Evaluation Method for Flow Field Adaptability in High-Water-Cut Reservoirs

Abstract

The present invention provides a method for evaluating the flow field adaptability of a high water cut reservoir. The method for evaluating the flow field adaptability of a high water cut reservoir includes: Step 1, establishing a numerical simulation model of the reservoir and obtaining evaluation parameters; Step 2, performing data preprocessing; Step 3, calculating the evaluation index for the flow field adaptability of a high water cut reservoir; Step 4, finding the optimal regulation plan for the reservoir. The method for evaluating the flow field adaptability of a high water cut reservoir can accurately understand the development laws and development status of oilfields in the ultra-high water cut development stage, propose a set of systematic evaluation indexes and evaluation criteria, establish an evaluation system, effectively determine whether the current development plan is reasonable, so as to find out the main factors restricting the development effect of the oilfield at this stage, and provide a basis for the development adjustment of the reservoir in the high water cut stage.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas development, and particularly to a method for evaluating the flow field adaptability of high water cut reservoirs. Background Art

[0002] At present, most of the old oilfields in the eastern part of China have entered the high water cut and extra-high water cut periods. The remaining oil distribution is complex, the streamline is fixed for a long time, and the problem of inefficient and ineffective water circulation is prominent, which seriously restricts the sustainable development of enterprises. With the sharp increase of the water-oil ratio, the enterprise efficiency has been continuously declining, and it is difficult to improve the recovery rate. Research shows that the interaction relationship between the driving force field and the saturation field is an important factor affecting the development effect. With the different development stages, the action mechanisms and influencing factors will change significantly. At present, there is still a lack of a quantitative evaluation method for this stage characteristics. The research on the expression methods of the adaptability relationship of the flow field by domestic and foreign scholars is not very perfect, and a systematic theoretical system has not been formed. Especially, the characterization technology of the flow field intensity has not been developed maturely, and a complete flow field evaluation system has not been established yet. Most scholars have only studied some local problems such as the description of large pores and the quantitative characterization of dominant channels.

[0003] Therefore, we have invented a new method for evaluating the flow field adaptability of high water cut reservoirs to solve the above technical problems. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for evaluating the flow field adaptability of high water cut reservoirs, which can effectively determine whether the current development plan is reasonable, so as to find out the main factors restricting the development effect of the oilfield at this stage and provide a basis for the development adjustment of high water cut reservoirs.

[0005] The purpose of the present invention can be achieved by the following technical measures: a method for evaluating the flow field adaptability of high water cut reservoirs, which includes: Step 1, establishing a reservoir numerical simulation model and obtaining evaluation parameters; Step 2, performing data preprocessing; Step 3, calculating the evaluation index for the flow field adaptability of high water cut reservoirs; Step 4, finding the optimal regulation plan for the reservoir.

[0006] The purpose of the present invention can also be achieved by the following technical measures:

[0007] In Step 1, the established reservoir numerical simulation model includes: reservoir structure parameters, reservoir parameters, rock physical property parameters, reservoir fluid parameters, and oil well and water well operating system parameters.

[0008] In Step 1, the evaluation parameters are obtained from the calculation results of the reservoir numerical simulation model, specifically including the monthly pressure distribution data and the monthly oil saturation distribution data.

[0009] In step 2, to compare the magnitude relationship between the driving force and the material potential at different positions, the pressure data is transformed into the magnitude of the pressure gradient through formula (1):

[0010]

[0011] where, is the magnitude of the pressure gradient at a certain position in space, is the rate of change of pressure in the x - direction of the abscissa, is the rate of change of pressure in the y - direction of the ordinate;

[0012] Since the dimensions of the pressure gradient and the oil - saturation data are completely different, the two sets of data cannot be directly compared and analyzed. To facilitate the comparison of their spatial distribution, the two types of data are respectively normalized, and the calculation methods are shown in formula (2) and formula (3):

[0013]

[0014] where, is the magnitude of the normalized pressure gradient, is the magnitude of the maximum pressure gradient among all positions in space;

[0015]

[0016] where s o ′ is the normalized oil - saturation at a certain position in space, and Max(S oi ) is the maximum oil - saturation among all positions in space.

