or dominant flow paths, leading to uneven water drive coverage, premature water breakthrough in production wells, and complex distribution of remaining oil. Therefore, identifying the dynamic changes in water drive and the main control factors affecting water drive monitoring response is of great significance for optimizing water injection regimes, adjusting water drive development, and determining water production channels.

[0003] Spontaneous potential (SPT) signals are the result of the combined effects of fluid flow, ion migration, and electrochemical processes at the solid-liquid interface in porous media. When fluid flows in a porous medium with surface charges, charge separation and corresponding potential changes occur. Therefore, during water drive, the advancement of the injected water front, changes in fluid properties, and changes in the seepage state of the porous medium can all induce spontaneous potential responses. Spontaneous potential monitoring has potential applications in water-driven state identification and active water discovery.

[0004] However, the spontaneous potential response during waterflooding is simultaneously influenced by a variety of reservoir parameters, fluid parameters, and injection parameters. For example, salinity can affect the conductivity of pore fluids and the charge state at the solid-liquid interface; fluid viscosity can change the oil-water mobility ratio, the stability of the waterflood front, and the pressure gradient; permeability can affect the conductivity of porous media and the fluid propulsion state; and injection flow rate can change the fluid velocity and pressure gradient.

[0005] Since the above-mentioned different influencing factors have different physical meanings, units of measurement, and parameter value ranges, if the original natural potential, the maximum potential change amplitude, or the response range under different parameter levels is directly used to compare the degree of influence of different factors, it is easily affected by the absolute change range of the factors and the difference in parameter scale, and it is difficult to accurately reflect the degree of control of the natural potential response when different factors undergo relative changes.

[0006] Furthermore, differences in initial electrode contact potential, experimental system baseline, and instrument zero point may exist between different experiments, making it difficult to directly compare the original spontaneous potential dynamic response signals. The amplitude of the spontaneous potential response may also be affected by the electrode placement and the distance between electrodes. Under different model sizes or measurement scales, directly using the amplitude of spontaneous potential changes for evaluation may lead to inconsistencies in the evaluation scale.

[0007] Existing studies on water drive spontaneous potential mainly focus on qualitative analysis of spontaneous potential variation patterns, water drive front response characteristics, and the mechanisms of action of different influencing factors. There is a lack of a method that can uniformly and quantitatively evaluate the influencing factors of water drive with different physical categories, different dimensions, and different parameter value ranges, and further determine the degree of control of each influencing factor on the water drive spontaneous potential response and the ranking of the main controlling factors.

[0008] Therefore, it is necessary to provide a quantitative evaluation method for the main controlling factors of water-drive spontaneous potential response that can comprehensively consider the differences in the initial baseline of spontaneous potential, the effective distance between electrodes, and the differences in the dimensions and parameter scales of different influencing factors, so as to achieve a unified quantitative comparison of the degree of control among different reservoir parameters, fluid parameters, and injection parameters. Summary of the Invention

[0009] The purpose of this invention is to overcome the problems in the prior art, such as inconsistent initial baselines of spontaneous potential under different experimental conditions, the influence of effective distance between electrodes and measurement scale on potential response, and the difficulty in making unified comparisons of different reservoir parameters, fluid parameters and injection parameters due to differences in dimensions and value ranges. This invention provides a quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient.

[0010] This invention performs baseline correction and extracts the maximum absolute potential change amplitude from the dynamic response signal of water-drive spontaneous potential. It constructs a unit potential gradient based on the effective distance between electrodes and establishes a logarithmic relationship between the water-drive influencing factors to be evaluated and the unit potential gradient. The absolute value of the slope of the logarithmic relationship is used as the master control elastic coefficient, thereby achieving a unified quantitative evaluation and ranking of the degree of control of water-drive influencing factors with different dimensions and different parameter value ranges on spontaneous potential response.

[0011] To achieve the above objectives, the present invention adopts the following technical solution.

[0012] A quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient includes the following steps.

