Offshore oilfield development effect grading method, device, equipment and medium

Abstract

The invention relates to the technical field of oil and gas field development, and discloses an offshore oilfield development effect grading method, device and equipment and a medium, which are used for determining a plurality of key indexes and a main control parameter group corresponding to each key index. And for any developed oil field in the oil fields of the target type, inputting the parameter value of each main control parameter of the developed oil field into the relation model for calculation to obtain the index expected value of each key index of the developed oil field. And determining a relative deviation value of each key index of the developed oil field according to the index expected value and the index actual value of each key index of the developed oil field. And according to the weight coefficient of each key index, carrying out weighted summation on the relative deviation value of each key index of the developed oil field to obtain a comprehensive deviation value of the developed oil field, and further determining the development effect grade of the developed oil field based on a set evaluation threshold value. The method can improve the evaluation accuracy of the development effect of the developed oil field.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, and in particular to a method, apparatus, equipment and medium for classifying the development effect of offshore oil fields. Background Technology

[0002] With the development of science and technology, oilfield development technology has been continuously improved. Among these improvements, the evaluation of oilfield development effectiveness is an integral part of the entire development process. Its purpose is to promptly grasp reservoir dynamics and systematically evaluate oilfield development policies. A reasonable and accurate evaluation of oilfield development effectiveness and the summarization of development experience are of paramount importance in guiding more rational and efficient oilfield development.

[0003] Offshore oilfields have entered a "high-and-low" stage, characterized by small well-controlled reserves, low reserve-to-production ratios, and declining oil production per well for both intervention and adjustment wells. This makes efficient tapping of potential increasingly difficult, necessitating a systematic study of oilfield development patterns and the development of scientific and rational strategies to enhance development effectiveness and improve recovery rates.

[0004] However, the accuracy of the relevant technologies in evaluating the development effects of offshore oil fields is relatively low. Summary of the Invention

[0005] This invention provides a method, apparatus, equipment, and medium for classifying the development effect of offshore oilfields, in order to address the shortcomings of low accuracy in evaluating the development effect of offshore oilfields in related technologies and improve the accuracy of evaluation.

[0006] In a first aspect, the present invention provides a method for classifying the development effects of offshore oil fields, comprising: Multiple key indicators for evaluating the development effect of target type oilfields are identified, as well as a set of master control parameters corresponding to each key indicator, wherein each set of master control parameters corresponding to the key indicator includes at least one master control parameter. For any developed oilfield in the target type of oilfield, the parameter value of each of the main control parameters of the developed oilfield is input into the created relational model for calculation to obtain the expected value of each of the key indicators of the developed oilfield. Based on the expected and actual values ​​of each key indicator of the developed oilfield, determine the relative deviation value of each key indicator of the developed oilfield. Based on the weighting coefficient of each key indicator, the relative deviation values ​​of each key indicator of the developed oilfield are weighted and summed to obtain the comprehensive deviation value of the developed oilfield. Based on the comprehensive deviation value of the developed oilfield and the set evaluation threshold, the development effect level of the developed oilfield is determined.

[0007] Optionally, the relational model includes a relational sub-model corresponding to each key indicator, the multiple key indicators include a first key indicator, and the master control parameter group corresponding to the first key indicator includes multiple first master control parameters; The process of creating the relational sub-model corresponding to the first key indicator includes: Obtain the index value of the first key indicator for each of the developed oil fields, and the parameter value of each of the first master control parameters for each of the developed oil fields; Using the first key indicator as the dependent variable and each of the first master control parameters as the independent variable, a multiple linear regression relationship between the dependent variable and each of the independent variables is established based on the actual values ​​of the first key indicator of each developed oilfield and the parameter values ​​of each of the first master control parameters of each developed oilfield. The multiple linear regression equation is used as the sub-model corresponding to the first key indicator.

[0008] Optionally, the step of inputting the parameter values ​​of each of the main control parameters of the developed oilfield into the created relational model for calculation to obtain the expected value of each of the key indicators of the developed oilfield includes: For any of the key indicators of the developed oilfield, the parameter value of each of the main control parameters corresponding to the key indicator of the developed oilfield is input into the relational sub-model corresponding to the key indicator for calculation to obtain the expected value of the key indicator of the developed oilfield.

[0009] Optionally, for any of the key indicators of the developed oilfield, the actual value of the key indicator of the developed oilfield is subtracted from the expected value of the indicator to obtain the corresponding difference. The ratio of the difference to the expected value of the indicator is determined as the relative deviation value of the key indicator of the developed oilfield.

