CN118057390A - Method, device, equipment and medium for determining numerical simulation fitting precision of oil reservoir - Google Patents
Method, device, equipment and medium for determining numerical simulation fitting precision of oil reservoir Download PDFInfo
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Abstract
The application discloses a method, a device, equipment and a medium for determining numerical simulation fitting precision of an oil reservoir. The method comprises the steps of determining predicted values of at least two times of oil reservoir parameters and corresponding actual values; according to the predicted value and the actual value, determining a predicted error value corresponding to the oil reservoir parameter at each time as an actual relative error of the oil reservoir parameter; predicting the error trend of the oil reservoir parameters according to each actual relative error, and determining the trend relative error of the oil reservoir parameters; and determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error. According to the technical scheme, the influence of the actual relative errors and the trend relative errors corresponding to each historical time of the oil reservoir parameters on the oil reservoir numerical simulation fitting precision is considered, the accuracy of the oil reservoir numerical simulation fitting precision is improved, and a basis is provided for the adjustment of a subsequent oil reservoir numerical simulation model.
Description
Technical Field
The application relates to the technical field of oil reservoir development engineering, in particular to a method, a device, equipment and a medium for determining oil reservoir numerical simulation fitting precision.
Background
The numerical reservoir simulation refers to solving a mathematical model of the oil reservoir by using a computer, simulating underground oil-water flow, and giving out oil-water distribution at a certain moment so as to predict the oil reservoir dynamics. The higher the fitting accuracy of the reservoir numerical simulation, the more reliable the reservoir mathematical model is represented and the higher the accuracy of the predictions. At present, the accuracy of the reservoir numerical simulation fit is generally characterized by using a single well fitting rate or fitting error.
The single well fitting rate is generally quantitatively calculated by using an observation method, an error square sum method, a history fitting quality index method or a ratio of the number of time periods of "fitting up" to the total number of time periods. However, the method only considers the difference between the predicted value and the actual value and the influence factor of the difference between the predicted value and the actual value on the fitting precision in different time periods, and cannot accurately and comprehensively quantitatively evaluate the fitting precision, so that the reliability of the oil reservoir mathematical model is reduced.
Therefore, how to provide a technical scheme capable of accurately, comprehensively and quantitatively evaluating the numerical simulation fitting accuracy of the oil reservoir is a technical problem to be solved urgently by those skilled in the art.
Disclosure of Invention
The application provides a method, a device, equipment and a medium for determining the numerical simulation fitting precision of an oil reservoir, which take the influence of actual relative errors and trend relative errors corresponding to each historical time of oil reservoir parameters on the numerical simulation fitting precision of the oil reservoir into consideration, improve the accuracy of the numerical simulation fitting precision of the oil reservoir and provide a basis for the adjustment of a follow-up numerical simulation model of the oil reservoir.
According to an aspect of the application, there is provided a method for determining the accuracy of a numerical simulation fit of a reservoir, the method comprising:
determining predicted values and corresponding actual values of at least two times of oil reservoir parameters;
According to the predicted value and the actual value, determining a predicted error value of the oil reservoir parameter corresponding to each time as an actual relative error of the oil reservoir parameter;
predicting the error trend of the oil reservoir parameter according to each actual relative error, and determining the trend relative error of the oil reservoir parameter;
And determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error.
According to another aspect of the present application, there is provided a device for determining accuracy of fitting of numerical simulations of a reservoir, the device comprising:
the oil reservoir parameter value determining module is used for determining predicted values and corresponding actual values of at least two times of oil reservoir parameters;
The actual relative error determining module is used for determining a predicted error value of the oil reservoir parameter corresponding to each time according to the predicted value and the actual value, and taking the predicted error value as an actual relative error of the oil reservoir parameter;
The trend relative error determining module is used for predicting the error trend of the oil reservoir parameter according to each actual relative error and determining the trend relative error of the oil reservoir parameter;
and the fitting precision determining module is used for determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error.