[0013] S1. Acquire dynamic response data of water-driven spontaneous potential. Obtain dynamic response signals of water drive spontaneous potential corresponding to at least two water drive influencing factors to be evaluated at multiple parameter levels, and the effective distance between electrodes of spontaneous potential measurement channels corresponding to each dynamic response signal of water drive spontaneous potential. The data sets corresponding to each water drive influencing factor to be evaluated were obtained under single-factor control conditions. That is, when evaluating any water drive influencing factor to be evaluated, only the parameter level of the current water drive influencing factor to be evaluated was changed, while the other experimental conditions remained the same. Let the first The water drive influencing factors to be evaluated are: , its first The parameter levels are The dynamic response signal of the water-drive spontaneous potential obtained at this parameter level is expressed as: ; In the formula, Indicates time; The water drive influencing factors to be evaluated may include at least two of the following: salinity, fluid viscosity, permeability, porosity, injection flow rate, injection pressure, temperature, and fluid saturation. Preferably, the water drive influencing factors to be evaluated include multiple influencing factors belonging to at least two categories: fluid property parameters, reservoir medium parameters, and injection condition parameters. Specifically, the fluid property parameters include at least one of salinity and fluid viscosity; the reservoir medium parameters include at least one of permeability and porosity; and the injection condition parameters include at least one of injection flow rate and injection pressure. In a preferred embodiment, the dynamic response signal of the water-driven spontaneous potential is obtained through a porous medium water-driven physical experiment; Specifically, a porous media water drive physical model is constructed, and at least two electrodes are set at different positions in the porous media water drive physical model to form at least one spontaneous potential measurement channel. Multiple parameter levels are set for each water drive influencing factor to be evaluated, and water drive experiments are carried out under single-factor control conditions. The dynamic response signal of the spontaneous potential of water drive corresponding to each parameter level is continuously collected. The porous media water drive physical model can be a one-dimensional sand-filled pipe model, a core displacement model, a two-dimensional flat plate sand-filled model, or other physical models that can simulate the porous media water drive process.

[0014] S2. Baseline correction of the dynamic response signal of water-driven spontaneous potential. For the dynamic response signal of the water drive natural potential corresponding to each parameter level, the baseline potential is determined based on the natural potential sampling value during the stable phase before the start of water drive. For the The first of the water drive influencing factors to be evaluated Each parameter level is selected within a time interval where the natural potential is stable before the water drive begins. The stable time interval includes For each natural potential sampled value, the baseline potential is calculated according to the following formula: ; In the formula: For the first The water drive influencing factors to be evaluated are in the first The baseline potential corresponding to each parameter level; The first time interval within the stable time interval One natural potential sample value; The number of natural potential sampling points within the stable time interval; Based on the baseline potential, the baseline-corrected natural potential change signal is obtained according to the following formula: ; In the formula, For the first The water drive influencing factors to be evaluated are in the first The baseline-corrected natural potential change signal corresponding to each parameter level; Baseline correction reduces the impact of differences in initial electrode contact potential, instrument zero point, and initial experimental conditions on direct comparisons of different experimental data.

[0015] S3. Extract the maximum absolute potential change amplitude and calculate the unit potential gradient. Extract the maximum absolute potential change amplitude from the baseline-corrected natural potential change signal: ; In the formula, For the first The water drive influencing factors to be evaluated are in the first The maximum absolute potential change amplitude corresponding to each parameter level; The maximum absolute potential change amplitude is used to characterize the spontaneous potential response intensity generated by the water drive process under the corresponding experimental conditions; Let the effective distance between the electrodes of the corresponding natural potential measurement channel be... Based on the maximum absolute potential change amplitude Effective distance between electrodes The unit potential gradient is calculated using the following formula: ; In the formula: For the first The water drive influencing factors to be evaluated are in the first The unit potential gradient corresponding to each parameter level; This corresponds to the maximum absolute potential change amplitude; This refers to the effective distance between electrodes in the corresponding natural potential measurement channel; The effective distance between the electrodes is the effective measurement distance between the measuring electrode and the reference electrode that constitute the natural potential measurement channel in the main water drive direction. By constructing a unit potential gradient based on the maximum absolute potential change amplitude and the effective distance between electrodes, the natural potential response has a unified characterization form under a unit spatial scale, thereby reducing the influence of different effective distances between electrodes or different measurement scales on the direct comparison of the natural potential response amplitude.