[0010] Optionally, the evaluation threshold includes an upper limit value greater than 0 and a lower limit value less than 0, wherein the absolute values ​​of the upper limit value and the lower limit value are equal; The determination of the development effectiveness level of the developed oilfield based on the comprehensive deviation value and the set evaluation threshold includes: If the comprehensive deviation value of the developed oilfield is greater than the upper limit value, then the development effect level of the developed oilfield is determined to be Level 1; If the comprehensive deviation value of the developed oilfield is greater than or equal to the lower limit value and less than or equal to the upper limit value, then the development effect level of the developed oilfield is determined to be Level II. If the comprehensive deviation value of the developed oilfield is less than the lower limit value, then the development effect level of the developed oilfield is determined to be level three.

[0011] Optionally, the relational sub-model corresponding to the first key indicator is: ; in, R e This is the expected value of the first key indicator; The total number of the first master control parameters. For the first i The parameter values ​​of the first master control parameter; For the first i The coefficients of the first master control parameter; C This is a constant term.

[0012] Optionally, the target type of oilfield is marine sandstone, conventional heavy oil deltaic facies, conventional heavy oil fluvial facies, or integrated medium-low viscosity or complex fault blocks. The key indicators include at least two of the following: water drive reserve control level, water drive reserve utilization level, pressure maintenance level, water cut increase rate, comprehensive decline rate of unit oil production rate, recovery rate, end-stage recovery rate, water injection quality compliance rate, water injection well distribution rate, distribution layer qualification rate, and comprehensive oil and water well operating rate.

[0013] Secondly, the present invention provides a method for classifying the development effects of offshore oil fields, including: The first determining unit is used to determine multiple key indicators for evaluating the development effect of target type oilfields, and a main control parameter group corresponding to each key indicator, wherein each main control parameter group corresponding to the key indicator includes at least one main control parameter. The calculation unit is used to input the parameter values ​​of each of the main control parameters of any developed oilfield in the target type oilfield into the created relational model for calculation, so as to obtain the expected value of each of the key indicators of the developed oilfield. The second determining unit is used to determine the relative deviation value of each key indicator of the developed oilfield based on the expected value and actual value of each key indicator of the developed oilfield. The weighting unit is used to perform a weighted summation of the relative deviation values ​​of each of the key indicators of the developed oilfield according to the weight coefficient of each key indicator, so as to obtain the comprehensive deviation value of the developed oilfield. The third determining unit is used to determine the development effect level of the developed oilfield based on the comprehensive deviation value of the developed oilfield and the set evaluation threshold.

[0014] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the offshore oilfield development effect grading method described in the first aspect or any corresponding embodiment thereof.

[0015] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the offshore oilfield development effect grading method described in the first aspect or any corresponding embodiment thereof.

[0016] This invention provides a method, apparatus, equipment, and medium for grading the development effect of offshore oilfields. It identifies multiple key indicators for evaluating the development effect of target type oilfields, and a set of master control parameters corresponding to each key indicator. Each master control parameter set includes at least one master control parameter. For any developed oilfield of the target type, the parameter values ​​of each master control parameter of the developed oilfield are input into a created relational model for calculation to obtain the expected value of each key indicator of the developed oilfield. Based on the expected and actual values ​​of each key indicator of the developed oilfield, the relative deviation value of each key indicator is determined. According to the weighting coefficient of each key indicator, the relative deviation values ​​of each key indicator of the developed oilfield are weighted and summed to obtain the comprehensive deviation value of the developed oilfield. Based on the comprehensive deviation value of the developed oilfield and a set evaluation threshold, the development effect level of the developed oilfield is determined. This invention can perform quantitative calculations based on oilfield production-related data, and evaluate the development effect level of each developed oilfield in the target type of oilfield according to the quantitative calculation results, effectively realizing the objective evaluation of the development effect level of developed oilfields and improving the accuracy of the evaluation of the development effect of developed oilfields. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart of a method for classifying the development effects of offshore oilfields, provided as an embodiment of the present invention; Figure 2 A data table of recovery rate and main controlling factor groups for various developed oilfields in a target type of oilfield provided for embodiments of the present invention; Figure 3A data table of recovery rate and main controlling factor groups for various developed oilfields in a target type of oilfield provided for embodiments of the present invention; Figure 4 A chart grading the development effect of various developed oilfields based on recovery rate, provided as an embodiment of the present invention; Figure 5 A classification chart for the development effect of various developed oilfields based on recovery rate, provided as an embodiment of the present invention; Figure 6 This is a schematic diagram of a device for grading the development effect of an offshore oilfield, provided in an embodiment of the present invention. Figure 7 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0020] The following is combined with Figures 1-5 The present invention describes a method for classifying the development effects of offshore oil fields.

