A method, system, and electronic equipment for assessing oil production in dolomite reservoirs.

Abstract

This invention discloses a method, system, and electronic equipment for dividing the oil production of dolomite reservoirs during testing. Belonging to the field of petroleum exploration production capacity prediction technology, the method preprocesses the oil production data to normalize and convert the reservoir's testing capacity; quantitatively characterizes the reservoir's reservoir properties; determines the lower limit of reservoir parameters based on the oil production and reservoir properties within the testing section, improving the accuracy and rationality of the lower limit; divides the testing section into multiple producing sub-layers based on the lower limit of reservoir parameters; calculates the reservoir properties ratio of each sub-layer; and calculates the production of each producing sub-layer based on the reservoir properties ratio. This oil production capacity division method based on multi-well optimization establishes an effective link between reservoir properties and oil production capacity, achieving reasonable division of oil production and solving the problem of dividing reservoir testing capacity.

Description

Technical Field

[0001] This invention belongs to the field of petroleum exploration production capacity prediction technology, specifically relating to a method, system and electronic equipment for dividing oil production in dolomite reservoir testing. Background Technology

[0002] The commonly used production volume splitting method in well logging is the KH coefficient-based method. Its principle is based on the assumption that oil and gas are distributed throughout the effective thickness. Production volume is split according to the ratio of the permeability of each producing layer to the effective thickness. This method is more suitable for ideal formations. However, the KH splitting method has limitations in dolomite reservoirs, mainly in the following aspects: Due to the presence of fractures and vulnerabilities in dolomite reservoirs, the calculation error of permeability is relatively large, resulting in a significant error after splitting; and the effective producing interval within very thick test layers is difficult to determine. Summary of the Invention

[0003] In order to overcome the shortcomings of the prior art, the present invention aims to provide a method, system and electronic equipment for dividing the oil production of dolomite reservoirs, so as to solve the technical problems of large errors after division and difficulty in determining the effective production section within the thick oil testing layer.

[0004] To achieve the above objectives, the present invention employs the following technical solution:

[0005] A method for dividing the oil production in a dolomite reservoir includes the following steps:

[0006] Acquire well logging data and oil testing data, preprocess the oil testing data, obtain the oil production rate under a unified standard based on the oil testing data, and calculate the reservoir performance within the oil testing section based on the well logging data.

[0007] The lower limit of reservoir parameters is determined based on the oil production rate and the reservoir performance in the test section.

[0008] Based on the lower limit of reservoir parameters, the test section is divided into multiple producing sub-layers, and the reservoir performance ratio of each sub-layer is calculated.

[0009] The output of each production layer is calculated based on the proportion of storage performance.

[0010] Preferably, when preprocessing the oil test data, the oil test production volume is normalized and converted according to influencing factors to form an oil test production volume under a unified standard that reflects the production capacity characteristics of different wells.

[0011] Preferably, the normalization conversion specifically includes:

[0012]

[0013] In the formula, Q o Daily oil production; Q gDaily gas production; Q w Daily water production; P o V represents the oil pressure during testing. a The nozzle is for testing; Y represents the converted liquid production volume.

[0014] Preferably, the calculation of reservoir performance within the test section is as follows: within the test section, an integral method is used according to depth, and the reservoir performance is quantitatively calculated by setting specific cutoff values ​​for parameters characterizing reservoir performance; and by setting an effective step size value, the cutoff value is continuously and stably increased, and the reservoir performance within the test section at different cutoff values ​​is calculated.

[0015] Preferably, the formula for quantitatively calculating storage performance is:

[0016]

[0017] In the formula, sdep and edep are the top and bottom boundaries of the test section, respectively; sdep_ and edep_t are the top and bottom boundaries of the section that is less than the cutoff value, respectively. These are parameters characterizing the reservoir's storage performance.