[0016] S4. Establish the logarithmic relationship and calculate the main control elasticity coefficient. Regarding the first Individual factors affecting water drive to be evaluated To obtain its multiple parameter levels: ; And the unit potential gradient corresponding to each parameter level: ; Perform natural logarithmic transformations on the parameter values ​​of the water drive influencing factors to be evaluated and the unit potential gradient respectively: ; ; Establish the following logarithmic relationship: ; In the formula: For the first The fitting slopes of the water drive influencing factors to be evaluated; The intercept is the fitting angle. Determined using linear fitting method and Furthermore, the goodness of fit of the logarithmic relationship to the corresponding experimental data can be evaluated using the goodness of fit. Based on the fitted slope The first one is determined according to the following formula. The main control elasticity coefficients corresponding to the water drive influencing factors to be evaluated: ; In the formula, For the first The main control elastic coefficients corresponding to the water drive influencing factors to be evaluated; The master control elasticity coefficient is used to characterize the first... The degree of relative change in the unit potential gradient when the relative changes of the water drive influencing factors to be evaluated occur; Main control elasticity coefficient The larger the value, the stronger the control effect of the corresponding water drive influencing factor on the water drive spontaneous potential response. Fitting slope The sign of the can also be used to characterize the overall direction of change between the corresponding water-drive influencing factor being evaluated and the unit potential gradient. Among them, This indicates that the overall unit potential gradient increases with the increase of the corresponding water drive influencing factor being evaluated. This indicates that the overall unit potential gradient decreases as the corresponding water drive influencing factor being evaluated increases.

[0017] S5. Determine the ranking of key control factors. Obtain the main control elasticity coefficients for each water drive influencing factor to be evaluated: ; Sort them in descending order of their respective control elasticity coefficients.

[0018] Among them, the water drive influencing factor with the largest main control elasticity coefficient is determined as the first main control factor, the water drive influencing factor with the second largest main control elasticity coefficient is determined as the second main control factor, and the remaining water drive influencing factors are ranked according to their control degree based on their main control elasticity coefficients.

[0019] The above methods enable a unified quantitative evaluation of the degree of control of water drive influencing factors on spontaneous potential response, based on different physical categories, different units of measurement, and different parameter value ranges.

[0020] Furthermore, based on the ranking results of the main control factors, the reservoir parameters, fluid parameters, or injection parameters that need to be prioritized or considered during the spontaneous potential water drive monitoring process can be determined. When interpreting the spontaneous potential monitoring results of water drive, the influence of the water drive influencing factors with larger main control elasticity coefficients on the spontaneous potential response can be analyzed first.

[0021] Compared with the prior art, the present invention has at least the following beneficial effects; 1. Establish evaluation indicators for natural potential response per unit spatial scale This invention constructs a unit potential gradient by using the ratio of the maximum absolute potential change amplitude to the effective distance between electrodes, so that the natural potential response has a uniform characterization form under a unit spatial scale, thereby reducing the influence of different effective distances between electrodes or different measurement scales on the direct comparison of the natural potential response amplitude. 2. Achieve unified evaluation among factors with different dimensions and parameter ranges. This invention establishes a logarithmic relationship between the water drive influencing factors to be evaluated and the unit potential gradient, and uses the absolute value of the fitting slope as the main control elastic coefficient, which can reduce the impact of differences in the physical units, absolute values ​​and parameter value ranges of different water drive influencing factors on the comparison of control degree. 3. Able to quantitatively determine the degree of control and the order of primary control factors for different factors. By calculating the principal control elastic coefficients for multiple water drive influencing factors to be evaluated and sorting them according to the magnitude of the principal control elastic coefficients, the relative degree of control of different reservoir parameters, fluid parameters and injection parameters on the water drive spontaneous potential response can be intuitively determined. 4. It can provide a basis for identifying monitoring parameters of spontaneous potential water drive. Based on the ranking of the main control factors, the reservoir parameters, fluid parameters, or injection parameters that need to be focused on during spontaneous potential water drive monitoring can be identified, providing a basis for interpreting spontaneous potential response during water drive, monitoring the water drive front, and actively seeking water. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments are briefly described below; it should be understood that the following drawings are only used to illustrate the technical solutions of the present invention and do not constitute a limitation on the scope of protection of the present invention; Figure 1 This is a flowchart of the quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response described in this invention; Figure 2 This is a schematic diagram of the porous media water-driven spontaneous potential monitoring experimental device described in this invention; Figure 3 This is a schematic diagram illustrating the baseline correction of the natural potential signal and the extraction of the maximum absolute potential change amplitude described in this invention. Figure 4 This is a bar chart showing the fitting results of the main control elastic coefficients for different water drive influencing factors in one embodiment of the present invention. Detailed Implementation

