CN107989597A - A kind of crack data screening technique, device and storage medium - Google Patents
A kind of crack data screening technique, device and storage medium Download PDFInfo
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Abstract
This specification provides a kind of crack data screening technique, device and storage medium, including：The amount of simulation extraction tracer is calculated in the sub- crack data acquisition system and well site tracer experiments data concentrated according to the crack data between target well group；Wherein, the crack data are used for the orientation and attribute for representing crack between target well group；Object function is generated according to the amount of the amount of true extraction tracer and the simulation extraction tracer；Wherein, the object function is used for the ratio of the change curve of the change curve area surrounded the and tracer dose truly produced for representing the change curve of the tracer dose and tracer dose of simulation extraction truly produced in the range of certain time surrounded area in a coordinate system；The sub- crack data acquisition system is changed, in the hope of the minimum value of the object function；The corresponding sub- crack data acquisition system of wherein described minimum value is as crack the selection result.Screening crack data meet the needs of reservoir study and note adopt effect prediction etc..
Description
Technical Field
The specification relates to the field of geological fracture model construction, in particular to a fracture data screening method, a fracture data screening device and a storage medium.
Background
The three-dimensional fracture modeling is important for developing a fractured reservoir of an oil field, and the key and difficulty of the three-dimensional fracture modeling are that the established fracture model is matched with various dynamic and static data.
In the aspect of fracture modeling technology, early research mostly focuses on establishing an equivalent continuous model, and the model is highly simplified for real fractures and stratums, cannot simulate a fracture type reservoir with strong heterogeneity and poor continuity, and cannot visually display fracture forms. In the DFN (discrete fracture grid model) developed in recent years, fracture grids are directly formed by fracture slices with different forms and attributes, a fracture system is described in a discrete data form, fracture forms and distribution are reflected more truly, and the DFN has important significance on oil reservoirs with poor reservoir continuity and random fracture characterization scales.
The tracer experiment is a research means of the oil field aiming at the communication between underground oil reservoirs and wells. A special chemical substance (tracer) is dissolved in water, injected from a water injection well and extracted from a monitoring well. The communication characteristic between two wells of the underground oil reservoir is researched by analyzing the changes of the concentration and the quality of the injected and produced tracers.
Because the scale of the cracks in the reservoir is very different, the hierarchical modeling principle is usually followed in the DFN establishment process, namely, a large-scale crack model is established deterministically by utilizing fault interpretation and ant tracking crack data, and on the basis of the large-scale crack model, a small-scale crack model is established randomly by adopting a target-based punctuality point process simulation method under the constraints of a crack density model, a ground stress field, a crack attribute statistical rule, well hole hard data and the like. However, because the large-scale fractures in the area are few, and the randomness of the small-scale fractures formed by simulation is high, the compatibility of connectivity among well groups in the existing DFN and dynamic data such as tracers is poor.
In the process of implementing the present specification, the inventor finds that at least the following problems exist in the prior art:
in the actual oil field production and research process, in order to enable the established fracture model to meet the requirements of the aspects of digital modeling, reservoir research, injection and production effect prediction and the like, modeling personnel often make the model qualitatively coincide with tracer data through a method of randomly and manually translating the fracture. Thus, although the inter-well connectivity in the model can be consistent with that reflected by the tracer, due to the randomness and subjectivity of manual operation, the consistency is only limited to qualitative connection or non-connection, and the consistency of the inter-well connectivity and the size of the tracer data cannot be guaranteed quantitatively. For example, tracer data confirms that two wells are connected, while two wells in the initial DFN model are not connected, and the two wells are connected by artificially translating fractures in the DNF, so that the model and the tracer are consistent in connection or disconnection, but the connectivity between wells in the model cannot be unified with the detailed tracer data size, and the manual modification method also greatly increases the working strength of modeling personnel.
Disclosure of Invention
The embodiments of the present disclosure are directed to a method, an apparatus, and a storage medium for screening fracture data, which are used to screen effective fractures in a fracture geological model, so that the quality of connectivity between wells in the model is consistent with the size of detailed tracer data.
Embodiments of the present description provide a fracture screening method, the method comprising: calculating to obtain the amount of the simulated produced tracer according to one sub-fracture data set in the fracture data sets among the target well groups and well site tracer experiment data; wherein the fracture data is used to represent the orientation and attributes of the fractures between the target well groups; generating a target function according to the amount of the real produced tracer and the amount of the simulated produced tracer; the target function is used for expressing the ratio of the area enclosed by the variation curve of the actually-extracted tracer quantity and the variation curve of the simulated-extracted tracer quantity within a certain time range to the area enclosed by the variation curve of the actually-extracted tracer quantity in a coordinate system; changing the sub-fracture data set to obtain the minimum value of the objective function; and taking the sub-fracture data set corresponding to the minimum value as a fracture data screening result.