[0018] Preferably, the step of determining the lower limit of reservoir parameters based on the test oil production and reservoir performance within the test section involves using the test oil production and reservoir performance within the test section as input data, calculating the covariance and overall variance among multiple wells, and establishing a correlation coefficient model. The formula for determining the lower limit of reservoir parameters based on the maximum correlation coefficient model is as follows:

[0019] Energy storage in the test section:

[0020] X = X1, X2, ..., X n (3)

[0021] Test oil production capacity:

[0022] Y = Y1, Y2, ..., Y n (4)

[0023] Covariance:

[0024]

[0025] Overall variance:

[0026]

[0027] Correlation coefficient:

[0028]

[0029] The lower limit of reservoir parameters is determined by the magnitude of the correlation coefficient;

[0030] Where X represents reservoir performance, Xi represents reservoir performance of different wells, Y represents the difference in oil testing section, and Yi represents the production of oil testing section of different wells.

[0031] Preferably, the step of dividing the test section according to the lower limit of reservoir parameters and establishing a production capacity partitioning model involves dividing the test section into multiple sub-layers based on the lower limit of reservoir parameters, and establishing a production capacity partitioning model based on the reservoir parameters and thickness of each sub-layer, resulting in the following partitioning relationship:

[0032]

[0033] In the formula, Q t Q represents the converted product yield; i This represents the yield of the i-th split layer after conversion; H represents the standard energy storage parameters for the i-th slit layer; i Let be the thickness of the i-th slice.

[0034] This invention also discloses a dolomite reservoir production splitting system based on a multi-well production optimization method, comprising:

[0035] The preprocessing unit is used to acquire well logging data and oil testing data, preprocess the oil testing data, obtain the oil production rate under a unified standard based on the oil testing data, and calculate the reservoir performance within the oil testing section based on the well logging data.

[0036] The first calculation unit is used to determine the lower limit of reservoir parameters based on the oil production rate and the reservoir performance in the oil test section.

[0037] The second calculation unit is used to divide the test section into multiple producing sub-layers according to the lower limit of reservoir parameters, and calculate the reservoir performance ratio of each sub-layer.

[0038] The third calculation unit is used to calculate the output of each production layer based on the storage performance ratio.

[0039] The present invention also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the dolomite reservoir oil production splitting method described above.

[0040] The present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the dolomite reservoir oil production splitting method described above.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] This invention discloses a method for dividing the oil production of dolomite reservoirs during testing. The method preprocesses the testing data, normalizes and converts the tested oil production capacity, and quantitatively characterizes the reservoir's storage properties. It determines the lower limit of reservoir parameters based on the tested oil production and storage properties within the tested section, improving the accuracy and rationality of the lower limit. Based on the lower limit, the tested section is divided into multiple producing sub-layers, and the storage performance ratio of each sub-layer is calculated. The production capacity of each sub-layer is then calculated based on this ratio. This multi-well optimization-based method establishes an effective link between reservoir storage properties and tested oil production capacity, achieving a reasonable division of tested oil production. It solves the problems of large errors after division and difficulty in determining effective producing sections within extremely thick tested layers.

[0043] Furthermore, by calculating the covariance and overall variance between the production capacity and reservoir performance of multi-well test sections and establishing a correlation coefficient model, a reasonable lower limit for reservoir performance parameters is determined. Attached Figure Description

[0044] Figure 1 This is a flowchart of the method of the present invention;

[0045] Figure 2 This is a flowchart of a method according to an embodiment of the present invention;

[0046] Figure 3 This is a schematic diagram of the storage performance calculation method with variable cutoff value provided in the embodiments of the present invention;

[0047] Figure 4 This is a graph showing the correlation between production capacity and energy storage when the correlation coefficient is at its maximum, provided in this embodiment of the invention.

[0048] Figure 5 This is a diagram illustrating the output splitting effect provided in an embodiment of the present invention;

[0049] Figure 6 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0050] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0051] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0052] The present invention will now be described in further detail with reference to the accompanying drawings:

[0053] This invention addresses the problem of analyzing existing logging and oil testing data in the research block, as well as oil and gas production data under different operating conditions within long perforation sections. It proposes a method for dividing oil testing production in dolomite reservoirs. This method utilizes normalized oil testing production and calculated reservoir performance to calculate the covariance and overall variance among multiple wells, establishes a correlation coefficient model, and determines the lower limit of reservoir parameters, providing a reliable data foundation for the reasonable division of oil testing production.