[0023] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments. It should be understood that the following embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the present invention. Equivalent substitutions or conventional adjustments made to the technical solution of the present invention without departing from the inventive concept should all fall within the scope of the inventive concept.

[0024] Example 1: Quantitative Evaluation Method for Main Controlling Factors of Water Drive Spontaneous Potential Response like Figure 1 As shown in the figure, this embodiment provides a quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient, including the following steps.

[0025] S1. Acquire dynamic response data of water-driven spontaneous potential. Obtain dynamic response signals of the water drive spontaneous potential corresponding to at least two water drive influencing factors to be evaluated at multiple parameter levels, as well as the effective distance between electrodes of the corresponding spontaneous potential measurement channel; The data sets corresponding to each water drive influencing factor to be evaluated were obtained under single-factor control conditions; For the Individual factors affecting water drive to be evaluated Set multiple parameter levels: ; Obtain the dynamic response signal of the water drive spontaneous potential corresponding to each parameter level: ; When evaluating any water drive influencing factor, only the parameter level of the current factor is changed, while the other experimental conditions remain the same.

[0026] In one specific implementation, such as Figure 2 As shown, a one-dimensional sand-filled pipe is used as the physical model for porous media water drive. One end of the sand-filled pipe is set as the injection end, and the other end is set as the production end. The first electrode E1 and the second electrode E2 are set at different positions along the main water drive direction to form the E1-E2 natural potential measurement channel.

[0027] The natural potential difference between E1 and E2 during the water drive process is continuously recorded using a natural potential data acquisition device.

[0028] S2. Perform baseline correction For the The water drive influencing factors to be evaluated are in the first Dynamic response signal of natural potential obtained at each parameter level Before water drive begins, select a time interval in which the natural potential is in a stable state.

[0029] Suppose that the time interval has If there are 1 natural potential sample value, then the baseline potential is: ; Baseline correction was performed on the original water-drive spontaneous potential dynamic response signal: ; The baseline-corrected natural potential change signal is obtained.

[0030] like Figure 3 As shown, the baseline-corrected natural potential change signal uses the average potential of the stable phase before displacement as the zero reference to characterize the relative natural potential change caused by the water drive process.

[0031] S3. Extract the maximum absolute potential change amplitude and calculate the unit potential gradient. Extract the maximum absolute potential change amplitude from the baseline-corrected natural potential change signal: ; The maximum absolute potential change amplitude is used to characterize the intensity of the spontaneous potential response generated by the water-drive process under the corresponding experimental conditions.

[0032] The effective distance between electrodes corresponding to the natural potential measurement channel is Then the unit potential gradient is: ; Through the above processing, the natural potential response is converted into a response index per unit spatial scale.

[0033] S4. Establish the logarithmic relationship and calculate the main control elasticity coefficient. Regarding the first One water drive influencing factor to be evaluated, and the levels of its parameters were obtained. and the corresponding unit potential gradient Perform natural logarithmic transformations on each, and establish: ; The slope of the fit is determined using a linear fitting method. and fitting intercept .

[0034] The main control elasticity coefficient is further calculated using the following formula: ; Main control elasticity coefficient The larger the value, the more significant the relative change in the unit potential gradient caused by the relative change of the water drive influencing factors to be evaluated, and the stronger the control effect on the water drive spontaneous potential response.

[0035] S5. Determine the ranking of key control factors. Calculate the main control elasticity coefficients for all water drive influencing factors to be evaluated: ; By sorting the main control elastic coefficients from largest to smallest, the relative degree of control of different water drive influencing factors on the water drive spontaneous potential response can be determined.