According to another aspect of the present application, there is provided an apparatus for determining accuracy of a numerical simulation fit of a reservoir, the apparatus comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of determining the accuracy of a reservoir numerical simulation fit as described in any of the embodiments of the present application.
According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for causing a processor to execute a method for determining the accuracy of a reservoir numerical simulation fit according to any of the embodiments of the present application.
According to the technical scheme provided by the application, the predicted value and the corresponding actual value of at least two times of oil reservoir parameters are determined; according to the predicted value and the actual value, determining a predicted error value corresponding to the oil reservoir parameter at each time as an actual relative error of the oil reservoir parameter; predicting the error trend of the oil reservoir parameters according to each actual relative error, and determining the trend relative error of the oil reservoir parameters; and determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error. According to the technical scheme, the influence of the actual relative errors and the trend relative errors corresponding to each historical time of the oil reservoir parameters on the oil reservoir numerical simulation fitting precision is considered, the accuracy of the oil reservoir numerical simulation fitting precision is improved, and a basis is provided for the adjustment of a subsequent oil reservoir numerical simulation model.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the application or to delineate the scope of the application. Other features of the present application will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for determining the accuracy of a numerical reservoir simulation fit according to an embodiment of the present application;
FIG. 2 is a flowchart of a method for determining the accuracy of a numerical reservoir simulation fit according to a second embodiment of the present application;
FIG. 3 is a schematic diagram of a fitted result of a bottom hole flow pressure provided by an embodiment of the present invention;
FIG. 4 is a schematic diagram of a calculation result of a weight coefficient of each actual relative error according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a fitting result of each actual relative error provided in an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of a device for determining the fitting accuracy of numerical simulation of oil reservoirs according to a third embodiment of the present application;
fig. 7 is a schematic structural diagram of an apparatus for implementing a method for determining accuracy of fitting numerical reservoir simulation according to an embodiment of the present application.
Detailed Description
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of a method for determining a fitting accuracy of a numerical reservoir simulation, which is provided in an embodiment of the present application, and the embodiment may be suitable for a case where a mathematical model of a reservoir simulates parameters of a reservoir, where the method may be performed by a device for determining a fitting accuracy of a numerical reservoir simulation, and the device for determining a fitting accuracy of a numerical reservoir simulation may be implemented in a form of hardware and/or software, and the device for determining a fitting accuracy of a numerical reservoir simulation may be configured in a device having data processing capability. As shown in fig. 1, the method includes:
S110, determining predicted values and corresponding actual values of at least two times of oil reservoir parameters.
The reservoir parameters may be parameters solved by a reservoir numerical simulation model, for example, may be bottom hole flow pressure, water saturation, gas saturation, and the like. The oil reservoir numerical simulation model can be a black oil model, a component model or a thermal model and the like which are established according to key parameters of the current oil reservoir type, wherein the key parameters can comprise dynamic parameters and static parameters of the oil reservoir and a single well, such as permeability, porosity, phase permeability data, geometric form and the like.
The predicted value may be a value obtained by predicting the oil reservoir parameter at different times according to the oil reservoir numerical simulation model, and the actual value may be a measured value obtained by actually observing at different times.
In the embodiment of the invention, at least two times can be determined according to the production process of the oil reservoir and the single well, the predicted value of the oil reservoir parameter at the at least two times can be determined according to the current oil reservoir numerical simulation model, and the actual value corresponding to the predicted value can be obtained according to actual measurement.
And S120, determining a predicted error value of the oil reservoir parameter corresponding to each time according to the predicted value and the actual value, and taking the predicted error value as an actual relative error of the oil reservoir parameter.
The actual relative error of the oil reservoir parameters can be the prediction deviation of the oil reservoir numerical simulation model at each time.