[0021] like Figure 1 As shown in the figure, this embodiment proposes a first method for classifying the development effect of offshore oil fields, which may include the following steps: S101. Determine multiple key indicators for evaluating the development effect of target type oilfields, and the main control parameter group corresponding to each key indicator. Each main control parameter group corresponding to each key indicator includes at least one main control parameter.

[0022] The target type of oilfield is a specific category of oilfield. Optionally, the target type of oilfield may be marine sandstone, conventional heavy oil deltaic facies, conventional heavy oil fluvial facies, or integrated low-to-medium viscosity or complex fault blocks.

[0023] Specifically, the target type of oil field may include one or more developed oil fields.

[0024] Key indicators refer to metrics used to measure whether oilfield and reservoir development and production have achieved expected targets in terms of production, recovery rate, and economic benefits. Optionally, these key indicators may include at least two of the following: water drive reserve control level, water drive reserve utilization level, pressure maintenance level, water cut increase rate, overall decline rate per unit production rate, recovery rate, end-stage recovery rate, water injection quality compliance rate, water injection well distribution rate, distribution layer qualification rate, and overall oil-water well operating rate.

[0025] Specifically, the master control parameters are the dynamic and static parameters of the oilfield and reservoir that play a leading role in the changes of key indicators. Master control parameters can include daily oil production, oil production rate, water cut, oil layer thickness, oil-bearing area, and well-controlled reserves, and can be comprehensively determined based on the specific conditions of the oilfield and reservoir.

[0026] The key indicator's corresponding master control parameter group includes all the master control parameters of that key indicator.

[0027] It should be noted that each key indicator can correspond to one or more master control parameters. The following example illustrates the key indicators and their corresponding master control parameter groups.

[0028] Example 1: Taking the key indicator recovery rate as an example, the main control parameter group corresponding to the recovery rate includes effective thickness, porosity, well-controlled reserves, mobility, permeability, oil-water viscosity ratio, and peak production rate.

[0029] S102. For any developed oilfield in the target type oilfield, input the parameter values ​​of each main control parameter of the developed oilfield into the created relational model for calculation to obtain the expected value of each key indicator of the developed oilfield.

[0030] Specifically, in this embodiment, for any key indicator of an developed oilfield, the parameter values ​​of each main control parameter of that key indicator can be obtained, and the parameter values ​​of each main control parameter of that key indicator can be input into the created relational model for calculation to obtain the expected value of that key indicator of the developed oilfield.

[0031] It should be noted that, in this embodiment, for any key indicator, a relational sub-model corresponding to the key indicator can be constructed first based on the indicator value and the parameter values ​​of each main control parameter of the key indicator. Then, this embodiment can use the relational sub-models corresponding to each key indicator to calculate the expected values ​​of each key indicator for each developed oilfield.

[0032] Optionally, the relational model includes a relational sub-model corresponding to each key indicator, and among the multiple key indicators is a first key indicator. The master control parameter group corresponding to the first key indicator includes multiple first master control parameters. In this case, the creation process of the relational sub-model corresponding to the first key indicator includes: Obtain the index value of the first key indicator for each developed oilfield, as well as the parameter value of each first master control parameter for each developed oilfield; The first key indicator is used as the dependent variable, and each first master control parameter is used as the independent variable. Based on the actual values ​​of the first key indicator and the parameter values ​​of each first master control parameter of each developed oilfield, a multiple linear regression relationship between the dependent variable and each independent variable is established. The multiple linear regression relationship is used as the sub-model corresponding to the first key indicator.

[0033] The first key indicator can be any one of multiple key indicators. The first master control parameter is the master control parameter of the first key indicator.

[0034] Specifically, in this embodiment, when creating the relational sub-model corresponding to the first key indicator, the actual value of the first key indicator of each developed oilfield and the parameter value of each first main control parameter of each developed oilfield can be obtained first. Then, based on the multiple linear regression method, the actual value of the first key indicator of each developed oilfield and the parameter value of each first main control parameter of each developed oilfield, a multiple regression linear relationship between the first key indicator and the first main control parameter is constructed, and the constructed multiple regression linear relationship is determined as the relational sub-model corresponding to the first key indicator.

[0035] Optionally, the relational sub-model corresponding to the first key indicator is: ; in, R e The expected value of the primary key indicator; This represents the total number of the first master control parameters. For the first i The parameter value of the first master control parameter; For the first i The coefficient of the first master control parameter; C This is a constant term.