[0036] Based on the obtained ranking of the main controlling factors, the key influencing factors that need to be prioritized in the monitoring of spontaneous potential water drive can be further identified.

[0037] Example 2: Evaluation Experiment of Main Controlling Factors of Spontaneous Potential in One-Dimensional Sand-Filled Pipe Water Drive This embodiment uses a one-dimensional sand-filled pipe model to further illustrate the method of the present invention.

[0038] 1. Experimental setup like Figure 2 As shown, the experimental system includes an injection fluid container, a constant-speed injection pump, a porous media water-drive physical model, a first electrode E1, a second electrode E2, a natural potential data acquisition device, a pressure acquisition device, a product liquid collection container, and a data processing terminal.

[0039] The porous media water drive physical model uses a one-dimensional sand-filled tube, which is filled with experimental sand to form a porous media that simulates the reservoir.

[0040] One end of the sand-filled pipe is set as the injection end, and the other end is set as the output end.

[0041] The first electrode E1 and the second electrode E2 are set at different positions along the main water drive direction in the sand-filled pipe to form the E1-E2 natural potential measurement channel; during the experiment, the change in the natural potential difference between E1 and E2 is continuously collected by the natural potential data acquisition device.

[0042] 2. Factors affecting water drive to be evaluated This embodiment selects the following four types of water drive influencing factors to be evaluated: (1) Degree of mineralization; (2) Oil phase viscosity; (3) Penetration rate; (4) Injected flow.

[0043] Among them, salinity and oil phase viscosity are fluid property parameters, permeability is a reservoir medium parameter, and injection flow rate is an injection condition parameter.

[0044] This embodiment uses a total of 12 sets of valid experimental data for evaluation.

[0045] 3. Experiment on the influence of mineralization In the experiment on the effect of mineralization, the injection flow rate was fixed at 3 mL / min; The sand filling medium is 160-200 mesh quartz sand, and the oil phase viscosity is 10 cP. The salinity of the saturated water and the injected water was kept consistent, set at 3000 mg / L, 5000 mg / L, and 7000 mg / L, respectively. Water drive experiments were conducted at various mineralization parameter levels, and dynamic response signals of spontaneous potentials from E1 to E2 were continuously collected.

[0046] 4. Viscosity Effect Experiment In the viscosity effect experiment, the injection flow rate was fixed at 3 mL / min; The filling medium is 160-200 mesh quartz sand, and the salinity of both saturated water and injected water is 7000 mg / L. The oil phase viscosities were set to 10 cP, 150 cP, and 300 cP, respectively. Water drive experiments were conducted at various viscosity parameter levels, and dynamic response signals of spontaneous potentials E1–E2 were continuously collected.

[0047] 5. Effect of Permeability on Experiments In the permeability effect experiment, the injection flow rate was fixed at 3 mL / min; The salinity of both saturated water and injected water is 7000 mg / L; The oil phase viscosity is 10 cP. Three different measured permeability levels were formed by using sand filling media with different particle sizes, and water drive experiments were carried out respectively, continuously collecting the dynamic response signals of spontaneous potential E1-E2.

[0048] 6. Experiment on the effect of injection flow rate In the experiment on the effect of injection flow rate, the filling medium was 160-200 mesh quartz sand, and the salinity of both saturated water and injection water was 7000 mg / L. The oil phase viscosity is 10 cP. The injection flow rates were set to 0.5, 1, and 3 mL / min, respectively. Water drive experiments were conducted at various injection flow rate parameter levels, and dynamic response signals of spontaneous potentials E1–E2 were continuously collected.

[0049] 7. Baseline correction of natural potential signal For each set of experiments, the corresponding dynamic response signal of the natural potential E1–E2 was obtained: ; Before starting water drive, select a period of stable natural potential and calculate the baseline potential: ; Obtain the baseline-corrected natural potential change signal: ; like Figure 3 As shown, the maximum absolute potential change amplitude is further extracted from the baseline-corrected natural potential change signal: .