In the embodiment of the invention, the difference value between the predicted value and the actual value can be used as the actual relative error of the oil reservoir parameter; the square of the difference between the predicted value and the actual value can be used as the actual relative error of the oil reservoir parameter to represent the absolute deviation degree of the predicted value and the actual value; the ratio of the difference between the predicted value and the actual value to the actual value can also be used as the actual relative error of the reservoir parameters. Of course, the embodiment of the invention is not limited thereto, and the deviation degree between the predicted value and the actual value can be determined according to the actual requirement.
S130, predicting the error trend of the oil reservoir parameter according to each actual relative error, and determining the trend relative error of the oil reservoir parameter.
The trend relative error can be the trend change degree of the fitting effect of the numerical simulation model of the oil reservoir. Specifically, as time increases, if the difference between the predicted value and the actual value is smaller, the fitting effect is better; if the difference between the predicted value and the actual value is larger, the fitting effect is poorer.
In the embodiment of the invention, the error trend of the oil reservoir parameter can be predicted by calculating the growth rate of the actual relative error corresponding to each time, and the error trend is used as the trend relative error of the oil reservoir parameter. The error trend of the oil reservoir parameter can be predicted by calculating a trend curve of the actual relative error corresponding to each time, and the relative error corresponding to the predicted time is calculated according to the trend curve and is used as the trend relative error of the oil reservoir parameter. Of course, the embodiment of the invention is not limited to this, and the determination mode of the trend relative error can be determined according to actual needs.
As an alternative but non-limiting implementation, predicting the error value of the reservoir parameter according to the actual relative error, and determining the trend relative error of the reservoir parameter may include, but is not limited to, the following processes of steps A1 to A2:
and A1, fitting the actual relative errors corresponding to the time to obtain a fitting result.
The fitting method for the actual relative error corresponding to each time may be fitting by using a least square method formula, or fitting by using a built-in function in MATLAB or a curve fitting tool box. The fitting result can be a fitting formula or a fitting curve obtained according to the fitting mode.
In the embodiment of the invention, a fitting curve formula of the actual relative error is determined by utilizing a least square method formula according to the actual relative error corresponding to each time.
And A2, determining a predicted error value corresponding to the oil reservoir parameter at the predicted time according to the fitting result, and taking the predicted error value as a trend relative error of the oil reservoir parameter.
Wherein the predicted time may be the next time to be predicted. For example, if each historical time is 2016, 2017, 2019, 2020, 2021, and 2021, respectively, then the predicted time may be 2023 and 3.
In the embodiment of the invention, a fitting formula of the actual relative error and time obtained by fitting according to the actual relative error corresponding to each time can be used for substituting the predicted time into the fitting formula to obtain a predicted error value of the oil reservoir parameter corresponding to the predicted time, and the predicted error value is used as the trend relative error of the oil reservoir parameter.
This has the advantage that the trend of the actual relative error corresponding to the historic time can be accurately predicted.
And S140, determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error.
The fitting precision can be the predicted deviation degree of the oil reservoir numerical simulation model to the oil reservoir parameters. The higher the fitting precision is, the worse the effect of the numerical reservoir simulation is indicated; the lower the fitting accuracy, the better the effect of reservoir numerical simulation is indicated.
In the embodiment of the invention, the sum of the actual relative errors and the trend relative errors can be used as the fitting precision of the oil reservoir parameters; the average value of the actual relative errors and the sum of the trend relative errors can be used as the fitting precision of the oil reservoir parameters; and the value obtained by weighting and summing each actual relative error and each trend relative error can be used as the fitting precision of the oil reservoir parameters. Of course, the embodiment of the invention is not limited to this, and the determination mode of the fitting precision can be determined according to actual needs.
As an alternative but non-limiting implementation, determining the fitting accuracy of the reservoir parameters according to the actual relative error and the trend relative error may include, but is not limited to, the process of steps B1 to B2:
And B1, determining the weight coefficient of the actual relative error according to the preset weight coefficient of the trend relative error so that the sum of the preset weight coefficient of the trend relative error and the weight coefficient of the actual relative error is 1.