Embodiments of the present description provide a fracture screening apparatus, the apparatus includes: a calculation module; the method comprises the steps of calculating to obtain the amount of a simulated production tracer according to one sub-fracture data set in the fracture data sets among target well groups and well site tracer experiment data; wherein the fracture data is used to represent the orientation and attributes of fractures between a target well group; an objective function generation module; generating an objective function according to the amount of the real produced tracer and the amount of the simulated produced tracer; the target function is used for expressing the ratio of the area enclosed by the variation curve of the actually-extracted tracer quantity and the variation curve of the simulated-extracted tracer quantity within a certain time range to the area enclosed by the variation curve of the actually-extracted tracer quantity in a coordinate system; a fracture data screening module; for altering the sub-fracture data set to find a minimum of the objective function; and taking the sub-fracture data set corresponding to the minimum value as a fracture screening result.
The present specification provides a storage medium storing computer program instructions which, when executed, implement: calculating to obtain the amount of the simulated produced tracer according to one sub-fracture data set in the fracture data sets among the target well groups and well site tracer experiment data; wherein the fracture data is used to represent the orientation and attributes of fractures between a target well group; generating a target function according to the amount of the real produced tracer and the amount of the simulated produced tracer; the target function is used for expressing the ratio of the area enclosed by the variation curve of the actually-extracted tracer quantity and the variation curve of the simulated-extracted tracer quantity within a certain time range to the area enclosed by the variation curve of the actually-extracted tracer quantity in a coordinate system; changing the sub-fracture data set to obtain the minimum value of the objective function; and taking the sub-fracture data set corresponding to the minimum value as a fracture screening result.
According to the technical scheme provided by the implementation mode of the specification, the implementation mode of the specification calculates the quantity of the simulated produced tracer according to one sub-fracture data set in the fracture data sets among the target well groups and the experimental data of the well site tracer, generates a target function according to the quantity of the simulated produced tracer and the quantity of the real produced tracer, obtains a sub-fracture data set enabling the target function to be minimum by changing the sub-fracture data set, the sub-fracture data set enabling the target function to be minimum is an effective fracture data set which is screened out, and the fractures corresponding to the fracture data are effective fractures. The inter-well communication is quantitatively ensured to be uniform with the size of tracer data, the inter-well communication in the model is quantitatively matched with the real tracer data, the requirements of digital modeling, reservoir research, injection and production effect prediction and the like are met, and the working strength of modeling personnel is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the description below are only some embodiments described in the present specification, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic flow chart of a fracture screening method provided in an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of an initial fracture geologic model provided in an embodiment of the present disclosure and a scenario of the initial fracture geologic model after a fracture that fails to connect to a target well group by translation is screened;
FIG. 3 is a schematic diagram of a scenario provided in an embodiment of the present disclosure for weighting candidate fractures according to their distances from a W1 well and a W2 well;
FIG. 4 is a plot of simulated production tracer quantity versus production time versus actual production tracer quantity versus production time provided in an illustrative embodiment;
fig. 5 is a schematic diagram of minimum values of objective functions corresponding to 20 sub-fracture data sets provided in an embodiment of the present specification;
FIG. 6 is a schematic diagram of a fracture model before and after translation of 8 fractures provided in an embodiment of the present disclosure;
FIG. 7 is a graph illustrating the goodness of fit between simulated tracer daily production data and actual data of a connected fracture provided in an embodiment of the present disclosure;
FIG. 8 is a schematic illustration of the compatibility of a communicating fracture with other fracture formations and elevations surrounding a well group as provided in embodiments of the present disclosure
FIG. 9 illustrates the compatibility of a communicating fracture with other fractures around a well group in terms of length, width, and opening provided in embodiments of the present disclosure
Fig. 10 is a block diagram illustrating a structure of a fracture screening apparatus provided in an embodiment of the present disclosure;
Detailed Description
The embodiment of the specification provides a method and a device for screening crack data and a storage medium.
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all the embodiments. All other embodiments obtained by a person of ordinary skill in the art without any inventive step based on the embodiments of the present disclosure should fall within the scope of protection of the present disclosure.
A fracture data screening method provided in an embodiment of the present disclosure is described in detail below with reference to the accompanying drawings. Although the present specification provides method steps as described in the following embodiments or flowcharts, more or fewer steps may be included in the method based on conventional or non-inventive efforts, and the execution order between the steps is not limited.
Referring to fig. 1, a fracture data screening method provided in an embodiment of the present disclosure may include the following steps.
Step S10: calculating to obtain the amount of the simulated produced tracer according to one sub-fracture data set in the fracture data sets among the target well groups and well site tracer experiment data; wherein the fracture data is used to represent the orientation and attributes of the fractures between the target intervals.
In this embodiment, the target well group may be a target well group in the range of the underground oil reservoir, one monitoring well may extract a solution injected from another surrounding water injection well, and the quality of connectivity between the water injection well and the monitoring well may be evaluated, and the selected monitoring well and the selected water injection well may be referred to as the target well group.