[0050] 8. Calculation of unit potential gradient Let the effective distance between the first electrode E1 and the second electrode E2 be... Then the unit potential gradient is: ; in: The potential gradient is a unit gradient. This represents the maximum absolute potential change amplitude. This represents the effective distance between E1 and E2. The unit potential gradients corresponding to each parameter level of salinity, oil phase viscosity, permeability, and injection flow rate were obtained respectively.

[0051] 9. Calculation of the main control elasticity coefficient For each type of water drive influencing factor to be evaluated ,Establish: ; The slope of the fit is obtained by using a linear fitting method. And calculate: ; The controlling elastic coefficients corresponding to salinity, oil phase viscosity, permeability, and injection flow rate were obtained respectively.

[0052] 10. Evaluation Results The master control elasticity coefficients obtained in this embodiment are shown in the table below.

[0053] ; like Figure 4 As shown, based on the fitting results, the master elastic coefficients are sorted from largest to smallest, resulting in: viscosity > mineralization > permeability > injection flow rate; The results indicate that, under the porous media conditions, fluid system, and parameter ranges used in this embodiment, oil phase viscosity has the strongest control effect on the water-driven spontaneous potential response, followed by mineralization and permeability, while the relative control effect corresponding to the injection flow rate is relatively weak.

[0054] Changes in oil phase viscosity can alter the oil-water mobility ratio, the propulsion stability of the water drive front, and the pressure state during the displacement process. Therefore, under the conditions of this embodiment, it exhibits a large master control elastic coefficient. Changes in mineralization can affect the electrical conductivity of pore fluids and the electrokinetic interaction at the solid-liquid interface, thus having a significant impact on the spontaneous potential response. Changes in permeability can alter the pore structure, conductivity, and propulsion state of porous media at the water drive front, thus having a certain controlling effect on the spontaneous potential response; The injection flow rate can change the fluid velocity and pressure gradient, but within the injection flow rate range used in this embodiment, its corresponding master control elasticity coefficient is smaller than the other three water drive influencing factors to be evaluated.

[0055] It should be noted that the above ranking of the main controlling factors corresponds to the porous media conditions, fluid system, and parameter value range given in this embodiment. Under other reservoir conditions, fluid systems, or parameter ranges, the main controlling elastic coefficients corresponding to each water drive influencing factor to be evaluated can be recalculated according to the method described in this invention, and the corresponding ranking of the main controlling factors can be obtained.

Claims

1. A quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient, characterized in that, Includes the following steps: S1. Obtain dynamic response signals of water drive natural potential corresponding to at least two water drive influencing factors to be evaluated at multiple parameter levels, and the effective distance between electrodes of the natural potential measurement channel corresponding to each of the dynamic response signals of water drive natural potential, wherein the data set corresponding to each water drive influencing factor to be evaluated is obtained under single-factor control conditions. S2. For the dynamic response signal of the water drive spontaneous potential corresponding to each parameter level, determine the baseline potential based on the spontaneous potential sampling value during the stable phase before the start of water drive. The baseline-corrected natural potential change signal is obtained according to the following formula: ； In the formula, For the first The water drive influencing factors to be evaluated are in the first Dynamic response signal of water-driven spontaneous potential at various parameter levels. This is the corresponding baseline-corrected natural potential change signal; S3. Extract the maximum absolute potential change amplitude from the baseline-corrected natural potential change signal: ； And based on the maximum absolute potential change amplitude Effective distance between electrodes and the corresponding natural potential measurement channel The unit potential gradient is calculated using the following formula: ； S4, Regarding the first Factors affecting water drive to be evaluated Based on its multiple parameter levels and the corresponding unit potential gradient Establish the following logarithmic relationship: ； And determine the first according to the following formula The main control elasticity coefficients corresponding to the water drive influencing factors to be evaluated: ； In the formula, The slope of the fitted logarithmic relationship is given. For the fitting intercept, For the first The main control elastic coefficients corresponding to the water drive influencing factors to be evaluated; S5. Obtain the main control elastic coefficients corresponding to each water drive influencing factor to be evaluated, and determine the degree of control of each water drive influencing factor to be evaluated on the water drive spontaneous potential response and the ranking results of the main control factors according to the main control elastic coefficients from large to small.