The preset weight coefficient of the trend relative error can be determined according to working experience or actual needs.
In order to make the sum of the preset weight coefficient of the trend relative error and the weight coefficient of the actual relative error be 1, the total weight coefficient of the actual relative error may be a total weight value obtained by subtracting the preset weight coefficient of the trend relative error from 1. The weight coefficient of each actual relative error can be obtained by averaging the total weight value according to the number of each actual relative error, can be determined according to the distance between the time intervals corresponding to each actual relative error and the prediction time, and can be determined according to actual needs. Of course, the determination manner of the weight coefficient of each actual relative error in the embodiment of the present invention is not limited.
Optionally, determining the weight coefficient of the actual relative error according to the preset weight coefficient of the trend relative error includes:
Calculating the weight coefficient of the actual relative error according to the following formula:
wherein j represents the current time, k represents the total time quantity, f j represents the weight coefficient of the actual relative error of the oil reservoir parameter at the jth time, and ω represents the preset weight coefficient of the trend relative error.
It can be understood that the closer the current time of the time interval corresponding to the actual relative error is, the larger the influence on the current fitting result is, the larger the weight coefficient occupied by the current time of the time interval corresponding to the actual relative error is, the smaller the influence on the current fitting result is, and the smaller the weight coefficient occupied by the current fitting result is.
The advantage of this arrangement is that the forgetting effect of time can be taken into account, and the accuracy of the determination of the fitting accuracy is improved.
And B2, determining the fitting precision of the oil reservoir parameters according to the trend relative error, a preset weight coefficient of the trend relative error, the actual relative error and a weight coefficient of the actual relative error.
In the embodiment of the invention, the trend relative error and each actual relative error can be summed according to the weight ratio to obtain the fitting precision of the oil reservoir parameters.
Optionally, determining the fitting accuracy of the reservoir parameter according to the trend relative error, the preset weight coefficient of the trend relative error, the actual relative error and the weight coefficient of the actual relative error may include, but is not limited to, the following processes of steps C1 to C3:
And C1, taking the product of the trend relative error and a preset weight coefficient of the trend relative error as a first error value.
And C2, taking the sum of products of the actual relative error and the weight coefficient of the actual relative error corresponding to each time as a second error value.
And C3, taking the sum of the first error value and the second error value as the fitting precision of the oil reservoir parameters.
The method has the advantages that the trend relative errors and the actual relative errors can be determined according to the influence degree on the fitting precision, the fitting precision is quantized, and the accuracy of the fitting precision is further improved.
The embodiment of the invention provides a method for determining the fitting precision of numerical simulation of an oil reservoir, which comprises the steps of determining predicted values and corresponding actual values of at least two times of oil reservoir parameters; according to the predicted value and the actual value, determining a predicted error value corresponding to the oil reservoir parameter at each time as an actual relative error of the oil reservoir parameter; predicting the error trend of the oil reservoir parameters according to each actual relative error, and determining the trend relative error of the oil reservoir parameters; and determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error. According to the technical scheme, the influence of the actual relative errors and the trend relative errors corresponding to each historical time of the oil reservoir parameters on the oil reservoir numerical simulation fitting precision is considered, the accuracy of the oil reservoir numerical simulation fitting precision is improved, and a basis is provided for the adjustment of a subsequent oil reservoir numerical simulation model.
Example two
Fig. 2 is a flowchart of a method for determining the accuracy of fitting numerical simulation of oil reservoirs according to a second embodiment of the present application, where the method is optimized based on the foregoing embodiment. As shown in fig. 2, the method of this embodiment specifically includes the following steps:
s210, determining predicted values and corresponding actual values of at least two times of oil reservoir parameters.
S220, grouping the predicted values and the actual values according to the time corresponding to the predicted values and the actual values and the preset time length to obtain at least two groups of predicted values and actual values.