In this embodiment, the fracture data may be data representing the orientation and properties of the fracture between the target set of wells. The fracture data may be obtained from the constructed fracture model. Specifically, a large-scale fracture model, a small-scale fracture model, or the like may be included. One fracture data may represent an orientation of one fracture, which may include a distance of the fracture from the target well group; the angle of inclination of the fracture with respect to the plane of the target well group, etc. A fracture data may also represent attributes of a fracture, which may include the length, width, opening, cross-sectional area, etc. of the fracture. The fracture data may include a distance between the fracture and the target well group; the cross-sectional area of the crack; the fracture connects the lengths of the channels of the two wells of the target well group; the width of the crack; the opening of the crack, etc.
In this embodiment, the fracture data set may be a set of fracture data obtained in the constructed fracture model. The fracture data set may include at least one fracture data, and the size of the fracture data in the fracture data set may be determined according to a fracture model that is constructed in advance.
In this embodiment, the sub-fracture data set may be a subset of the fracture data set. The sub-fracture data set may contain fracture data in at least one of the fracture data sets. The fracture data in the sub-fracture data set may be randomly selected or selected according to a specified rule, and the selecting according to the specified rule may include numbering the fractures in the fracture data set and selecting the fracture data according to a specified sequence; weighting the fractures in the fracture data set, selecting the fractures according to different weight values, and the like.
In this embodiment, the wellsite tracer experiment may be a means for studying the connectivity between wells of a subterranean reservoir. The method is mainly characterized in that a certain special chemical substance is dissolved in water, injected from an injection well and extracted from a monitoring well. The process of communication characteristics between two wells of an underground reservoir is studied by analyzing the changes of the concentration and quality of injected and produced tracers. The tracer experimental data may include, as an initial concentration of tracer; conducting tracer concentration to the monitoring well on a certain day in the fracture; the total injection volume of the tracer in the water injection well of the target well group; the distribution coefficient of the injected water of the water injection well to the monitoring well; viscosity of the fluid; and the bottom hole pressure difference of the water injection well and the monitoring well, and the like.
In this embodiment, the amount of tracer produced by simulation may be a prediction of the amount of tracer produced from the monitoring well by injecting a certain amount of tracer from an injection well, and simulating the process of conducting tracer in the fracture between the target well groups by calculation or analysis processing according to the fracture data and the wellsite experimental data.
Specifically, the amount of the simulated production tracer can be calculated through a driving force and viscous force balance equation. Solving a hydrodynamic dispersion equation of one-dimensional instantaneous injection to obtain the distribution of the concentration of the tracer along with time and distance:
in the formula, C 0 Initial concentration of tracer; c i Conducting tracer concentration to a monitoring well on the ith fracture day t; l is i The length of a channel connecting the two wells for the ith fracture; Δ L i Tracer slug length at water injection well for ith fracture; sigma i The standard deviation of the distribution curve; v. of i The average flow velocity of the fluid in the ith fracture; t is time, α i The hydrodynamic dispersion of the tracer in the ith fracture is constant. And the fracture flow resistance is defined according to the Hegen-Poiseuille formula:
in the formula, R i The flow resistance in the ith crack is shown, and delta P is the bottom hole pressure difference of the water injection well and the monitoring well; q. q.s i The average flow rate of the ith fracture. Taking the reciprocal of the fracture flow resistance as an example, calculating the lengths of tracer slugs flowing into different fractures:
A i ＝a i b i
in the formula,. DELTA.L i Is the length of the i-th crack tracer slug after splitting, V d For total injection body of tracer in water injection wellAccumulating; f. of j The distribution coefficient of injected water of the water injection well to the monitoring well can be calculated according to the ratio of the quality of the tracer agent produced by the monitoring well to the quality of the tracer agent injected into the water injection well; a. The i Denotes the cross-sectional area of the crack, a i The width of the ith slit; b i The opening degree of the ith crack. Introducing a balance equation of fluid driving force and viscosity, and calculating the flow of the ith crack according to the balance equation:
in the formula, q i The unit of (A) is; a is i The width of the ith slit; b i The opening degree of the ith crack; μ is the fluid viscosity. By combining the above formulas, the following can be obtained through mathematical derivation: under the conditions of the known channel length, width and opening degree of each communicated fracture between wells, the volume and concentration of injected tracer, the quality of produced tracer, the pressure difference between two wells, the viscosity coefficient and hydrodynamic dispersion of the tracer, the quality of the tracer produced on the t day of all fractures in a monitoring well can be solved through a mathematical model of the fracture conduction tracer:
wherein the content of the first and second substances,wherein m (t) is in the unit of g/d, C i The tracer concentration produced on day t in the monitoring well for the ith fracture.