[0036] Following Example 1 above, this embodiment uses recovery rate as the first key indicator to introduce the process of creating the relational sub-model. See also Figure 2 The main controlling factors of oil recovery include effective thickness. Porosity Well-controlled reserves N Flow rate SPenetration rate K Oil-water viscosity ratio M and peak oil production rate v o The target type of oilfield includes 40 developed oilfields. The actual recovery rate and parameter values ​​of each main control parameter are obtained for each developed oilfield.

[0037] Using multiple linear regression and Figure 2 Based on the data shown, a multiple linear regression relationship is constructed between the recovery rate and various key control parameters. That is, the sub-model corresponding to the recovery rate is: .

[0038] Optionally, the parameter values ​​of each main control parameter of the developed oilfield are input into the created relational model for calculation to obtain the expected value of each key indicator of the developed oilfield, including: For any key indicator of an developed oilfield, the parameter values ​​of each main control parameter corresponding to the key indicator of the developed oilfield are input into the relational sub-model corresponding to the key indicator for calculation, so as to obtain the expected value of the key indicator of the developed oilfield.

[0039] Specifically, in this embodiment, when calculating the expected value of a key indicator of a developed oilfield, the parameter values ​​of each main control parameter of the key indicator of the developed oilfield can be obtained first, and then the obtained parameter values ​​of each main control parameter can be input into the relational sub-model corresponding to the key indicator for calculation to obtain the expected value of the key indicator of the developed oilfield.

[0040] Continuing with the example of evaluating oil recovery, let's assume that oilfield 41 in the target type of oilfield is a newly commissioned oilfield. The known values ​​of the main control parameters for the oil recovery of oilfield 41 include: effective thickness. The porosity is 16.5. 19.43, well-controlled reserves N 96.22, flow rate S The penetration rate is 243.05. K The oil-water viscosity ratio is 461.8. M The peak oil production rate is 22.73. v o The value is 6.8. In this embodiment, these parameter values ​​can be input into the relational sub-model corresponding to the recovery rate for calculation, yielding the expected recovery rate of oilfield 41. R e =50.87%.

[0041] S103. Based on the expected and actual values ​​of each key indicator of the developed oilfield, determine the relative deviation value of each key indicator.

[0042] Specifically, in this embodiment, for any key indicator of any developed oil field, the actual value of the key indicator of the developed oil field can be obtained, and the relative deviation value of the key indicator of the developed oil field can be calculated based on the actual value and the expected value of the key indicator of the developed oil field.

[0043] Optionally, step S103 includes: For any key indicator of an developed oilfield, the actual value of the key indicator is subtracted from the expected value of the indicator to obtain the corresponding difference. The ratio of the difference to the expected value of the indicator is determined as the relative deviation value of the key indicator of the developed oilfield.

[0044] Specifically, in this embodiment, for any key indicator of any developed oil field, the actual value of the key indicator of the developed oil field can be divided by the expected value of the key indicator of the developed oil field to obtain the corresponding difference. The ratio of the difference to the expected value of the indicator is determined as the relative deviation value of the key indicator of the developed oil field.

[0045] S104. Based on the weighting coefficient of each key indicator, the relative deviation values ​​of each key indicator in the developed oilfield are weighted and summed to obtain the comprehensive deviation value of the developed oilfield.

[0046] Specifically, this embodiment can assign weights to the aforementioned key indicators of the developed oilfield to obtain a weight coefficient for each key indicator. It should be noted that the weight coefficients of the key indicators can be set by technical personnel according to the actual situation; this embodiment does not impose such limitations.

[0047] Specifically, in this embodiment, for any developed oil field, the relative deviation values ​​of each key indicator are weighted and summed according to the weight coefficient of each key indicator to obtain the corresponding sum value as the comprehensive deviation value of the developed oil field.

[0048] S105. Based on the comprehensive deviation value of the developed oilfield and the set evaluation threshold, determine the development effect level of the developed oilfield.

[0049] The evaluation threshold can be set by technicians according to the actual situation, and this embodiment does not limit it.

[0050] Specifically, in this embodiment, for any developed oil field, the development effect level of the developed oil field can be determined based on the comprehensive deviation value of the developed oil field and the set evaluation threshold.

[0051] Optionally, the evaluation threshold includes an upper limit value greater than 0 and a lower limit value less than 0, where the absolute values ​​of the upper and lower limits are equal. In this case, step S105 includes: If the comprehensive deviation value of the developed oilfield is greater than the upper limit value, the development effect level of the developed oilfield is determined to be Level 1; If the comprehensive deviation value of a developed oilfield is greater than or equal to the lower limit and less than or equal to the upper limit, then the development effect level of the developed oilfield is determined to be Level II. If the comprehensive deviation value of the developed oilfield is less than the lower limit, the development effect level of the developed oilfield is determined to be Level III.

