Method for predicting oil reservoir recovery factor based on spontaneous imbibition of surfactants

Abstract

The application provides a kind of oil reservoir recovery prediction method based on surfactant spontaneous imbibition, it is related to oilfield development recovery prediction technical field, the application is based on surfactant spontaneous imbibition oil displacement experiment, records the surfactant injection amount and crude oil production in unit imbibition time, combines oil reservoir reserves and exploitation time and delimits imbibition recovery curve, and establishes surfactant adsorption migration model, correlates oil reservoir parameter and surfactant concentration change, calculates the actual and ideal concentration difference of each subinterval, generates recovery coefficient, and corrects the recovery curve of each subinterval according to this, obtains the corrected oil pump output, accumulates the oil pump output of all subintervals, combines oil reservoir reserves to calculate the overall oil pump output and recovery rate.The application realizes the accurate prediction of oil reservoir surfactant spontaneous imbibition oil displacement process and the effective evaluation of recovery rate by establishing surfactant adsorption migration model and combining experimental data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oilfield development recovery prediction, in particular to an oil reservoir recovery prediction method based on spontaneous imbibition of surfactants. BACKGROUND

[0002] The oil reservoir recovery prediction method based on spontaneous imbibition of surfactants aims to improve the recovery of crude oil by reducing the oil-water interfacial tension and improving the oil-water flow characteristics of surfactants, promoting the spontaneous imbibition of water into the oil reservoir pores. This technology helps to expel the remaining crude oil by changing the capillary action and oil-water interaction in the reservoir. In order to optimize the application effect of this technology, researchers use various prediction methods such as establishing experimental data regression models, numerical simulation models and mechanism analysis models, combined with the characteristics of reservoir rocks and fluids, to predict the best surfactant injection strategy, so as to achieve higher oil reservoir recovery.

[0003] The existing recovery prediction methods rely on empirical formulas or single oil displacement mechanisms, which cannot accurately reflect the dynamic imbibition behavior of surfactants in complex reservoirs and their influence on oil reservoir displacement efficiency, especially under the interaction of reservoir wettability, porous medium characteristics and surfactant adsorption and migration. Traditional methods cannot accurately predict the amount of crude oil production and recovery. In addition, the recovery curves used in traditional oil reservoir recovery methods often ignore the influence of reservoir heterogeneity and dynamic changes in oil displacement, resulting in inaccurate values of oil pumpage, which in turn affects the oil reservoir recovery rate.

[0004] Therefore, it is necessary to provide an oil reservoir recovery prediction method based on spontaneous imbibition of surfactants to solve the above problems.

[0005] The above information disclosed in the background section is only used to strengthen the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0006] The present application aims to provide an oil reservoir recovery prediction method and system based on spontaneous imbibition of surfactants to solve the problems raised in the background.

[0007] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0008] An oil reservoir recovery prediction method based on spontaneous imbibition of surfactants, comprising the following specific steps:

[0009] Step 1: Obtain the geological parameters, wettability parameters, reservoir crude oil physical property parameters, and core samples of the oil reservoir to be predicted. Perform spontaneous imbibition oil displacement experiments with surfactants using the core samples. Record the surfactant dosage and crude oil production at a set unit imbibition recovery time under the same pressure. The geological parameters include core porosity and permeability. The wettability parameters include contact angle. The reservoir crude oil physical property parameters include crude oil density and crude oil viscosity.

[0010] Step 2: Determine the initial concentration of the surfactant. Draw the spontaneous imbibition recovery curve based on the oil reservoir geological reserves and the required crude oil production time. Divide the crude oil production time into integer unit imbibition recovery time subintervals to obtain the imbibition recovery curve for each subinterval.

[0011] Step 3: Establish a surfactant adsorption and migration model. Associate the obtained related parameters of the oil reservoir to be predicted with the indicators affecting the concentration of the surfactant. Analyze the differences between the concentration changes of the surfactant and the ideal surfactant in each subinterval and generate a recovery coefficient. Based on the recovery coefficient in each subinterval, modify the imbibition recovery curve corresponding to each subinterval to obtain the oil pumping volume in each interval.

[0012] Step 4: Calculate the total oil pumping volume under the oil reservoir geological reserves and the required crude oil production time based on the oil pumping volume in each interval. Determine the oil reservoir recovery rate of spontaneous imbibition of the surfactant based on the oil reservoir geological reserves.