[0054] To achieve the above objectives, the present invention provides the following technical solution:

[0055] This invention discloses a method for dividing the oil production during oil testing in dolomite reservoirs, see [link to relevant documentation]. Figure 1 This includes the following steps:

[0056] S1: Acquire well logging data and oil testing data, preprocess the oil testing data, obtain the oil production rate under a unified standard based on the oil testing data, and calculate the reservoir performance within the oil testing section based on the well logging data;

[0057] S2: Determine the lower limit of reservoir parameters based on the oil production rate and reservoir performance in the test section;

[0058] S3: Based on the lower limit of reservoir parameters, the test section is divided into multiple producing sub-layers, and the reservoir performance ratio of each sub-layer is calculated.

[0059] S4: Calculate the output of each production layer based on the storage performance ratio.

[0060] In some embodiments, when preprocessing the oil test data, the oil test production is normalized and converted according to influencing factors to form an oil test production under a unified standard that reflects the production capacity characteristics of different wells.

[0061] In some embodiments, the normalization conversion specifically includes:

[0062]

[0063] In the formula, Q o Daily oil production; Q g Daily gas production; Q w Daily water production; P o V represents the oil pressure during testing. a The nozzle is for testing; Y represents the converted liquid production volume.

[0064] In step S1, the processing and preprocessing of the oil test data involves the normalization of the data, primarily including the standardization of the produced phase, operating conditions, and production pressure differential. Through gas-liquid conversion and by standardizing nozzle size and pressure differential, a uniform standard for the oil test production volume is achieved.

[0065] In some embodiments, the calculation of reservoir performance within the test section involves: using an integral method based on depth within the test section, quantitatively calculating reservoir performance by setting specific cutoff values ​​for parameters characterizing reservoir performance; and by setting effective step sizes to ensure continuous and stable increases in the cutoff values, calculating the reservoir performance within the test section at different cutoff values. The method of calculating continuously variable reservoir performance using depth integration is a mature calculation method with high computational accuracy.

[0066] In some embodiments, the formula for quantitatively calculating storage performance is:

[0067]

[0068] In the formula, Sdep and edep are the top and bottom boundaries of the test section, respectively; sdep_cut and edep_cut t are the top and bottom boundaries of the section that is less than the cutoff value, respectively. These are parameters characterizing the reservoir's storage performance.

[0069] In some embodiments, determining the lower limit of reservoir parameters based on the test oil production and reservoir performance within the test section involves using the test oil production and reservoir performance within the test section as input data, calculating the covariance and overall variance among multiple wells, and establishing a correlation coefficient model. The formula for determining the lower limit of reservoir parameters based on the maximum correlation coefficient model is as follows:

[0070] Energy storage in the test section:

[0071] X = X1, X2, ..., X n (3)

[0072] Test oil production capacity:

[0073] Y = Y1, Y2, ..., Y n (4)

[0074] Covariance:

[0075]

[0076] Overall variance:

[0077]

[0078] Correlation coefficient:

[0079]

[0080] The lower limit of reservoir parameters is determined by the magnitude of the correlation coefficient;

[0081] Where X represents reservoir performance, Xi represents reservoir performance of different wells, Y represents the difference in oil testing section, and Yi represents the production of oil testing section of different wells.

[0082] In some embodiments, the step of dividing the test section according to the lower limit of reservoir parameters and establishing a production capacity partitioning model involves dividing the test section into multiple sub-layers based on the lower limit of reservoir parameters, and establishing a production capacity partitioning model based on the reservoir parameters and thickness of each sub-layer, resulting in the following partitioning relationship:

[0083]

[0084] In the formula, Q t Q represents the converted product yield; i This represents the yield of the i-th split layer after conversion; H represents the standard energy storage parameters for the i-th slit layer; i Let be the thickness of the i-th slice.

[0085]

Example

[0086] like Figure 2 As shown, the present invention discloses a method for allocating oil production in dolomite reservoirs using a multi-well production optimization approach, which is carried out according to the following steps:

[0087] Step 1: Organize the test oil data. Normalize and preprocess the test oil production volume, considering factors such as liquid phase, operating conditions, and production pressure differential, to obtain the test oil yield under a unified standard.

[0088] Normalized conversion formula for oil production yield:

[0089]

[0090] In the formula, Q o Daily oil production, m 3 / d;Q g Daily gas production, m 3 / d;Q w Daily water production, m 3 / d;Po The oil pressure during the test is measured in MPa; V. a The nozzle used for testing is in mm; Y represents the converted liquid production rate in m. 3 / d.