[0052] It is understandable that Level 1 development is more effective than Level 2 development, and Level 2 development is more effective than Level 3 development.

[0053] It should be noted that this embodiment determines the development effect level of the developed oilfield by comparing the comprehensive deviation value of the developed oilfield with the evaluation threshold. This can evaluate the development effect of the developed oilfield under the current geological reservoir conditions. Specifically: if the development effect level of the developed oilfield is level two, it indicates that the development plan is very successful, the underground understanding is clear, the process technology is effective, and the actual production fully meets expectations; if the development effect level of the developed oilfield is level one, it indicates that the actual effect is better than the plan prediction, indicating that the geological reserves are richer than known, the oil displacement efficiency is higher, or more efficient new technologies have been adopted; if the development effect level of the developed oilfield is level three, it indicates that the development effect has not reached the design level of the plan, and the reasons need to be analyzed in depth to guide researchers to study and formulate corresponding improvement measures.

[0054] The offshore oilfield development effectiveness grading method proposed in this embodiment identifies multiple key indicators for evaluating the development effectiveness of target type oilfields, and a set of master control parameters corresponding to each key indicator. Each master control parameter set includes at least one master control parameter. For any developed oilfield of the target type, the parameter values ​​of each master control parameter of the developed oilfield are input into a created relational model for calculation to obtain the expected value of each key indicator of the developed oilfield. Based on the expected and actual values ​​of each key indicator of the developed oilfield, the relative deviation value of each key indicator is determined. According to the weighting coefficient of each key indicator, the relative deviation values ​​of each key indicator of the developed oilfield are weighted and summed to obtain the comprehensive deviation value of the developed oilfield. Based on the comprehensive deviation value of the developed oilfield and a set evaluation threshold, the development effectiveness level of the developed oilfield is determined. This embodiment can perform quantitative calculations based on oilfield production-related data, and evaluate the development effect level of each developed oilfield in the target type of oilfield according to the quantitative calculation results, effectively realizing the objective evaluation of the development effect level of developed oilfields and improving the accuracy of the evaluation of the development effect of developed oilfields.

[0055] based on Figure 1In the second method for classifying the development effect of offshore oilfields proposed in this embodiment, the development effect level of developed oilfields can be evaluated based on only a single key indicator.

[0056] Continuing with the example of oil recovery rate, this embodiment can calculate the following using the constructed relational sub-model corresponding to the oil recovery rate: Figure 2 The expected recovery rates of oilfields 1 to 40 were calculated, and the relative deviations of the recovery rates for oilfields 1 to 40 were determined based on both the expected and actual recovery rates. Rel Set an upper limit for the threshold of the competence assessment. C u and the lower limit of the threshold for evaluating the ability to meet standards C d , C u Greater than 0, C d The values ​​are less than 0, and their absolute values ​​are equal. This embodiment can classify the key performance indicators of developed oilfields according to the following rules: .

[0057] Specifically, in this embodiment, the calculation results of the relative deviation values ​​of the recovery rate and the evaluation results of the compliance level for oilfields 1 to 40 can be as follows: Figure 3 As shown.

[0058] like Figure 4 As shown, this embodiment can classify the key indicator compliance level of each developed oilfield based on the expected and actual recovery rates, generating a quantitative evaluation grading chart for offshore oilfield development level, i.e., a quantitative evaluation grading chart for offshore oilfield development effectiveness. Figure 4 The actual value of the indicator is the actual value of the recovery rate, and the expected value of the indicator is the expected value of the recovery rate. Figure 4 The x-axis of the point corresponding to the actual value in the graph represents the expected recovery rate of the developed oilfield, and the y-axis represents the actual recovery rate of the developed oilfield. This embodiment can plot the corresponding points based on the expected and actual recovery rates of each developed oilfield. Figure 4 The red dashed line represents the case where the relative deviation of the recovery rate is assumed to be 0, and the purple dashed line represents the case where the relative deviation of the recovery rate is assumed to be equal to... The blue dashed line represents the assumed relative deviation of the recovery rate. The coordinates are drawn as follows: When the relative deviation of the recovery rate of the developed oilfield is equal to 0, its corresponding coordinate point is located on the red dashed line; when the relative deviation of the recovery rate of the developed oilfield is greater than 0, its corresponding coordinate point is located on the red dashed line. At that time, its corresponding coordinate point is located above the purple dashed line; when the relative deviation of the recovery rate of the developed oilfield is greater than or equal to and less than or equal to When the corresponding coordinate point is located between the purple and blue dashed lines; when the relative deviation of the recovery rate of the developed oilfield is less than At that time, its corresponding coordinate point is located below the blue dashed line.