[0013] Further, the method for dividing the spontaneous imbibition recovery curve is as follows:

[0014] The spontaneous imbibition recovery curve is divided based on the oil reservoir geological reserves and the required crude oil production time. The horizontal axis of the spontaneous imbibition recovery curve is time, and the vertical axis is the real-time crude oil production at the wellhead. The expression of the divided spontaneous imbibition recovery curve is:

[0015] wherein, represents the spontaneous imbibition recovery curve, represents the oil reservoir geological reserves, represents the required crude oil production time, represents the maximum crude oil production at the wellhead, represents the curve steepness coefficient, is the time variable, .

[0016] Further, the method for adjusting the crude oil production time is as follows:

[0017] When the crude oil mining time is an integer multiple of the unit imbibition recovery time, the mining time does not need to be adjusted, and the mining time is directly divided by averaging; when the crude oil mining time is not an integer multiple of the unit imbibition recovery time, the number of integer unit operation time periods is calculated and rounded up, and then the adjusted total time is calculated by the integer time period number and the unit imbibition recovery time period, and the formula is:

[0018]

[0019] wherein, represents rounding up, is the number of unit operation time periods after rounding up, represents the set unit imbibition recovery time, is the index of the divided sub-interval, and .

[0020] Further, a surfactant adsorption and migration model is established, and the method is as follows:

[0021] Based on the multi-modal feature correlation, the obtained geological parameters, wettability parameters, reservoir crude oil physical property parameters and indicators affecting the concentration of surfactant are correlated, the indicators affecting the concentration of surfactant include effective diffusion coefficient, average imbibition flow rate and adsorption coefficient, the geological parameters include porosity and permeability of the core, the wettability parameters include contact angle, and the reservoir crude oil physical property parameters include crude oil density and crude oil viscosity, and the formula for multi-modal feature correlation is as follows:

[0022]

[0023] wherein, , , indicates the indicators affecting the concentration of surfactant, which are effective diffusion coefficient, average imbibition flow rate and adsorption coefficient, is the permeability, is the crude oil viscosity, is the exponential influence function of porosity, is the porosity, is the contact angle, is the crude oil density, is the density of water, is the acceleration of gravity;

[0024] Based on the Advection-Dispersion-Adsorption model, the partial differential relationship of the concentration of surfactant under the influence of the indicators of effective diffusion coefficient, average imbibition flow rate and adsorption coefficient is established, and the formula is as follows:

[0025]

[0026] wherein, represents the partial differential equation of surfactant concentration based on the model, represents the instantaneous concentration of surfactant in the core pore, is the spatial coordinate, representing the position in the core, is the rock skeleton density.

[0027] Further, the variation of surfactant concentration in each sub-interval is analyzed, and the coefficient correction of the imbibition recovery curve corresponding to each sub-interval is carried out based on the recovery coefficient in each sub-interval, and the method is as follows:

[0028] According to the surfactant experiment from the beginning into the core to flow out, the initial condition of the experiment is set as the initial core without surfactant , the inlet boundary is the continuous input concentration of surfactant , and the outlet boundary condition is set as the remote concentration is limited, that is .

[0029] The partial differential equation of surfactant concentration is solved by using Laplace transform, and the function analytical expression of surfactant concentration changing with time under the joint action of diffusion, convection and adsorption is as follows:

[0030]

[0031] wherein, represents the function analytical expression of surfactant concentration, which is used to calculate the concentration of surfactant at time, represents the complementary error function;

[0032] Based on the function analytical expression of surfactant concentration, the variation of surfactant concentration in each sub-interval after division is analyzed, and the coefficient correction of the imbibition recovery curve in each sub-interval is carried out, and the formula is as follows:

[0033]

[0034] wherein, represents the variation of surfactant concentration in the th sub-interval, represents the oil production in the th sub-interval;

[0035] The ideal variation of surfactant concentration in each sub-interval is divided , the difference between the ideal concentration change of each sub-interval and the calculated concentration change is analyzed, the recovery coefficient is generated, and the oil production of each sub-interval is corrected according to the recovery coefficient of each sub-interval to obtain the oil pumping amount of each interval, and the formula is:

[0036]

[0037]

[0038] wherein, represents the recovery coefficient of the i-th sub-interval, represents the oil pumping amount of the i-th sub-interval.