[0017] In step 3, the index system for evaluating the flow - field adaptability of high - water - cut oil reservoirs includes three types: spatial adaptability factor, flow - field adaptability level, and adaptability balance degree.

[0018] In step 3, the spatial adaptability factor ω i , which reflects the difference between the magnitude of the normalized pressure gradient and the matching of the normalized saturation at any position, is calculated through formula (4):

[0019]

[0020] In step 3, the flow - field adaptability level reflects the average magnitude of the matching between the overall pressure - gradient field of the flow - field and the oil - saturation, and is calculated through formula (5):

[0021]

[0022] N is the number of all data points in space.

[0023] In step 3, the adaptability balance degree δ ω, reflecting the difference degree of the spatial distribution of the flow field adaptation factor, obtained through the standard deviation calculation formula in formula (6):

[0024]

[0025] N is the number of all data points in the space.

[0026] In step 4, with the goal of minimizing the flow field adaptation level and adaptation balance degree, through optimization algorithms such as the gradient descent method and genetic algorithm, find the optimal control scheme under the conditions of changing parameters such as the number of wells, well types, injection volume, and production volume in the reservoir.

[0027] The method for evaluating the flow field adaptability of high water cut reservoirs in the present invention can realize the quantitative evaluation of the reservoir development status. Through the optimized calculation of evaluation parameters, the direction of reservoir development adjustment can be found, and improvement suggestions can be put forward to guide oilfield production. This method can accurately understand the development laws and development status of oilfields in the ultra-high water cut development stage, put forward a set of systematic evaluation indicators and evaluation criteria, establish an evaluation system, and can effectively judge whether the current development plan is reasonable, so as to find out the main factors restricting the oilfield development effect at this stage and provide a basis for the development adjustment of high water cut reservoirs. Brief Description of the Drawings

[0028] Figure 1 It is a flowchart of a specific embodiment of the method for evaluating the flow field adaptability of high water cut reservoirs in the present invention. Detailed Embodiment

[0029] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0030] As Figure 1 shown, Figure 1 It is a flowchart of the method for evaluating the flow field adaptability of high water cut reservoirs in the present invention.

[0031] Step 1: Model establishment and parameter acquisition

[0032] For the target research area, establish a reservoir numerical simulation model, which usually includes: reservoir structure parameters, reservoir parameters, rock physical property parameters, reservoir fluid parameters, oil well and water well operating regime parameters, etc. The reservoir numerical simulation method is a conventional research method in the reservoir engineering specialty in the oil and gas field development field.

[0033] Obtain evaluation parameters from the calculation results of the reservoir numerical simulation model, specifically including monthly pressure distribution data and monthly oil saturation distribution data.

[0034] Step 2, Data Preprocessing

[0035] In order to compare the magnitude relationship between the driving force and the material potential, the pressure data needs to be converted into the magnitude of the pressure gradient through formula (1).

[0036]

[0037] Among them, is the magnitude of the pressure gradient at a certain position in space, is the rate of change of pressure along the x-axis of the abscissa, is the rate of change of pressure along the y-axis of the ordinate.

[0038] Since the dimensions of the pressure gradient and the oil saturation data are completely different, the two sets of data cannot be directly compared and analyzed. To facilitate the comparison of their spatial distribution, the two types of data are respectively normalized, and the calculation methods are shown in formula (2) and formula (3).

[0039]

[0040] Among them, is the magnitude of the normalized pressure gradient, is the magnitude of the maximum pressure gradient among all positions in space.

[0041]

[0042] Among them, S o ′ is the normalized oil saturation at a certain position in space, and Max(S oi ) is the maximum oil saturation among all positions in space.

[0043] Step 3, Calculation of Evaluation Index

[0044] The index system adopted for the evaluation of the flow field adaptability of high water cut oil reservoirs includes three types: spatial adaptability factor, flow field adaptability level, and adaptability balance degree.

[0045] Spatial adaptability factor ω i , which reflects the difference between the magnitude of the normalized pressure gradient and the normalized saturation at any position, and is calculated through formula (4).

[0046] (4)

[0048] Flow field adaptability level reflects the average magnitude of the matching between the overall pressure gradient field of the flow field and the oil saturation, and is calculated through formula (5).