[0059] like Figure 5 As shown in the example, this embodiment also uses a grading standard for the development effect of offshore medium-to-high permeability water-driven sandstone reservoirs to classify and evaluate the development level of each oilfield, i.e., the development effect, and classify them into Category 1, Category 2, and Category 3. The classification results are then compared with... Figure 4 The grading results are combined to form a quantitative evaluation grading and classification chart of offshore oilfield development effects. Figure 5 The two solid blue lines are used to distinguish different development effects. If the coordinate point corresponding to the developed oil field is located between the two solid blue lines, it means that the development effect of the developed oil field is Class 2. If the coordinate point corresponding to the developed oil field is located below the first solid blue line, it means that the development effect of the developed oil field is Class 3. If the coordinate point corresponding to the developed oil field is located above the second solid blue line, it means that the development effect of the developed oil field is Class 1.

[0060] It should be noted that several evaluation methods exist for assessing the development level and effectiveness of offshore oilfields, including: state comparison evaluation, recoverable reserves evaluation, system dynamic analysis, fuzzy comprehensive evaluation, grey theory evaluation, analogy, and numerical simulation evaluation. However, the methods for calculating the weights of hierarchical and categorized indicators in the comprehensive evaluation of the development effectiveness of these technologies lack objectivity. This embodiment derives the quantitative characterization relationship between different dynamic and static main control factors and key development indicators in offshore oilfields, establishing a quantitative evaluation method for offshore oilfield development level based on main control factors. This forms a quantitative evaluation system for development level, laying the foundation for the scientific analysis of offshore oilfield development level.

[0061] The offshore oilfield development effect classification method proposed in this embodiment addresses the problem that related technologies are difficult to use to accurately evaluate the development level of offshore oilfields. By deriving the quantitative characterization relationship between different dynamic and static main control factors and key development indicators of offshore oilfields, a development level classification judgment chart is formed. This method can realize the determination of the development level based on given dynamic and static parameters of the oilfield, laying the foundation for oilfield optimization and improvement of development effect.

[0062] like Figure 6 As shown in the figure, this embodiment proposes a device for grading the development effect of offshore oil fields. The device may include: The first determining unit 601 is used to determine multiple key indicators for evaluating the development effect of target type oilfields, as well as the main control parameter group corresponding to each key indicator. Each main control parameter group corresponding to the key indicator includes at least one main control parameter. The calculation unit 602 is used to input the parameter values ​​of each main control parameter of any developed oil field in the target type oil field into the created relational model for calculation, so as to obtain the expected value of each key indicator of the developed oil field. The second determining unit 603 is used to determine the relative deviation value of each key indicator of the developed oilfield based on the expected value and actual value of each key indicator. Weighting unit 604 is used to perform weighted summation of the relative deviation values ​​of each key indicator of the developed oilfield according to the weight coefficient of each key indicator, so as to obtain the comprehensive deviation value of the developed oilfield. The third determining unit 605 is used to determine the development effect level of the developed oilfield based on the comprehensive deviation value of the developed oilfield and the set evaluation threshold.

[0063] It should be noted that the processing procedures and beneficial effects of the first determining unit 601, the calculation unit 602, the second determining unit 603, the weighting unit 604, and the third determining unit 605 can be referred to respectively. Figure 1 Steps S101 to S105 are not described in detail here.

[0064] Optionally, the relational model includes a relational sub-model corresponding to each key indicator, and among multiple key indicators is a first key indicator. The master control parameter group corresponding to the first key indicator includes multiple first master control parameters. The creation process of the relational sub-model corresponding to the first key indicator is set as follows: Obtain the index value of the first key indicator for each developed oilfield, as well as the parameter value of each first master control parameter for each developed oilfield; The first key indicator is used as the dependent variable, and each first master control parameter is used as the independent variable. Based on the actual values ​​of the first key indicator and the parameter values ​​of each first master control parameter of each developed oilfield, a multiple linear regression relationship between the dependent variable and each independent variable is established. The multiple linear regression relationship is used as the sub-model corresponding to the first key indicator.

[0065] Optionally, the computing unit 602 is also used for: For any key indicator of an developed oilfield, the parameter values ​​of each main control parameter corresponding to the key indicator of the developed oilfield are input into the relational sub-model corresponding to the key indicator for calculation, so as to obtain the expected value of the key indicator of the developed oilfield.