The preset time length can be determined according to a preset standard. The preset standard may be the development stage of the oil reservoir and the single well, or a fixed time period, etc. For example, when the water content is simulated, each time period may be divided into a low water content period, a medium water content period, and a high water content period according to the development stages of the oil reservoir and the individual wells. Of course, the mode of dividing the predicted value and the actual value in the embodiment of the present invention is not limited.
S230, for each set of predicted values and actual values, determining the difference value between each set of predicted values and actual values.
The difference between each set of predicted values and the actual values can be determined by the following formula:
Yri＝Ymri-Yori；
Where r represents the r-th time period, i represents the current number of measurements of the reservoir parameter in the current time period, Y mri represents the predicted value of the i-th simulation of the reservoir parameter in the r-th time period, and Y ori represents the actual value of the i-th measurement of the reservoir parameter in the r-th time period.
S240, determining the actual relative errors corresponding to the predicted values and the actual values of each group according to the difference value between the predicted values and the actual values of each group and each actual value.
In the embodiment of the invention, the difference between each set of predicted values and actual values and the ratio of the sum of the actual values in each set can be used as the actual relative error of each set.
Optionally, determining the actual relative error corresponding to each set of predicted values and actual values according to the difference between each set of predicted values and actual values and each actual value may include, but is not limited to, the following steps D1 to D3:
And D1, taking the sum of the differences between each group of predicted values and the actual values as a first parameter.
Wherein the first parameter may be determined by the following formula:
Where r represents an r-th time period, Y r represents a first parameter of the r-th time period, i represents a current number of measurements of the reservoir parameter in the current time period, n represents a total number of observations of the reservoir parameter in the r-th time period, Y mri represents a predicted value of an i-th simulation of the reservoir parameter in the r-th time period, and Y ori represents an actual value of an i-th measurement of the reservoir parameter in the r-th time period.
And D2, taking the sum of the actual values as a second parameter.
Wherein the second parameter may be determined by the following formula:
wherein Y or represents the second parameter for the r-th time period.
And D3, taking the ratio of the first parameter to the second parameter as actual relative errors corresponding to each group of predicted values and actual values.
Wherein, each group of predicted values and the actual relative error corresponding to the actual values can be determined by the following formula:
Where Δη r represents the actual relative error of the reservoir parameters over the r-th time period.
This has the advantage that each set of predicted values and the actual relative error corresponding to the actual value can be accurately quantified.
S250, predicting the error trend of the oil reservoir parameter according to each actual relative error, and determining the trend relative error of the oil reservoir parameter.
And S260, determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error.
The fitting accuracy of the reservoir parameters can be determined by the following formula:
Wherein Δη represents the fitting accuracy of the reservoir parameters, r represents the r-th time period, s represents the classification number of the time periods, f r represents the weight coefficient of the actual relative error of the reservoir parameters at the j-th time period, μ represents the preset weight coefficient of the trend relative error, Δη r represents the actual relative error of the reservoir parameters in the r-th time period, and Δη p represents the trend relative error.
The embodiment of the invention provides a method for determining the fitting precision of numerical simulation of an oil reservoir, which comprises the steps of determining predicted values and corresponding actual values of at least two times of oil reservoir parameters; grouping the predicted values and the actual values according to the time corresponding to the predicted values and the actual values and the preset time length to obtain at least two groups of predicted values and actual values; for each set of predicted values and actual values, determining differences between each set of predicted values and actual values; according to the difference value between each group of predicted values and the actual values and each actual value, determining the actual relative error corresponding to each group of predicted values and the actual values; predicting the error trend of the oil reservoir parameters according to each actual relative error, and determining the trend relative error of the oil reservoir parameters; and determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error. According to the technical scheme, each historical time is segmented, so that the actual relative errors of different stages are determined, and the accuracy of the numerical simulation fitting precision of the oil reservoir is further improved.