Step S12: generating a target function according to the amount of the real produced tracer and the amount of the simulated produced tracer; the target function is used for expressing the ratio of the area enclosed by the variation curve of the actually-extracted tracer quantity and the variation curve of the simulated-extracted tracer quantity within a certain time range to the area enclosed by the variation curve of the actually-extracted tracer quantity in a coordinate system;
in this embodiment, the actual produced tracer amount may be a real-condition tracer produced amount obtained by injecting a certain amount of tracer from a water injection well and collecting from a monitoring well according to the wellsite tracer experiment. The amount of the truly produced tracer can truly reflect the communication condition of the fractures among the target well groups.
In this embodiment, the variation curve of the amount of tracer actually extracted within a certain time range may be obtained by dissolving a tracer substance into a solution, injecting the solution into a water injection well, and extracting the solution from a monitoring well to obtain the concentration and quality of the tracer in the solution. The amount of tracer produced varies with the time of production. The tracer agent can be extracted from the monitoring well at a certain time interval, the amount of the tracer agent extracted at the corresponding time is recorded, and a curve is drawn. The time interval may be determined according to specific engineering needs.
Specifically, the amount of the tracer agent extracted from the monitoring well on the first day when the tracer agent solution is injected is recorded, the amount of the tracer agent extracted from the monitoring well on the second day and the amount of the tracer agent extracted from the monitoring well on the third day are recorded by taking the day as a time interval until the monitoring well cannot extract the tracer agent, and the quantities are drawn into a curve.
In this embodiment, the curve for simulating the tracer production amount may be obtained by simulating the tracer production amount from the detection well in the same time unit as the actual tracer production amount, and then drawing the curve.
Specifically, the tracer is produced by the monitoring well in units of days, the tracer dosage is simulated and produced in units of days until the simulated produced tracer dosage is zero, and a curve is drawn.
In this embodiment, the area enclosed by the variation curve of the actually-extracted tracer amount and the variation curve of the simulated-extracted tracer amount may be, for the variation curve of the actually-extracted tracer amount, calculating the integral of the curve, and obtaining the area enclosed by the variation curve of the actually-extracted tracer amount in the coordinate system; and solving curve integral for the change curve of the simulated sampled tracer quantity to obtain the area enclosed by the change curve of the simulated sampled tracer quantity in the coordinate system. And subtracting the integral of the change curve of the simulated produced tracer quantity from the integral of the change curve of the real produced tracer quantity to obtain the area enclosed by the change curve of the real produced tracer quantity and the change curve of the simulated produced tracer quantity.
In this embodiment, the objective function may be a ratio of an area enclosed by a variation curve of a quantity of actually-extracted tracer to a variation curve of a quantity of simulated-extracted tracer within a certain time range and an area enclosed by a variation curve of a quantity of actually-extracted tracer in a coordinate system. The larger the ratio is, the larger the error between the amount of the real produced tracer and the amount of the simulated produced tracer is; the smaller the ratio, the smaller the error between the amount of actual produced tracer and the amount of simulated produced tracer. In the objective function, the area enclosed by the variation curve of the actually-extracted tracer amount is constant, and the ratio changes when different crack data are selected for calculation.
In this embodiment, the objective function may be:
wherein m is j (t)＝C(t)q w (t), m (t) and m j (t) the tracer quantity of the simulated production and the tracer quantity of the real production on the t day are respectively; c (t) is the concentration of the actually produced tracer on the t day; q. q.s w (t) the real daily water yield of the crack on the t day; t is time.
S14, changing the sub-crack data set to obtain the minimum value of the objective function; and taking the sub-fracture data set corresponding to the minimum value as a fracture data screening result.
In this embodiment, the changing the sub-fracture data set may include randomly selecting a random number of fracture data from the fracture data set to form the sub-fracture data set; randomly selecting a specified number of crack data from the crack data set to form the sub-crack data set; and selecting a random number or a specified number of cracks from the crack data set according to a specified algorithm.
In this embodiment, the minimum value of the objective function may be obtained by randomly selecting a random number or a predetermined number of fracture data from the fracture data set according to a simulated annealing algorithm, changing the sub-fracture data set according to a preset simulated annealing rule until a sub-fracture data set that can minimize the objective function value is selected, and using the sub-fracture data set as a result of fracture data screening.
In this embodiment, the size of the objective function value is only related to the selected sub-fracture data set, the smaller the objective function value is, the smaller the error between the amount of the real produced tracer and the amount of the simulated produced tracer is, and the more the attribute and distribution of the sub-fracture set corresponding to the objective function value are matched with the fracture of the real communicated target well group, so that the fracture which can be effectively communicated with the target well group in the fracture model can be effectively screened out.