[0066] Optionally, the second determining unit 603 is also used for: For any key indicator of an developed oilfield, the actual value of the key indicator is subtracted from the expected value of the indicator to obtain the corresponding difference. The ratio of the difference to the expected value of the indicator is determined as the relative deviation value of the key indicator of the developed oilfield.

[0067] Optionally, the evaluation threshold includes an upper limit value greater than 0 and a lower limit value less than 0, and the absolute values ​​of the upper limit value and the lower limit value are equal; The third determining unit 605 is also used for: If the comprehensive deviation value of the developed oilfield is greater than the upper limit value, the development effect level of the developed oilfield is determined to be Level 1; If the comprehensive deviation value of a developed oilfield is greater than or equal to the lower limit and less than or equal to the upper limit, then the development effect level of the developed oilfield is determined to be Level II. If the comprehensive deviation value of the developed oilfield is less than the lower limit, the development effect level of the developed oilfield is determined to be Level III.

[0068] Optionally, the relational sub-model corresponding to the first key indicator is: ; in, R e The expected value of the primary key indicator; This represents the total number of the first master control parameters. For the first i The parameter value of the first master control parameter; For the first i The coefficient of the first master control parameter; C This is a constant term.

[0069] Optional target types of oilfields include marine sandstone, conventional heavy oil deltaic facies, conventional heavy oil fluvial facies, and integrated medium-low viscosity or complex fault blocks. The key indicators include at least two of the following: water drive reserve control level, water drive reserve utilization level, pressure maintenance level, water cut increase rate, overall decline rate per unit oil production rate, recovery rate, end-of-stage recovery rate, water injection quality compliance rate, water injection well distribution rate, distribution layer qualification rate, and overall oil and water well utilization rate.

[0070] The offshore oilfield development effect grading device proposed in this embodiment identifies multiple key indicators for evaluating the development effect of target type oilfields, and a set of master control parameters corresponding to each key indicator. Each master control parameter set includes at least one master control parameter. For any developed oilfield of the target type, the parameter values ​​of each master control parameter of the developed oilfield are input into a created relational model for calculation to obtain the expected value of each key indicator of the developed oilfield. Based on the expected and actual values ​​of each key indicator of the developed oilfield, the relative deviation value of each key indicator is determined. According to the weighting coefficient of each key indicator, the relative deviation values ​​of each key indicator of the developed oilfield are weighted and summed to obtain the comprehensive deviation value of the developed oilfield. Based on the comprehensive deviation value of the developed oilfield and a set evaluation threshold, the development effect level of the developed oilfield is determined. This embodiment can perform quantitative calculations based on oilfield production-related data, and evaluate the development effect level of each developed oilfield in the target type of oilfield according to the quantitative calculation results, effectively realizing the objective evaluation of the development effect level of developed oilfields and improving the accuracy of the evaluation of the development effect of developed oilfields.

[0071] In this embodiment, the offshore oilfield development effect grading device is presented in the form of functional units. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0072] This invention also provides a computer device having the above-described features. Figure 6 The device shown is a grading device for the development effect of offshore oil fields.

[0073] Please see Figure 7 The present invention provides a schematic diagram of the structure of a computer device according to an optional embodiment. The computer device includes one or more processors 10, a memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are interconnected via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, multiple processors and / or multiple buses can be used with multiple memories, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 7Take a processor 10 as an example.

[0074] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0075] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0076] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function. The data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, which can be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0077] Memory 20 may include volatile memory, such as random access memory. Memory may also include non-volatile memory, such as flash memory, hard disk, or solid-state drive. Memory 20 may also include combinations of the above types of memory.

[0078] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0079] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0080] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for classifying the development effect of offshore oilfields, characterized in that, include: Multiple key indicators for evaluating the development effect of target type oilfields are identified, as well as a set of master control parameters corresponding to each key indicator, wherein each set of master control parameters corresponding to the key indicator includes at least one master control parameter. For any developed oilfield in the target type of oilfield, the parameter value of each of the main control parameters of the developed oilfield is input into the created relational model for calculation to obtain the expected value of each of the key indicators of the developed oilfield. Based on the expected and actual values ​​of each key indicator of the developed oilfield, determine the relative deviation value of each key indicator of the developed oilfield. Based on the weighting coefficient of each key indicator, the relative deviation values ​​of each key indicator of the developed oilfield are weighted and summed to obtain the comprehensive deviation value of the developed oilfield. Based on the comprehensive deviation value of the developed oilfield and the set evaluation threshold, the development effect level of the developed oilfield is determined.