Illustratively, the bottom hole flow pressure fitting of an oilfield oil well W-1 is explained.
In the first step, in order to quantitatively evaluate the fitting effect of the bottom hole flow pressure of the oil field oil production well W-1, the fitting time is divided into 12 time windows, and the predicted value and the actual value of the bottom hole flow pressure corresponding to each time in each time window are determined.
FIG. 3 is a schematic diagram of a result of fitting the bottom hole flow pressure according to an embodiment of the present invention. As shown in fig. 3, the predicted value and the actual value of the bottom hole pressure Y of the oil field oil well W-1 at each time t are shown.
And secondly, setting the weight coefficient of the trend relative error to be 0.4, and calculating the weight coefficient of each actual relative error through the following formula.
Where a represents the current time and g a represents the weight coefficient of the actual relative error of the reservoir parameter at the jth time.
Fig. 4 is a schematic diagram of a weight coefficient calculation result of each actual relative error according to an embodiment of the present invention. As shown in fig. 4, the weight coefficient of each actual relative error increases with the time window order.
And thirdly, fitting each actual relative error, and determining a predicted error value corresponding to the bottom hole flow pressure in a predicted time window according to the fitting result to serve as a trend relative error of the bottom hole flow pressure.
Fig. 5 is a schematic diagram of a fitting result of each actual relative error according to an embodiment of the present invention. As shown in fig. 5, the fitting result of each actual relative error is obtained as y=0.4019x+4.0825, where y represents the actual relative error and x represents the time window. The correlation coefficient of the fitting result of the actual relative error R 2 =0.2133. Substituting the prediction window x=14 into the function of the fitting result gives a trend relative error of 9%.
And fourthly, determining the fitting accuracy of the bottom hole flow pressure according to the actual relative error and the trend relative error by the following formula.
Wherein Δσ represents the fitting accuracy of the bottom hole flow pressure, a represents the a time window, g a represents the weight coefficient of the actual relative error of the bottom hole flow pressure in the a time window, Δσ a represents the actual relative error of the reservoir parameter in the a time period, and Δσ p represents the trend relative error.
According to the formula, the fitting accuracy of the bottom hole flow pressure is 13%.
Example III
Fig. 6 is a schematic structural diagram of a determining device for oil reservoir numerical simulation fitting accuracy according to a fourth embodiment of the present application. As shown in fig. 6, the apparatus includes:
The reservoir parameter value determining module 610 is configured to determine a predicted value and a corresponding actual value of at least two times of the reservoir parameter;
An actual relative error determining module 620, configured to determine, according to the predicted value and the actual value, a predicted error value of the reservoir parameter corresponding to each time, as an actual relative error of the reservoir parameter;
A trend relative error determination module 630, configured to predict an error trend of the reservoir parameter according to each of the actual relative errors, and determine a trend relative error of the reservoir parameter;
And the fitting precision determining module 640 is configured to determine the fitting precision of the reservoir parameter according to the actual relative error and the trend relative error.
The embodiment of the invention provides a device for determining the numerical simulation fitting precision of an oil reservoir, which is characterized in that predicted values and corresponding actual values of at least two times of oil reservoir parameters are determined; according to the predicted value and the actual value, determining a predicted error value corresponding to the oil reservoir parameter at each time as an actual relative error of the oil reservoir parameter; predicting the error trend of the oil reservoir parameters according to each actual relative error, and determining the trend relative error of the oil reservoir parameters; and determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error. According to the technical scheme, the influence of the actual relative errors and the trend relative errors corresponding to each historical time of the oil reservoir parameters on the oil reservoir numerical simulation fitting precision is considered, the accuracy of the oil reservoir numerical simulation fitting precision is improved, and a basis is provided for the adjustment of a subsequent oil reservoir numerical simulation model.