[0039] Further, the oil reservoir recovery of the spontaneous imbibition of the surfactant is determined, and the method is:

[0040] The total oil pumping amount is calculated according to the total number of the divided sub-intervals and the oil pumping amount corresponding to each sub-interval, and the formula is:

[0041]

[0042]

[0043] wherein, represents the total oil pumping amount, is the predicted oil reservoir recovery.

[0044] Compared with the prior art, the beneficial effects of the present application are:

[0045] The present application aims at the problem that the spontaneous imbibition behavior of the surfactant in the reservoir and its influence on the oil displacement effect cannot be accurately reflected in the existing oil reservoir recovery prediction method, by introducing the mathematical description of the surfactant adsorption and migration process, combining the recovery curve obtained by the oil displacement experiment and the concentration correction technology, the shortcomings of the traditional model in considering the dynamic distribution and adsorption influence of the surfactant are solved, and the accuracy and reliability of the recovery prediction are improved.

[0046] In addition, the present application also effectively solves the complexity problem caused by the heterogeneity of the oil reservoir and the dynamic change of the oil displacement by the interval division and the segmented recovery coefficient calculation method, and realizes the fine prediction of the recovery rate of different reservoir intervals. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 It is the overall method flowchart of the present application. DETAILED DESCRIPTION

[0048] ​​For the purposes of making the objectives, technical solutions and advantages of the present application clearer, further detailed explanations of the present application are provided below in conjunction with specific embodiments.

[0049] It should be noted that, unless otherwise defined, technical terms or scientific terms used in the present application should be understood as their common meanings to those having ordinary skills in the art to which the present application pertains. The terms "first", "second", and similar terms used in the present application do not denote any order, quantity, or importance, but are only used to distinguish different components. The terms "comprise", "include" and similar terms mean that the elements or objects before the terms encompass the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connect" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "upper", "lower", "left", "right", and the like only represent relative positional relationships, and when the absolute positions of the described objects change, the relative positional relationships can also change accordingly.

[0050] Embodiment:

[0051] Please refer to Figure 1 A surfactant spontaneous imbibition-based oil reservoir recovery prediction method, and the specific steps include:

[0052] Step 1: Obtain the geological parameters, wettability parameters, reservoir crude oil physical property parameters, and core samples of the oil reservoir to be predicted, and perform surfactant spontaneous imbibition oil displacement experiments using the core samples. The amount of surfactant injected and the amount of crude oil produced are recorded within a set unit imbibition recovery time at the same pressure. The geological parameters include the porosity and permeability of the core, the wettability parameters include the contact angle, and the reservoir crude oil physical property parameters include the crude oil density and crude oil viscosity.

[0053] In the specific embodiments of the present application, representative core samples of the reservoir to be predicted are collected, which ensures that the samples can better reflect the geological characteristics of the reservoir. Detailed physical parameter measurements are performed on these core samples, including porosity and permeability tests, which are usually accurately measured by using a helium porosimeter and a permeability tester. At the same time, the wettability parameters of the core are measured, mainly by measuring the contact angle between the rock surface and the water-oil interface by using a contact angle measuring instrument to evaluate the wettability state of the reservoir. Secondly, reservoir crude oil samples are collected, and their physical parameters including the density and viscosity of the crude oil are measured by using a special densimeter and a rotational viscometer to ensure the accuracy and representativeness of the data. Subsequently, using the obtained core samples, a surfactant spontaneous imbibition oil displacement experimental device is built in the laboratory. During the experiment, the constant pressure condition similar to that of the reservoir is maintained, a surfactant solution of a predetermined concentration and dosage is injected, the actual oil displacement process is simulated, and the amount of surfactant injected and the corresponding crude oil production are monitored and recorded in real time within a set unit imbibition recovery time.

[0054] Step 2: Determine the initial concentration of the surfactant, and combine the geological reserves of the reservoir with the oil production time requirement to delineate the spontaneous imbibition recovery curve. Divide the oil production time into integer unit imbibition recovery time subintervals to obtain the imbibition recovery curve of each subinterval.