In one scenario application provided in the present specification, referring to fig. 2, 455 small-scale fractures within 500 meters from the center of the perforation segments of two wells W1 and W2 are displayed in the initial fracture geological model, and there are 455 fracture data in the fracture data set. According to the geometrical elements of the cracks, small cracks which cannot be connected with the extended areas of the W1 and W2 well perforation sections through translation are filtered. The distance between the two wells W1 and W2 is closer and smaller than the length of the peripheral cracks, so the peripheral cracks do not need to be prolonged. The perforation section refers to a section of an underground water injection well or an underground oil production well of an oil field which is perforated into a screen shape so as to allow oil gas to enter the oil well from rocks or water to be injected into the rocks from the well, and the perforation section is called a perforation section.
In the application of this scenario, please refer to fig. 3, a weight is assigned to each fracture data, a linear distance between the center of the fracture and the center of the uphole perforation segment is obtained according to the fracture geological model, a weight is assigned to each fracture according to the distance between the fracture and the perforation segment of the target well group, the weight is inversely proportional to the distance, and the sum of all fracture weights is 1, according to the formula:
calculating the weight value of each crack, wherein lambda i Weight of i-th crack, l i The distance from the ith fracture to the center of the perforation section of the target well group.
In the application of the scenario, please refer to fig. 4, the real monitored daily production tracer quality data is obtained, and the amount of the tracer to be produced in simulation is calculated according to one sub-fracture data set in the fracture data set among the target well groups and the well site tracer experiment data.
In the application of the scene, considering that the average longitudinal length of the perforation sections of the W1 and W2 wells is 82m, the W1 core shows small density of nearby fractures, and therefore the number of the communicated fractures between the W1 and W2 wells is set to be in a range from 1 to 20.
In this scenario application, a simulated annealing rule is set, as shown in Table 1, T 0 Is the initial temperature; λ is a temperature reduction factor, and each temperature reduction is multiplied by λ,0<λ<1；K max The maximum number of iterations for selecting a fracture combination at a certain temperature; k is Receiving The maximum number of times the preferred fracture combination is accepted, at a particular temperature, when the fracture combination is accepted K Receiving Then, entering the next temperature state; s is the number of stops, if there are S times to reach K max The simulation is terminated; Δ O is the lowest objective function value representing convergence. In the table, quenching, extremely fast cooling, fast cooling and general cooling are different simulated annealing rules, and the four are independent from each other. Different simulated annealing rules determine different parameter values, which represent the speed and the precision of the simulated annealing process. The slower the cooling, the longer the simulated annealing process, and the more accurate the results.
TABLE 1 annealing simulation plan
In the present scenario, the number of connected fractures between W1 and W2 wells is set to range from 1 to 20, and annealing is performed according to extremely fast coolingThe simulation plan screens the sub-fracture data set. Screening a sub-fracture data set with the set length of 1, randomly selecting one fracture data T0 from the fracture data set, calculating an objective function value F0, randomly selecting one fracture data T1 from the fracture data set again, calculating an objective function value F1, comparing the sizes of the F0 and the F1, and receiving the value of the F1, wherein the F1 is smaller than the F0. In order to obtain the ideal effect, the threshold value e of the objective function for terminating the simulation is 0.2, and the threshold value e of the temperature is 10 -6 And F1 is larger than 0.2, selecting one piece of crack data from the crack data set again, calculating the objective function value until the objective function value corresponding to one piece of crack data is smaller than the threshold number of the objective function or the difference between the objective function values calculated twice continuously is smaller than the threshold value of the objective function 0.2, and screening out corresponding crack data, wherein the crack data is a sub-crack data set when the number of cracks is 1. Referring to fig. 5, according to the same method, a total of 20 sub-fracture data sets are screened, and the 20 sub-fracture data sets correspond to 20 corresponding fracture numbers respectively.
In the application of the scene, in the 20 sub-crack data sets, the data sets are respectively according to the formulaAn average fracture weight is calculated for each converging fracture combination, wherein,to contain n j Average fracture weight of the convergence fracture combination of the strip fractures; w is a i Is the weight of the i cracks in the combination. The calculation results are shown in table 2, where the combined average weight of 8 fractures is the largest and the corresponding objective function value is the smallest, and the sub-fracture data set is selected as the optimal sub-fracture data set as shown in table 3.
TABLE 2 average weights of single fractures for each converging fracture combination
TABLE 3 optimal fracture combination basic information
In the application of this scenario, please refer to fig. 6, the fractures in the optimal sub-fracture data set are translated to connect the W1 and W2 perforation segments, i.e., to form an optimized connected fracture model, as shown in fig. 6, 8 fractures after translation can well communicate the W1 and W2 perforation segments, and through conducting tracer simulation, the simulated tracer data generated by the fracture combination matches the real tracer data well, as shown in fig. 7. In the translation process, the moving distance of 8 cracks is 1651.9m and 308.0m at the maximum, and the average value of a single crack is 206.5m, and fig. 8 and 9 show that in a sub-crack data set, the length, the width, the azimuth angle, the inclination angle and the opening degree of the crack are not very different, no contradiction exists among the cracks in the combination, the properties of the cracks are compared with the properties of other cracks in the range of 250m around the W1 and W2 well perforation sections, the compatibility is very good, and the combination is also proved to be well matched with a local stress field.