[0091] Within the test section, an integral method is used based on depth. By setting specific cutoff values ​​for parameters characterizing reservoir performance, the reservoir performance is quantitatively calculated. Furthermore, by setting effective step sizes, the cutoff values ​​are continuously and stably increased, thereby calculating the reservoir performance within the test section at different cutoff values.

[0092]

[0093] In the formula: sdep and edep are the top and bottom boundaries of the test section, respectively, in meters; sdep_cut and edep_cut are the top and bottom boundaries of the section that is less than the cutoff value, respectively, in meters; These are dimensionless parameters characterizing reservoir performance. The reservoir performance at different cutoff values ​​was calculated using VBI programming.

[0094] Step two involves using the oil production and reservoir performance determined in step one as input data to calculate the covariance and overall variance among multiple wells, establishing a correlation coefficient model, and determining the lower limit of reservoir parameters based on the maximum correlation coefficient model. The specific algorithm is as follows:

[0095] Energy storage in the test section:

[0096] X = X1, X2, ..., X n (3)

[0097] Test oil production capacity:

[0098] Y = Y1, Y2, ..., Y n (4)

[0099] Covariance:

[0100]

[0101] Overall variance:

[0102]

[0103] Correlation coefficient:

[0104]

[0105] The lower limit of reservoir parameters is determined by the magnitude of the correlation coefficient (see appendix). Figure 3 ).

[0106] Step 3: Based on the lower limit of reservoir parameters, divide the test section into multiple sub-layers and calculate the reservoir performance ratio of each sub-layer;

[0107] Step four: Calculate the output of each production layer based on the storage performance ratio; specifically, the following splitting formula is used:

[0108]

[0109] In the formula, Q t The converted product volume is m 3 / d;Q i m represents the yield of the i-th split layer after conversion. 3 / d; H represents the standard energy storage parameters for the i-th slit layer; i Let be the thickness of the i-th slice.

[0110] The following is a detailed description of the specific implementation of this embodiment to support the technical problem to be solved by the present invention. The operation is carried out according to the following steps:

[0111] Step 1: Select 7 wells in the study area with clear oil test results and complete logging data as the basic sample for normalized conversion of production capacity to obtain the oil production volume under a unified standard.

[0112] Step two involves organizing the reservoir characterization parameters of the seven selected wells. Within the test section, an initial cutoff value for the reservoir characterization parameter is set, excluding depths where the parameter is less than the cutoff value. Integration calculations are then performed. Next, an effective step size is set, and integration calculations continue to be performed, thereby calculating the reservoir performance within the test section at consecutively different cutoff values. Figure 3 As shown.

[0113] Step 3: Using the reservoir performance of the test section at different cutoff values ​​obtained in Step 2 and the standard test production calculated in Step 1, calculate the covariance and overall variance among multiple wells, and establish a correlation coefficient model. Determine the lower limit of reservoir parameters based on the maximum correlation coefficient. The correlation relationship diagram is shown below. Figure 4 .

[0114] Step four: Based on the lower limit of reservoir parameters determined in step three, the testing section is divided into multiple sub-layers. The reservoir performance of each sub-layer and the cumulative total reservoir performance are calculated based on the reservoir parameters and thickness. The production of a single sub-layer is calculated using the proportion of reservoir performance. The results of this application in a certain well are shown below. Figure 5 .

[0115] In summary, the innovation of the dolomite reservoir testing production fractionation method proposed in this invention lies in: normalizing and converting the reservoir testing production capacity; quantitatively characterizing the reservoir's reservoir properties; and determining a reasonable lower limit for reservoir properties parameters by calculating the covariance and overall variance between multi-well testing section production capacity and reservoir properties and establishing a correlation coefficient model. This method establishes an effective link between reservoir properties and testing production capacity, achieving a reasonable fractionation of testing production.

[0116] This invention also discloses a dolomite reservoir production splitting system based on multi-well production optimization, see [link to relevant documentation]. Figure 6 ,include:

[0117] The preprocessing unit is used to acquire well logging data and oil testing data, preprocess the oil testing data, obtain the oil production rate under a unified standard based on the oil testing data, and calculate the reservoir performance within the oil testing section based on the well logging data.