2. The method according to claim 1, characterized in that, The relational model includes a relational sub-model corresponding to each key indicator, and the multiple key indicators include a first key indicator. The master control parameter group corresponding to the first key indicator includes multiple first master control parameters. The process of creating the relational sub-model corresponding to the first key indicator includes: Obtain the index value of the first key indicator for each of the developed oil fields, and the parameter value of each of the first master control parameters for each of the developed oil fields; Using the first key indicator as the dependent variable and each of the first master control parameters as the independent variable, a multiple linear regression relationship between the dependent variable and each of the independent variables is established based on the actual values ​​of the first key indicator of each developed oilfield and the parameter values ​​of each of the first master control parameters of each developed oilfield. The multiple linear regression equation is used as the sub-model corresponding to the first key indicator.

3. The method according to claim 2, characterized in that, The step of inputting the parameter values ​​of each of the main control parameters of the developed oilfield into the created relational model for calculation to obtain the expected value of each of the key indicators of the developed oilfield includes: For any of the key indicators of the developed oilfield, the parameter value of each of the main control parameters corresponding to the key indicator of the developed oilfield is input into the relational sub-model corresponding to the key indicator for calculation to obtain the expected value of the key indicator of the developed oilfield.

4. The method according to claim 1, characterized in that, The step of determining the relative deviation value of each key indicator of the developed oilfield based on the expected value and actual value of each key indicator includes: For any of the key indicators of the developed oilfield, the actual value of the key indicator of the developed oilfield is subtracted from the expected value of the indicator to obtain the corresponding difference. The ratio of the difference to the expected value of the indicator is determined as the relative deviation value of the key indicator of the developed oilfield.

5. The method according to claim 1, characterized in that, The evaluation threshold includes an upper limit value greater than 0 and a lower limit value less than 0, and the absolute values ​​of the upper limit value and the lower limit value are equal. The determination of the development effectiveness level of the developed oilfield based on the comprehensive deviation value and the set evaluation threshold includes: If the comprehensive deviation value of the developed oilfield is greater than the upper limit value, then the development effect level of the developed oilfield is determined to be Level 1; If the comprehensive deviation value of the developed oilfield is greater than or equal to the lower limit value and less than or equal to the upper limit value, then the development effect level of the developed oilfield is determined to be Level II. If the comprehensive deviation value of the developed oilfield is less than the lower limit value, then the development effect level of the developed oilfield is determined to be level three.

6. The method according to claim 2, characterized in that, The relational sub-model corresponding to the first key indicator is: ； in, R e This is the expected value of the first key indicator; The total number of the first master control parameters. For the first i The parameter values ​​of the first master control parameter; For the first i The coefficients of the first master control parameter; C This is a constant term.

7. The method according to any one of claims 1 to 6, characterized in that, The target type of oilfield is marine sandstone, conventional heavy oil deltaic facies, conventional heavy oil fluvial facies, and integrated medium-low viscosity or complex fault blocks. The key indicators include at least two of the following: water drive reserve control level, water drive reserve utilization level, pressure maintenance level, water cut increase rate, comprehensive decline rate of unit oil production rate, recovery rate, end-stage recovery rate, water injection quality compliance rate, water injection well distribution rate, distribution layer qualification rate, and comprehensive oil and water well operating rate.

8. A method for classifying the development effect of offshore oilfields, characterized in that, include: The first determining unit is used to determine multiple key indicators for evaluating the development effect of target type oilfields, and a main control parameter group corresponding to each key indicator, wherein each main control parameter group corresponding to the key indicator includes at least one main control parameter. The calculation unit is used to input the parameter values ​​of each of the main control parameters of any developed oilfield in the target type oilfield into the created relational model for calculation, so as to obtain the expected value of each of the key indicators of the developed oilfield. The second determining unit is used to determine the relative deviation value of each key indicator of the developed oilfield based on the expected value and actual value of each key indicator of the developed oilfield. The weighting unit is used to perform a weighted summation of the relative deviation values ​​of each of the key indicators of the developed oilfield according to the weight coefficient of each key indicator, so as to obtain the comprehensive deviation value of the developed oilfield. The third determining unit is used to determine the development effect level of the developed oilfield based on the comprehensive deviation value of the developed oilfield and the set evaluation threshold.

9. A computer device, characterized in that, include: A memory and a processor are interconnected, the memory stores computer instructions, and the processor executes the offshore oilfield development effect grading method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the offshore oilfield development effect grading method according to any one of claims 1 to 7.

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