In one embodiment, the method further comprises: comparing the well spacing between the target groups of wells to fracture lengths represented by fracture data in the fracture data set; and extending the fracture with the fracture length smaller than the well spacing so that the fracture length is larger than the well spacing.
In this embodiment, the well spacing may be a distance between the water injection well and the monitoring well in the target well group, and may be obtained according to actual measurement.
In this embodiment, the fracture data set may include at least one of fracture data that can indicate fracture properties and orientations, and the fracture data may include fracture length information that can indicate the length of a fracture.
In this embodiment, the fracture with the fracture length smaller than the well interval may be extended by traversing the fracture length information of all fracture data in the fracture data set, screening out the fracture with the fracture length smaller than the well interval, modifying the fracture data parameter of the fracture with the fracture length smaller than the well interval, and modifying the fracture length to make the fracture length larger than the well interval.
In the present embodiment, by extending the fracture length, it is possible to avoid the situation where some fractures that can effectively communicate with the well group in practice but cannot connect with the target well group in the fracture model due to too short fracture length are regarded as invalid fractures, and the accuracy of fracture screening is improved.
In one embodiment, a fracture capable of connecting a target group of wells by spatial translation is screened out from the fracture data.
In this embodiment, the fracture data may represent the azimuth and the attribute of the fracture, the fracture data may include inclination angle information of the fracture, and the spatial position relationship between the fracture and a plane formed by the monitoring well and the water injection well may be determined according to the inclination angle information. Screening out the cracks if the cracks are parallel to a plane formed between the monitoring well and the water injection well according to the dip angle information of the cracks; fracture data representing the fracture is removed from the fracture data set if the fracture is not parallel to a plane formed between the monitor well and the injection well based on the dip angle information for the fracture.
In the embodiment, if the spatial position of the crack cannot be parallel to the plane formed between the monitoring well and the water injection well, the crack cannot be connected with the target well group, the crack data set is excluded from the crack information of the crack which cannot be connected with the target well group through spatial translation, invalid cracks are prevented from being screened, and the crack screening precision is improved.
In one embodiment, altering the fracture data in the fracture set to find the minimum value of the objective function may include:
setting a simulated annealing strategy according to a specified rule;
executing a simulated annealing algorithm according to the simulated annealing strategy to calculate the minimum value of the objective function; and taking the sub-fracture data set corresponding to the minimum value of the objective function as a fracture screening result.
In this embodiment, the simulated annealing algorithm may be a probabilistic algorithm. The simulated annealing algorithm is based on the solid annealing principle, and heats the solid to be sufficiently high and then slowly cools the solid. When the temperature is raised, the internal particles in the solid become disordered along with the temperature rise, the internal energy is increased, the particles gradually get ordered when the solid is slowly cooled, the particles reach an equilibrium state at each temperature and finally reach a ground state at normal temperature, and the internal energy is reduced to the minimum.
Specifically, the internal energy E may be modeled as an objective function O, the temperature T may be modeled as a control parameter T, the calculated objective function value F0 starts according to the initially selected sub-fracture data set, and an iteration from generating a new objective function value F1 to comparing the new objective function value with the current objective function value and then to accepting or rejecting is repeated for the current objective function value, and the probability of accepting or rejecting may be calculated according to a formula:wherein t represents the initial temperature, i.e. the control parameter, F1 represents the new objective function value, F0 represents the current objective function value, and gradually attenuates the t value, and the current objective function value when the algorithm is terminated is the obtained approximate optimal solution. The annealing process is controlled by an annealing simulation plan.
In this embodiment, the simulated annealing rule may be set according to the requirement of crack screening, and a simulated annealing algorithm is executed according to the simulated annealing rule to screen a sub-crack data set that minimizes the objective function. The simulated annealing rule can comprise an initial temperature and a temperature reduction factor, wherein the temperature reduction factor needs to be multiplied when the temperature is reduced each time; selecting the maximum iteration times of the sub-fracture data set at a certain temperature; the maximum number of times a sub-fracture data set can be accepted at a certain temperature; the number of stops; objective function thresholds, etc. Different simulated annealing rules determine different parameter values, which represent the speed and the precision of the simulated annealing process. The slower the cooling, the longer the simulated annealing process, and the more accurate the results.
Specifically, the simulated annealing rule is that the initial temperature is 0.5, the temperature reduction factor is 0.01, the maximum iteration number of the selected sub-crack data set is 10, the maximum acceptable number of times of the target function value at a certain temperature is 2, the stop number is 3, and the threshold value of the target function is 0.2.
Selecting a sub-fracture data set T0 from the fracture data set, calculating a corresponding objective function value to be F0, selecting a sub-fracture data set T1 again, calculating a corresponding objective function value to be F1, and F0&F1, according to the formula: p = e -(F1-F0)0.5 The probability of accepting F1 is calculated.