[0055] In the specific embodiments of the present application, first, the initial concentration of the surfactant is determined to ensure the accuracy of the concentration parameters of the oil displacement agent used in the experiment and prediction process, which lays the foundation for simulating the spontaneous imbibition behavior of the surfactant in the reservoir. And combining the geological reserves of the reservoir with the oil production time requirement, the overall oil displacement process is divided into several integer unit imbibition recovery time subintervals, which can refine the dynamic changes of the oil displacement process. This segmented processing method enables the model to capture the changing rules of the surfactant oil displacement performance at different time stages. By delineating the spontaneous imbibition recovery curve and subdividing the subintervals, the model can not only reflect the dynamic evolution of the recovery rate with time during the oil displacement process, but also adjust the oil displacement scheme for different time periods, optimize the injection strategy of the surfactant, and achieve more efficient reservoir development management.

[0056] Further, the spontaneous imbibition recovery curve is delineated, and the oil production time is divided into integer unit imbibition recovery time subintervals, and the method is as follows:

[0057] According to the geological reserves of the reservoir and the oil production time requirement, the spontaneous imbibition recovery curve is delineated, the horizontal coordinate of the spontaneous imbibition recovery curve is time, and the vertical coordinate is the real-time crude oil production at the wellhead. The expression of the delineated spontaneous imbibition recovery curve is:

[0058]

[0059] wherein, This represents the spontaneous infiltration harvesting curve. Indicates the geological reserves of the oil reservoir. Indicates the required duration of crude oil extraction. This indicates the maximum crude oil production at the wellhead. Indicates the curve steepness coefficient. For time variables, ;

[0060] In the above-described spontaneous seepage recovery curve, the logistic function is used. Because the logistic function has an "S"-shaped curve characteristic, it can well describe the dynamic changes in crude oil production during the oil displacement process: slow initial growth, rapid increase in the middle stage, and stabilization in the later stage. This basically matches the actual oil reservoir development and recovery process, avoiding the neglect of the phased effects of increasing and decreasing displacement agents by linear or simple exponential models. The reservoir geological reserves in the formula... and mining duration requirements Using these two parameters, the formula directly links the reservoir's resource situation with the production cycle, ensuring that the total recovery rate does not exceed the reservoir's maximum recoverable reserves. It also allows for adjustments to the pace and intensity of the seepage process based on the development plan, while setting the maximum crude oil production rate at the wellhead. This is a practical constraint in oilfield development. The formula uses the curve steepness coefficient to... Incorporating the harvest curve ensures that the curve does not exhibit unrealistic instantaneous high yields, reflecting the capacity limits of the actual production system;

[0061] In curve steepness coefficient In its design, this expression integrates core factors such as maximum production, geological reserves, and duration to determine the steepness of the curve's ascent and descent. This makes the recovery process more closely resemble the actual oilfield's production capacity utilization rate, avoiding unreasonable situations where the curve is too flat or too steep. This is achieved by adjusting the curve steepness coefficient. The control mechanism can flexibly adapt to the oil displacement process under different reservoir and wellhead conditions.

[0062] It should be noted that the reason for adjusting the crude oil extraction time is primarily to standardize the time scale and the unit percolation recovery time. The total production time is typically determined based on the optimal time scale established by reservoir characteristics, oil displacement mechanisms, and engineering practices. The division into integer multiples of the time helps to ensure that the length of each sub-interval is completely consistent, facilitates the analysis and control of the recovery process at a uniform pace, and the development of the reservoir simulation and real-time monitoring often uses discrete time step processing problems, if the length of the exploitation is not an integer multiple of the unit time, the length of the last time interval is inconsistent, which increases the calculation complexity and the difficulty of boundary condition processing, and even affects the numerical stability, through the upward rounding division method, the spontaneous imbibition recovery curve between each sub-interval is continuous, and the recovery amount mutation or discontinuity phenomenon caused by non-integer division is avoided.

[0063] Therefore, it is necessary to adjust the crude oil exploitation length, divide the crude oil exploitation length into integer sub-intervals of unit imbibition recovery time, and the method is as follows:

[0064] When the length of the crude oil exploitation is an integer multiple of the unit imbibition recovery time, the exploitation length does not need to be adjusted, and is directly divided in average; when the length of the crude oil exploitation is not an integer multiple of the unit imbibition recovery time, the number of integer unit operation time intervals is calculated and rounded up, and then the adjusted total time is calculated through the integer time interval number and the unit imbibition recovery time interval, and the formula is as follows:

[0065]

[0066] Among them, indicates rounding up, is the number of unit operation time intervals after rounding up, indicates the set unit imbibition recovery time, is the index of the sub-interval after division, and .