[0049]

[0050] Adaptability balance degree δω , reflecting the difference degree of the spatial distribution of the flow field adaptation factor, which is obtained through the standard deviation calculation formula in formula (6).

[0051]

[0052] Step 4: Find the optimal regulation plan for the oil reservoir.

[0053] With the flow field adaptation level The adaptation balance degree δ ω being the minimum as the goal, through optimization algorithms such as the gradient descent method and genetic algorithm, find the optimal regulation plan under the conditions of changing parameters such as the number of wells, well types, injection volume, and production volume in the oil reservoir.

[0054] The following is a specific embodiment of applying the present invention, including the following steps:

[0055] Step 1, establish an oil reservoir geological model and a numerical simulation model. The number of model grids is 30×30, a total of 900. Through simulation calculations, 900 pressure and saturation point data of the oil reservoir are obtained.

[0056] Step 2, convert the pressure data and oil saturation data into normalized pressure gradient modulus and normalized oil saturation through formulas (1), (2), and (3).

[0057] Step 3, calculate the spatial adaptation factor ω of 900 points through formula (4) i , calculate the flow field adaptation level through formula (5) and the adaptation balance degree δ ω , and at this time, the adaptation evaluation result of the current state is obtained.

[0058] Step 4, under the condition that the injection-production well pattern remains unchanged, change the injection volume and production reserve. According to the simulation calculation results, a new set of evaluation index results can be obtained Adopt the optimization algorithm, continue to change the injection volume and production volume until the minimum value and δ ω value are obtained, and this is the optimal plan at this time.

[0059] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for evaluating the flow field adaptability of high water cut oil reservoirs, characterized in that The method for evaluating the flow field adaptability of a high water cut reservoir includes: Step 1: Establish a reservoir numerical simulation model and obtain evaluation parameters; Step 2: Conduct data preprocessing; Step 3: Calculate the evaluation index for the flow field adaptability of a high water cut reservoir; Step 4: Find the optimal regulation plan for the reservoir; In Step 1, the established reservoir numerical simulation model includes: reservoir structure parameters, reservoir parameters, rock physical property parameters, reservoir fluid parameters, and oil well and water well operating regime parameters; In Step 1, obtain evaluation parameters from the calculation results of the reservoir numerical simulation model, including monthly pressure distribution data and monthly oil saturation distribution data; In Step 2, in order to compare the position and magnitude relationship between the driving force and the material potential, convert the pressure distribution data into the modulus of the pressure gradient through formula (1): Among them, is the modulus of the pressure gradient at a certain position in space, is the rate of change of pressure in the x-direction of the abscissa, is the rate of change of pressure in the y-direction of the ordinate; Since the dimensions of the pressure gradient and oil saturation data are completely different, the two sets of data cannot be directly compared and analyzed. To facilitate the comparison of their spatial distribution, normalize the two types of data respectively, and the calculation methods are shown in formula (2) and formula (3): Among them, the magnitude of the normalized pressure gradient, is the magnitude of the maximum pressure gradient among all positions in space; Among them, S o ′ is the normalized oil saturation at a certain position in space, s oi is the oil saturation at a certain position in space; Max(S oi ) is the maximum oil saturation among all positions in space; In Step 3, the evaluation index system for the flow field adaptability of a high water cut reservoir includes three types: spatial adaptability factor, flow field adaptability level, and adaptability balance degree; In step 3, the spatial adaptation factor ω i , which reflects the difference between the magnitude of the normalized pressure gradient and the normalized saturation match at any position, is calculated by formula (4): In step 3, the flow field adaptation level reflects the average magnitude of the matching between the overall pressure gradient field of the flow field and the oil saturation, and is calculated by formula (5): N is the number of all data points in the space; In step 3, the adaptation equilibrium degree δ ω , which reflects the difference degree of the spatial distribution of the flow field adaptation factor, is obtained through the standard deviation calculation formula in formula (6). In Step 4, with the goal of minimizing the flow field adaptability level and adaptability balance degree, find the optimal regulation plan under the conditions of changing the number of wells, well types, injection volume, and production volume of the reservoir through an optimization algorithm.

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