Further, the trend relative error determination module 630 includes:
The actual relative error fitting unit is used for fitting the actual relative errors corresponding to the time to obtain a fitting result;
and the trend relative error determining unit is used for determining a predicted error value corresponding to the oil reservoir parameter at the prediction time according to the fitting result, and taking the predicted error value as the trend relative error of the oil reservoir parameter.
Further, the fitting accuracy determining module 640 includes:
A weight coefficient determining unit, configured to determine a weight coefficient of the actual relative error according to a preset weight coefficient of the trend relative error, so that a sum of the preset weight coefficient of the trend relative error and the weight coefficient of the actual relative error is 1;
And the fitting precision determining unit is used for determining the fitting precision of the oil reservoir parameters according to the trend relative error, the preset weight coefficient of the trend relative error, the actual relative error and the weight coefficient of the actual relative error.
Further, the weight coefficient determining unit is specifically configured to:
Calculating the weight coefficient of the actual relative error according to the following formula:
wherein j represents the current time, k represents the total time quantity, f j represents the weight coefficient of the actual relative error of the oil reservoir parameter at the jth time, and ω represents the preset weight coefficient of the trend relative error.
Further, the fitting accuracy determining unit includes:
A first error value determining subunit, configured to take, as a first error value, a product of the trend relative error and a preset weight coefficient of the trend relative error;
a second error value determination subunit configured to take, as a second error value, a sum of products of the actual relative error and a weight coefficient of the actual relative error corresponding to each time;
and the fitting precision determining subunit is used for taking the sum of the first error value and the second error value as the fitting precision of the oil reservoir parameters.
Further, the actual relative error determining module 620 includes:
The oil reservoir parameter value grouping unit is used for grouping the predicted value and the actual value according to the time corresponding to the predicted value and the actual value and the preset time length to obtain at least two groups of predicted values and actual values;
each group of prediction difference value determining units is used for determining the difference value between each group of prediction values and the actual value according to each group of prediction values and the actual value;
And the actual relative error determining unit is used for determining the actual relative errors corresponding to the groups of predicted values and the actual values according to the differences between the groups of predicted values and the actual values.
Further, the actual relative error determination unit includes:
A first parameter determination subunit configured to take a sum of differences between each set of predicted values and actual values as a first parameter;
a second parameter determination subunit configured to take a sum of the actual values as a second parameter;
And the actual relative error determination subunit is used for taking the ratio of the first parameter to the second parameter as each group of predicted values and the actual relative error corresponding to the actual values.
The device for determining the oil reservoir numerical simulation fitting precision provided by the embodiment of the application can be used for executing the method for determining the oil reservoir numerical simulation fitting precision provided by any embodiment of the application, and has the corresponding functional modules and beneficial effects of the executing method.
Example IV
Fig. 7 shows a schematic diagram of the structure of a device 10 that may be used to implement an embodiment of the application. Devices are intended to represent various forms of digital computers, such as laptops, desktops, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The device may also represent various forms of mobile apparatuses such as personal digital processing, cellular telephones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing apparatuses. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the applications described and/or claimed herein.
As shown in fig. 7, the apparatus 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the device 10 can also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
The various components in the device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the determination of the accuracy of the reservoir numerical simulation fit.
In some embodiments, the method of determining the accuracy of the reservoir numerical simulation fit may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the above-described method of determining the accuracy of the reservoir numerical simulation fit may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the method of determining the accuracy of the reservoir numerical simulation fit in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present application, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present application may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present application are achieved, and the present application is not limited herein.
The above embodiments do not limit the scope of the present application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of the present application.
Claims (10)
1. A method for determining the accuracy of a numerical simulation fit of a reservoir, the method comprising:
determining predicted values and corresponding actual values of at least two times of oil reservoir parameters;
According to the predicted value and the actual value, determining a predicted error value of the oil reservoir parameter corresponding to each time as an actual relative error of the oil reservoir parameter;
predicting the error trend of the oil reservoir parameter according to each actual relative error, and determining the trend relative error of the oil reservoir parameter;
And determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error.