[0067] Step 3: Establishing a surfactant adsorption migration model, associating the obtained related parameters of the to-be-predicted reservoir with the indicators affecting the concentration of the surfactant, analyzing the difference between the concentration change of the surfactant and the concentration change of the ideal surfactant in each sub-interval and generating a recovery coefficient, and based on the recovery coefficient in each sub-interval, the imbibition recovery curve corresponding to each sub-interval is coefficient corrected to obtain the oil pumping amount of each interval.

[0068] In the specific embodiment of the present application, through the multi-modal feature correlation method, the reservoir geological parameters, wettability parameters and reservoir crude oil physical property parameters are combined with the key influence indicators of the surfactant concentration to construct a quantitative model with clear physical meaning and quantifiable parameters, the transport and dynamic change process of the surfactant in the pore space of the reservoir is accurately described by establishing a convection-diffusion-adsorption partial differential equation, and the change of the crude oil exploitation amount in different sub-intervals is indirectly reflected through the quantitative processing of different key influence indicators.

[0069] Further, a surfactant adsorption migration model is established, and the method is as follows:

[0070] Based on the multi-modal feature correlation, the obtained geological parameters, wettability parameters, reservoir crude oil physical parameters and indicators affecting the surfactant concentration are correlated, the indicators affecting the surfactant concentration include effective diffusion coefficient, average imbibition flow rate and adsorption coefficient, the geological parameters include core porosity and permeability, the wettability parameters include contact angle, and the reservoir crude oil physical parameters include crude oil density and crude oil viscosity, and the formula for the multi-modal feature correlation is as follows:

[0071]

[0072] wherein, 、 、 indicates the indicators affecting the surfactant concentration, and is respectively effective diffusion coefficient, average imbibition flow rate and adsorption coefficient, is permeability, is crude oil viscosity, is the exponential influence function of porosity, is porosity, is contact angle, is crude oil density, is water density, is gravitational acceleration;

[0073] In the above multi-modal feature correlation formula, the effective diffusion coefficient reflects the diffusion degree of the surfactant, the permeability is larger, is larger, which indicates that the pore structure of the oil layer is more unobstructed, and the diffusion ability of the surfactant is enhanced; and the porosity is adjusted by the exponential function, which embodies the nonlinear influence of the pore structure on diffusion, is larger, is larger, which indicates that the rock pore space is more and more connected, which is beneficial to the free diffusion of the surfactant molecules in the rock pore; is crude oil viscosity, is larger, is smaller, which conforms to the physical law that viscosity hinders diffusion in fluid dynamics, and the overall formula conforms to the basic principles of Darcy's law and diffusion mechanism;

[0074] The average imbibition flow rate Taking into account permeability, viscosity, porosity, contact angle, and gravity driving force generated by density difference, the flow velocity is proportional to permeability. The influence of viscosity and porosity reasonably reflects the coupling relationship between fluid flow resistance and reservoir porosity characteristics. The cosine function of contact angle reflects the regulating effect of wettability on oil displacement flow velocity. Density difference and gravitational acceleration reflect the natural driving force of infiltration and adsorption. The formula as a whole conforms to fluid mechanics and multiphase flow theory.

[0075] Adsorption coefficient By contact angle To reflect the influence of wettability on surfactant adsorption behavior, the larger the contact angle, the more hydrophobic the rock surface, and the more significant the change in surfactant adsorption characteristics. The tangent function form shows the nonlinear relationship between the adsorption coefficient and the wettability parameter, which is consistent with the experimental and theoretical analysis results.