And if the acceptance of the F1 is rejected, selecting a sub-crack data set again, calculating a corresponding objective function value, if the sub-crack data set is still larger than the F0 and the acceptance of the objective function value is rejected for 10 times, selecting a sub-crack data set again, if the sub-crack data set is still larger than the F0 and the acceptance of the objective function value is rejected, rejecting the objective function value for 10 times according to a simulated annealing rule, multiplying the initial temperature 0.5 by a cooling factor 0.01 to enter the next temperature, if the rejection is totally 30 times, comparing the F0 with a target threshold value 0.2, if the F0 is smaller than the target function threshold value 0.2, taking the F0 as the minimum value of the target function, and screening out a sub-crack data set T0 corresponding to the F0. And if the F0 is larger than the threshold of the target function, selecting one sub-crack data set again until the target function value corresponding to one sub-crack data set is smaller than the threshold of the target function or the difference between the target function values calculated twice continuously is smaller than the threshold of the target function by 0.2. Screening out the corresponding sub-fracture data set.
And if the F1 is received, comparing the F1 with a threshold value of the target function of 0.2, if the F1 is less than 0.2, taking the F1 as the minimum value of the target function, and screening out a sub-crack data set T1 corresponding to the F1. If F1 is larger than the threshold value of the target function 0.2, selecting a sub-crack data set T2 again, wherein the corresponding target function value is F2, if F2 is larger than F1, calculating the probability of accepting F2, if F2 is received, comparing F2 with the threshold value of the target function 0.2, wherein F2 is larger than 0.2, selecting a sub-crack data set again, already accepting two target function values, multiplying the initial temperature 0.5 by the cooling factor 0.01, entering the next temperature, and continuing to perform the simulated annealing operation until one sub-crack data set corresponds to a target function value smaller than the threshold value of the target function or the difference between two continuously calculated target function values is smaller than the threshold value of the target function 0.2. Screening out the corresponding sub-fracture data set.
In the embodiment, an annealing simulation algorithm is executed by setting an annealing simulation plan, a sub-crack data set is screened from a crack data set by each disturbance in annealing simulation, an objective function is continuously reduced to be close to 0 and converged by screening for multiple times, and the objective function is used as a screening limiting condition to be executed to screen an effective crack.
In one embodiment, the method further comprises: determining the number range of cracks communicating the target well group according to geological data; determining a set length range of the sub-fracture data set according to the number range of the fractures; wherein, in the range of the number of the cracks, each number of the cracks corresponds to one set length; the set length is the number of fracture data in the sub-fracture data set; and selecting a sub-crack data set corresponding to the set length from the crack data set, and screening the sub-crack data set which is corresponding to each crack number and enables the objective function value to be minimum within the range of the crack number according to the simulated annealing rule.
In this embodiment, the geological data may be obtained by performing an experiment on the geology within the target well group, and may include core experiment data; imaging well log data, etc. The geological data may include fracture distributions between target well groups.
In this embodiment, the number of the fractures may be in a range of how many fractures are probably communicated with the target well group according to the fracture distribution between the target well groups, which may be obtained according to the geological data. Specifically, the distribution condition of the fractures among the target well groups is obtained according to the imaging logging information, 10-20 fractures communicated with the target well groups are obtained, and 10-20 fractures are the number range of the fractures.
In this embodiment, the set length may be the number of fracture data in the sub-fracture data set, and each fracture may correspond to one fracture data. The number range of the fractures can be obtained according to the geological data, and the number of the fracture data in the sub-fracture data set is determined.
In this embodiment, the selecting of the sub fracture data set corresponding to the set length from the fracture data set may be determining a number range of fractures according to the geological data, and selecting the sub fracture data set corresponding to the set length according to each number in the number range of fractures. For example, when the number of the cracks ranges from 1 to 3, when the number of the cracks takes 1, only 1 crack data exists in the sub-crack data set; when the number of the cracks is 2, 2 crack data exist in the sub-crack data set; when the number of fractures is 3, there are 3 fractures in the sub-fracture data set.
In this embodiment, the sub-fracture data set corresponding to each number of fractures and enabling the objective function value to be the minimum within the range of the number of fractures and selected according to the simulated annealing rule may be obtained by determining the range of the number of fractures according to the geological data, and performing annealing simulation operation on the sub-fracture data set of the set length corresponding to each number of fractures to obtain the sub-fracture data set corresponding to each number of fractures and enabling the objective function value to be the minimum. Specifically, for example, the number of the cracks ranges from 1 to 3, when the number of the cracks is 1, the set length of the sub-crack data sets subjected to the annealing simulation operation is 1, and the sub-crack data sets with the set length of 1 and the smallest objective function value are screened; when the number of the cracks is 2, the set length of the sub-crack data sets subjected to the annealing simulation operation is 2, and the sub-crack data sets with the minimum objective function value and the set length of 2 are screened; and when the number of the cracks is 3, the set length of the sub-crack data sets subjected to the annealing simulation operation is 3, and the sub-crack data sets with the minimum objective function value and the set length of 3 are screened.