2. The method of claim 1, wherein predicting the error value of the reservoir parameter based on the actual relative error, determining a trend relative error of the reservoir parameter comprises:
fitting the actual relative errors corresponding to the times to obtain a fitting result;
And according to the fitting result, determining a predicted error value corresponding to the oil reservoir parameter at the predicted time, and taking the predicted error value as a trend relative error of the oil reservoir parameter.
3. The method of claim 1, wherein determining the accuracy of the fit of the reservoir parameters based on the actual relative error and the trend relative error comprises:
Determining the weight coefficient of the actual relative error according to the preset weight coefficient of the trend relative error so that the sum of the preset weight coefficient of the trend relative error and the weight coefficient of the actual relative error is 1;
and determining the fitting precision of the oil reservoir parameters according to the trend relative error, the preset weight coefficient of the trend relative error, the actual relative error and the weight coefficient of the actual relative error.
4. A method according to claim 3, wherein determining the weighting factor for the actual relative error based on the preset weighting factor for the trend relative error comprises:
Calculating the weight coefficient of the actual relative error according to the following formula:
wherein j represents the current time, k represents the total time quantity, f j represents the weight coefficient of the actual relative error of the oil reservoir parameter at the jth time, and ω represents the preset weight coefficient of the trend relative error.
5. A method according to claim 3, wherein determining the accuracy of the fit of the reservoir parameters based on the trend relative error, a preset weight coefficient for the trend relative error, the actual relative error, and a weight coefficient for the actual relative error comprises:
taking the product of the trend relative error and a preset weight coefficient of the trend relative error as a first error value;
Taking the sum of products of the weight coefficients of the actual relative error and the actual relative error corresponding to each time as a second error value;
And taking the sum of the first error value and the second error value as the fitting precision of the oil reservoir parameters.
6. The method of claim 1, wherein determining the predicted error value of the reservoir parameter as an actual relative error based on the predicted value and the actual value comprises:
Grouping the predicted values and the actual values according to the time corresponding to the predicted values and the actual values and the preset time length to obtain at least two groups of predicted values and actual values;
for each set of predicted values and actual values, determining differences between each set of predicted values and actual values;
And determining the actual relative errors corresponding to the predicted values and the actual values of each group according to the difference value between the predicted values and the actual values of each group and each actual value.
7. The method of claim 6, wherein determining actual relative errors for each set of predicted values and actual values based on differences between each set of predicted values and actual values and each actual value comprises:
Taking the sum of the differences between each set of predicted values and the actual values as a first parameter;
taking the sum of the actual values as a second parameter;
and taking the ratio of the first parameter to the second parameter as the actual relative error corresponding to each group of predicted values and actual values.
8. A device for determining the accuracy of a numerical simulation fit of a reservoir, the device comprising:
the oil reservoir parameter value determining module is used for determining predicted values and corresponding actual values of at least two times of oil reservoir parameters;
The actual relative error determining module is used for determining a predicted error value of the oil reservoir parameter corresponding to each time according to the predicted value and the actual value, and taking the predicted error value as an actual relative error of the oil reservoir parameter;
The trend relative error determining module is used for predicting the error trend of the oil reservoir parameter according to each actual relative error and determining the trend relative error of the oil reservoir parameter;
and the fitting precision determining module is used for determining the fitting precision of the oil reservoir parameters according to the actual relative error and the trend relative error.
9. An electronic device, the device comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of determining the accuracy of the reservoir numerical simulation fit of any of claims 1-7.
10. A computer readable storage medium storing computer instructions for causing a processor to perform the method of determining the accuracy of the reservoir numerical simulation fit of any one of claims 1-7.
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| CN202211458175.8A CN118057390A (en) | 2022-11-21 | 2022-11-21 | Method, device, equipment and medium for determining numerical simulation fitting precision of oil reservoir |
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