[0076] The partial differential equation of surfactant concentration under the influence of effective diffusion coefficient, average percolation velocity, and adsorption coefficient is established based on the Advagesion-Dispersion-Adsorption model. The formula used is as follows:

[0077]

[0078] in, This represents the partial differential equation for surfactant concentration established based on the model. This indicates the instantaneous concentration of the surfactant in the core pores. These are spatial coordinates, representing the location within the rock core. Density of the rock skeleton;

[0079] In the partial differential equation for surfactant concentration established above, This part represents the diffusion term related to the concentration gradient and the effective diffusion coefficient. This value characterizes the diffusion ability of surfactants in the pores of the core. A higher value indicates a stronger diffusion ability of surfactant molecules through the pores. This contributes to a more uniform concentration distribution along the spatial direction, reducing the concentration gradient, i.e., the surfactant diffuses from high-concentration areas to low-concentration areas, while increasing... It will accelerate the diffusion rate of concentration, help the surfactant to be distributed more evenly in the pores, and promote the oil displacement effect; This part represents the convection term related to the average osmotic velocity and concentration gradient. The migration speed of surfactant in pore media is described, which embodies the convection process, the representation of surfactant transport in the core along the flow direction, the greater the flow rate, the faster the surfactant migration, this part plays a "transport" role in the surfactant concentration distribution, causes the concentration peak to move over time, affects the spatial distribution of diffusion and adsorption, and through flow rate adjustment, the transport efficiency of surfactant to the deep part of the reservoir can be controlled; This part is the adsorption coefficient related to the concentration gradient, which describes the concentration attenuation of surfactant due to adsorption on the rock surface, which is the "consumption" term of concentration, The greater the adsorption capacity, the stronger the adsorption capacity, the more the amount of surfactant adsorbed by the rock, the effective concentration in the pore is reduced, the adsorption effect will reduce the activity and effective concentration of surfactant in the mobile phase, and the actual utilization rate of the oil displacement agent is affected.

[0080] It should be noted that the reason for calculating the recovery coefficient of each sub-interval to correct the imbibition recovery curve of the corresponding sub-interval is that the concentration of surfactant directly affects its ability to reduce oil-water interfacial tension, change wettability, and improve oil-water mobility, thereby affecting oil displacement efficiency and recovery. In an ideal state, surfactant in a certain concentration interval should correspond to a certain recovery effect, but in actual reservoirs, due to complex factors such as geological heterogeneity, fluid interaction, adsorption loss, etc., there is a deviation between the actual concentration distribution and the ideal distribution.

[0081] Therefore, it is necessary to analyze the change amount of surfactant concentration in each sub-interval, and based on the recovery coefficient of each sub-interval, the imbibition recovery curve of each corresponding sub-interval is corrected. The method is as follows:

[0082] According to the surfactant experiment from entering the core to flowing out, the initial condition of the experiment is set as no surfactant in the core , the inlet boundary is the continuous input concentration of surfactant , and the outlet boundary condition is set as the remote concentration is limited, that is ;

[0083] The partial differential relationship of surfactant concentration is solved by using Laplace transform, and the function analytical expression of surfactant concentration changing with time under the joint action of diffusion, convection and adsorption is as follows:

[0084]

[0085] Among them, represents the function analytical expression of surfactant concentration, which is used to calculate the concentration of surfactant at time, represents the complementary error function;

[0086] In the above function analysis of surfactant concentration, This part is the standard one-dimensional convection-diffusion equation without adsorption, which is a classic analytical solution form, describing a surfactant concentration wave front moving in the positive direction, is the complementary error function, derived from the solution of the diffusion equation, reflecting the diffusion and smooth transition of concentration in space, This part represents the balance between the moving offset of convection and the spatial expansion of diffusion: when , the surfactant concentration begins to rise significantly, reflecting the position of the wave front; when , the surfactant concentration tends to zero, consistent with the far-end boundary condition; when , the surfactant concentration tends to the inlet concentration ; the exponential decay term mainly reflects the time decay effect of adsorption on concentration, with the increase of time , adsorption gradually consumes surfactant, leading to an exponential decrease in concentration in the pore water phase.

[0087] It should be noted that this expression is a known analytical solution of the classic convection-diffusion equation combined with a first-order decay source, which satisfies the partial differential equation and the given initial boundary conditions. Based on the Laplace transform method, for linear equations with constant coefficients, this type of analytical solution can be obtained, and the appearance of the complementary error function is a standard solution of the diffusion problem, which conforms to the mathematical characteristics of the diffusion process.