[0118] The first calculation unit is used to determine the lower limit of reservoir parameters based on the oil production rate and the reservoir performance in the oil test section.

[0119] The second calculation unit is used to divide the test section into multiple producing sub-layers according to the lower limit of reservoir parameters, and calculate the reservoir performance ratio of each sub-layer.

[0120] The third calculation unit is used to calculate the output of each production layer based on the storage performance ratio.

[0121] The present invention also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the dolomite reservoir oil production splitting method described above.

[0122] The present invention also discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the dolomite reservoir oil production splitting method described above.

[0123] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0124] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0125] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0126] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for testing production of a dolomite reservoir, characterized in that, The method comprises the following steps: obtaining logging data and test data, and pre-processing the test data to obtain test liquid production under a unified standard according to the test data; calculating reservoir performance in a test section according to the logging data; determining a lower limit of reservoir parameters according to the test liquid production and the reservoir performance in the test section; dividing the test section into multiple production sublayers according to the lower limit of the reservoir parameters, and calculating a reservoir performance proportion of each sublayer; calculating the production of each production sublayer according to the reservoir performance proportion. The calculation of the reservoir performance in the test section is: quantitatively calculating the reservoir performance by setting a specific cutoff value of a reservoir performance parameter according to depth in the test section by using the integral method, and continuously and stably increasing the cutoff value by setting an effective step value to calculate the reservoir performance in the test section at different cutoff values. The determination of the lower limit of the reservoir parameters according to the test liquid production and the reservoir performance in the test section is: taking the test liquid production and the reservoir performance in the test section as input data, calculating the covariance and the overall variance among multiple wells, establishing a correlation coefficient model, and determining the lower limit of the reservoir parameters according to the maximum correlation coefficient model.

2. The method of claim 1, wherein, The pre-processing of the test data is: normalizing and converting the test liquid production according to influencing factors to form the test liquid production under the unified standard to reflect the productivity characteristics of different wells.

3. The method of claim 2, wherein, The normalizing and converting is specifically: （1） wherein is the daily oil production, ; is the daily gas production, ; is the daily water production, ; is the oil pressure during the test, ; is the choke used during the test, ; Y is the converted liquid production, .

4. The method of claim 1, wherein, The calculation formula of the quantitatively calculated reservoir performance is: （2） wherein , are the top and bottom boundaries of the test oil section, m; , are the top and bottom boundaries of the section less than the cutoff value, m; is a reservoir storage performance characterization parameter.

5. The method of claim 1, wherein, The formula for determining the lower limit of the reservoir parameters according to the maximum correlation coefficient model is as follows: Reservoir energy in the test section: X = X1, X2,..., X n (3) Production capacity in the test section: Y = Y1, Y2,..., Y n (4) Covariance: （5） Overall variance: （6） Correlation coefficient: （7） The lower limit of the reservoir parameters is determined by the size of the correlation coefficient. wherein, represents the reservoir performance, represents the reservoir performance of different wells, represents the test production of different wells, represents the test production of different wells.

6. The method of claim 1, wherein, The calculation of the production of each production sublayer according to the reservoir performance proportion is specifically using the following splitting relationship formula: （8） wherein, is the converted liquid production, ; is the converted liquid production of the i-th split layer, ; is the energy storage standard parameter of the i-th split layer; is the thickness of the i-th split layer, m.

7. A dolomite reservoir test production splitting system by multi-well productivity optimization method, characterized in that, It comprises: a pre-processing unit for obtaining logging data and test data, and pre-processing the test data to obtain test liquid production under a unified standard according to the test data; calculating reservoir performance in a test section according to the logging data; a first calculation unit for determining a lower limit of reservoir parameters according to the test liquid production and the reservoir performance in the test section; a second calculation unit for dividing the test section into multiple production sublayers according to the lower limit of the reservoir parameters, and calculating a reservoir performance proportion of each sublayer; a third calculation unit for calculating the production of each production sublayer according to the reservoir performance proportion. 8.An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the dolomite reservoir test production splitting method according to any one of claims 1-6 when executing the computer program. 9.A computer readable storage medium storing a computer program, wherein the computer program implements the steps of the dolomite reservoir test production splitting method according to any one of claims 1-6 when executed by a processor.

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