2. The quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient as described in claim 1, characterized in that, In step S1, the dynamic response signal of the water-driven spontaneous potential is obtained in the following way: A porous media water drive physical model is constructed, and at least two electrodes are set at different positions of the porous media water drive physical model to form at least one natural potential measurement channel. Multiple parameter levels were set for each water drive influencing factor to be evaluated, and water drive experiments were carried out under single-factor control conditions. The dynamic response signals of the water drive spontaneous potential at each parameter level were continuously collected.

3. The quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient as described in claim 2, characterized in that: The porous media water drive physical model is one of a one-dimensional sand-filled pipe model, a core displacement model, or a two-dimensional flat plate sand-filled model. The at least two electrodes include a measuring electrode and a reference electrode, and a natural potential measurement channel is formed between the measuring electrode and the reference electrode for continuously collecting the natural potential difference between the two electrodes during water drive.

4. The quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient as described in claim 1, characterized in that: The water drive influencing factors to be evaluated include at least two of the following: salinity, fluid viscosity, permeability, porosity, injection flow rate, injection pressure, temperature, and fluid saturation. For each water drive influencing factor to be evaluated, at least three different parameter levels should be set.

5. The quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient according to claim 1, characterized in that: In step S2, a time interval in which the natural potential is in a stable state is selected before the water drive begins. This time interval includes... Each natural potential is sampled, and the baseline potential is calculated according to the following formula: ； In the formula, For the first The water drive influencing factors to be evaluated are in the first The baseline potential corresponding to each parameter level The first time interval within the stable time interval One natural potential sample value, The number of natural potential sampling points within the stable time interval.

6. The quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient according to claim 3, characterized in that: The measuring electrode and the reference electrode are respectively disposed at different positions along the main water drive direction of the porous medium water drive physical model; The effective distance between the electrodes is the effective measurement distance between the measuring electrode and the reference electrode in the main water drive direction, and the maximum absolute potential change amplitude is spatially normalized based on the effective distance between the electrodes.

7. The quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient according to claim 1, characterized in that: In step S4, for the first The parameter levels of each factor affecting water drive to be evaluated and the corresponding unit potential gradient Perform natural logarithmic transformations on each side, and then use a linear fitting method to determine the fitting slope in the logarithmic relationship. and fitting intercept ; The goodness of fit of the logarithmic relationship is calculated to characterize how well the logarithmic relationship fits the corresponding experimental data.

8. The quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient according to claim 1, characterized in that: The main control elastic coefficient Used to characterize the The degree of relative change in the unit potential gradient when the relative changes of the water drive influencing factors to be evaluated occur; The fitting slope The absolute value is used to evaluate the control strength of the corresponding water drive influencing factor on the water drive spontaneous potential response, and the fitting slope The sign of is used to characterize the overall direction of change between the corresponding water drive influencing factor to be evaluated and the unit potential gradient.

9. The quantitative evaluation method for the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient according to any one of claims 1 to 8, characterized in that: The water drive influencing factors to be evaluated include multiple influencing factors belonging to at least two categories: fluid property parameters, reservoir medium parameters, and injection condition parameters. Wherein, the fluid property parameters include at least one of salinity and fluid viscosity, the reservoir medium parameters include at least one of permeability and porosity, and the injection condition parameters include at least one of injection flow rate and injection pressure; Calculate the main control elasticity coefficients for different categories of water drive influencing factors to be evaluated, and then perform a unified quantitative evaluation and ranking of different categories of water drive influencing factors to be evaluated according to the main control elasticity coefficients.

10. The method for quantitatively evaluating the main controlling factors of water-driven spontaneous potential response based on unit potential gradient and elastic coefficient according to any one of claims 1 to 9, characterized in that: Based on the ranking of the main control factors, the reservoir parameters, fluid parameters, or injection parameters that need to be prioritized or considered during the spontaneous potential water drive monitoring process are determined. When interpreting the spontaneous potential monitoring results of water drive, the influence of the water drive influencing factors with larger main control elasticity coefficients on the spontaneous potential response is analyzed first.

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