[0088] Based on the function analysis of surfactant concentration, the concentration change in each sub-interval is analyzed, and the coefficient of the imbibition recovery curve in each sub-interval is corrected. The formula is:

[0089]

[0090] where, represents the surfactant concentration change of the th sub-interval, represents the oil production of the th sub-interval;

[0091] The ideal surfactant concentration change of each sub-interval is determined , the difference between the ideal concentration change and the calculated concentration change in each sub-interval is analyzed, the recovery coefficient is generated, and the corresponding oil production is corrected according to the recovery coefficient of each sub-interval to obtain the oil pumping rate of each interval. The formula is:

[0092]

[0093] ​

[0094] wherein, represents the recovery coefficient of the th sub-interval, represents the oil pumping volume of the th sub-interval; in the above formula for calculating the recovery coefficient, the difference between the actual surfactant concentration variation amount and in a certain interval can be quantitatively described by the introduction of the recovery coefficient, so as to reflect the deviation degree of the oil displacement effect in the interval, the closer the recovery coefficient is to 1, the closer the actual oil displacement effect is to the ideal state; the farther the recovery coefficient deviates from 1, the more the actual recovery efficiency is reduced due to the influence of factors such as insufficient concentration, adsorption loss and seepage resistance.

[0095] Step 4: Calculate the total oil pumping volume under the requirement of the oil reservoir geological reserves and the crude oil mining time length according to the oil pumping volume of each interval divided, and determine the oil reservoir recovery rate of surfactant spontaneous imbibition in combination with the oil reservoir geological reserves.

[0096] In the specific embodiment of the present application, the significance of calculating the oil pumping volume by interval and accumulating lies in that the oil reservoir often has geological heterogeneity, including porosity, permeability, uneven distribution of displacement agent concentration and change of adsorption characteristics, etc., and the oil reservoir or experimental core is divided into a plurality of sub-intervals, the oil pumping volume of each interval is calculated respectively, the difference of oil displacement efficiency in different regions can be captured, and the recovery coefficient is introduced for each sub-interval to correct the oil production after the actual influence of the surfactant concentration , so as to ensure that the production prediction of each interval is more in line with the actual oil displacement effect.

[0097] The method for determining the oil reservoir recovery rate of surfactant spontaneous imbibition is:

[0098] The total oil pumping volume is calculated according to the total number of sub-intervals divided and the oil pumping volume corresponding to each sub-interval, and the formula is:

[0099]

[0100]

[0101] wherein, represents the total oil pumping volume, is the predicted oil reservoir recovery rate.

[0102] The above formulas are all dimensionless values calculated, the formula is obtained by collecting a large amount of data to simulate the most recent real situation, and the preset parameters in the formula are set by a person skilled in the art according to the actual situation.

[0103] The above embodiments can be implemented wholly or partially by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented wholly or partially in the form of a computer program product. Those skilled in the art can realize that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solutions.

[0104] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, which can be located in one place or distributed on multiple network units. Part or all of the units can be selected to achieve the purpose of the embodiments according to actual needs.

[0105] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered within the protection scope of the present application.

Claims

1. A surfactant-based spontaneous imbibition method for predicting oil recovery, characterized by, The specific steps include: Step 1: Obtain the geological parameters, wettability parameters, reservoir crude oil physical property parameters and core samples of the reservoir to be predicted, use the core samples to conduct spontaneous imbibition oil displacement experiments of surfactants, record the surfactant injection amount and crude oil production amount within a set unit imbibition recovery time under the same pressure, the geological parameters include the porosity and permeability of the core, the wettability parameters include the contact angle, and the reservoir crude oil physical property parameters include the crude oil density and crude oil viscosity; Step 2: Determine the initial concentration of the surfactant, combine the oil reservoir geological reserves and the crude oil production time requirement to draw a spontaneous imbibition recovery curve, divide the crude oil production time into an integer number of unit imbibition recovery time subintervals to obtain the imbibition recovery curve of each subinterval; Step 3: Establish a surfactant adsorption and migration model, associate the obtained related parameters of the reservoir to be predicted with the indexes affecting the concentration of the surfactant, analyze the difference between the concentration change of the surfactant and the ideal concentration change of the surfactant in each subinterval and generate a recovery coefficient, and based on the recovery coefficient in each subinterval, correct the imbibition recovery curve of the corresponding each subinterval to obtain the oil pumping amount of each interval; Step 4: Calculate the total oil pumping amount under the oil reservoir geological reserves and the crude oil production time requirement according to the oil pumping amount of each interval, and determine the oil reservoir recovery rate of the spontaneous imbibition of the surfactant in combination with the oil reservoir geological reserves; The method for drawing the spontaneous imbibition recovery curve is: The method for dividing the crude oil production time into an integer number of unit imbibition recovery time subintervals is: wherein, represents a spontaneous imbibition recovery curve, represents a geological reserve of the reservoir, represents a crude oil production duration requirement, represents a maximum crude oil production amount at the wellhead, represents a curve steepness coefficient, is a time variable, ; The method for adjusting the crude oil production time is: When the crude oil production time is an integer multiple of the unit imbibition recovery time, the production time does not need to be adjusted, and it is directly divided on average; when the crude oil production time is not an integer multiple of the unit imbibition recovery time, the number of integer unit time periods is calculated and rounded up, and then the adjusted total time is calculated based on the number of integer time periods and the unit imbibition recovery time period, the formula is: wherein, denotes rounding up, is the number of unit operation time periods after rounding up, denotes the set unit wicking recovery time, is the index of the divided sub-interval, and .

2. A surfactant-based spontaneous imbibition oil recovery prediction method according to claim 1, characterized in that, The method for establishing the surfactant adsorption and migration model is: Based on the multi-modal feature association, the obtained geological parameters, wettability parameters, reservoir crude oil physical property parameters and indexes affecting the concentration of the surfactant are associated, the indexes affecting the concentration of the surfactant include the effective diffusion coefficient, the average imbibition flow rate and the adsorption coefficient, the geological parameters include the porosity and permeability of the core, the wettability parameters include the contact angle, and the reservoir crude oil physical property parameters include the crude oil density and crude oil viscosity, the formula for multi-modal feature association is: wherein, , , denote the indicators affecting the surfactant concentration, respectively, the effective diffusion coefficient, the average imbibition flow rate, and the adsorption coefficient, is the permeability, is the crude oil viscosity, is the exponential influence function of porosity, is the porosity, is the contact angle, is the crude oil density, is the density of water, is the gravitational acceleration; Based on the Advection-Dispersion-Adsorption model, the partial differential equation of surfactant concentration under the influence of effective diffusion coefficient, average imbibition flow rate and adsorption coefficient is established, and the formula is as follows: wherein, represents a partial differential relationship of surfactant concentration based on model establishment, represents the instantaneous concentration of surfactant in the core pore, is a spatial coordinate, representing the position in the core, is the rock skeleton density.

3. A surfactant-based spontaneous imbibition oil recovery prediction method according to claim 2, characterized in that, The variation of surfactant concentration in each sub-interval is analyzed, and the imbibition recovery curve in each sub-interval is corrected based on the recovery coefficient in each sub-interval, and the method is as follows: According to the surfactant experiment from the beginning into the core to flow out, the initial conditions of the experiment are set as the initial core without surfactant , the inlet boundary is the continuous input concentration of surfactant , and the outlet boundary condition is set as the remote concentration is limited, that is ; The partial differential equation of surfactant concentration is solved by using Laplace transform, and the function solution of surfactant concentration changing with time under the joint action of diffusion, convection and adsorption is as follows: in, An analytical expression representing the surfactant concentration, used to calculate... The concentration of surfactant at any given time, Represents the complementary error function; The variation of surfactant concentration in each sub-interval is analyzed based on the function solution of surfactant concentration, and the imbibition recovery curve in each sub-interval is corrected, and the formula is as follows: wherein, represents the surface active agent concentration change amount of the first sub-interval, represents the crude oil production amount of the first sub-interval; The ideal concentration variation of the surfactant for each sub-interval The difference between the ideal concentration variation of each sub-interval and the calculated concentration variation is analyzed to generate the recovery coefficient, and the oil production of each sub-interval is corrected according to the recovery coefficient of the corresponding sub-interval to obtain the oil production of each interval, and the formula is: wherein, represents the recovery factor of the th subinterval, represents the oil production of the th subinterval.

4. The surfactant-based spontaneous imbibition oil recovery prediction method according to claim 3, characterized in that, The oil reservoir recovery of spontaneous imbibition of surfactant is determined, and the method is as follows: The total oil pumping rate is calculated according to the total number of sub-intervals and the corresponding oil pumping rate of each sub-interval, and the formula is as follows: wherein, represents the total oil pump-out, is the predicted reservoir recovery.

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