In this embodiment, by determining the range of the number of fractures among the target well groups, determining the set length of the sub-fracture data set, and screening out the sub-fracture data set which is in the range of the number of fractures and corresponds to each number of fractures and enables the objective function value to be the smallest according to the simulated annealing rule, the problem that the number of fracture data in the sub-fracture data set is uncertain when each iterative screening is performed according to the annealing simulation plan, the program randomly selects the number of fractures, the efficiency is low, and part of fracture combinations may not be traversed is solved.
In one embodiment, the method further comprises: acquiring the distance between a crack and the target well group according to the crack data; weighting the fracture data according to the distance between the fracture and the target well group, wherein the weight is in inverse proportion to the distance between the fracture and the target well group, and the weighted values of all the fracture data are added to be 1; and calculating the crack data average weight of the sub-crack data set corresponding to each crack number and enabling the objective function value to be minimum, and screening out the sub-crack data set with the maximum average weight.
In this embodiment, the distance between the fracture and the target well group may be acquired, the fracture data may include azimuth information of the fracture, the azimuth information may include distance information between the fracture and the target well group, and the distance between the fracture and the target well group is obtained according to the distance information.
In this embodiment, the weighting given to the fracture data according to the distance between the fracture and the target well group may be that, according to a specified rule, the weighting given to the fracture data corresponding to the fracture is given according to the distance between the fracture and the target well group. The size of the assignment may indicate how important the fracture data is. The assignment may be performed by adding an assigned data to the corresponding fracture data. The assigned weight value may be inversely proportional to the distance between the fracture and the target well group, and the sum of all fracture weight values is 1. Can be determined according to the formula:weighting the corresponding crack; wherein λ is i Weight of i-th crack, l i K is the total number of fractures for its distance to the target well group.
In this embodiment, the calculating of the average weight of the fracture data of the sub-fracture data set corresponding to each number of fractures and minimizing the objective function value, and the screening of the sub-fracture data set with the maximum average weight may be performed by obtaining a number range of fractures between target well groups according to geological data, obtaining a sub-fracture data set with a corresponding set length and minimizing the objective function for each number within the number range, calculating the average weight of the fracture data in the sub-fracture data sets, and screening the sub-fracture data set with the maximum average weight. The average fracture weight is according to the formula:
and calculating to obtain the result that, wherein,to contain n j An average fracture weight of sub-fracture data of the individual fracture data; w is a i And the weight value of the ith crack data.
In the embodiment, the selected sub-fracture data set is not only controlled by the target function, but also constrained by the fracture weight by giving the weight to the fracture data and screening out the sub-fracture data set with the large weight, so that the requirement of the tracer data goodness of fit reflected by the target function is effectively met preferentially, the requirement of the distance reflected by the weight is met secondarily, and the screened fracture is ensured to be as close as possible to the target well group.
In one embodiment, the method further comprises translating fractures corresponding to the fracture data in the screened sub-fracture data set to connect the target well group.
In this embodiment, translating the fractures corresponding to the fracture data in the screened sub-fracture data set, connecting the sub-fracture data set to a target well group, and if all other fractures remain unchanged, obtaining a sub-fracture data set capable of minimizing a target function value through screening, modifying position information in the fracture data in the sub-fracture data set, and modifying the distance between the fracture data and the target well group to zero; or in the fracture model, manually translating the fracture corresponding to the fracture data in the sub-fracture data set, connecting the fracture to the target well group, and keeping other fractures unchanged.
In this embodiment, the fractures corresponding to the fracture data in the screened sub-fracture data set are translated to connect the target well group, and other fractures are kept unchanged, so that the fracture data in the fracture model can be matched with the communication condition of the fractures between the target well groups under the real condition.
Referring to fig. 10, an embodiment of the present disclosure further provides a fracture data screening apparatus, including a computing module; the method comprises the steps of calculating to obtain the amount of a simulated production tracer according to one sub-fracture data set in the fracture data sets among target well groups and well site tracer experiment data; wherein the fracture data is used to represent the orientation and attributes of fractures between a target well group; an objective function generation module; generating an objective function according to the amount of the real produced tracer and the amount of the simulated produced tracer; the target function is used for expressing the ratio of the area enclosed by the variation curve of the actually-extracted tracer quantity and the variation curve of the simulated-extracted tracer quantity within a certain time range to the area enclosed by the variation curve of the actually-extracted tracer quantity in a coordinate system; a crack data screening module; for altering the sub-fracture data set to find a minimum of the objective function; and taking the sub-fracture data set corresponding to the minimum value as a fracture screening result.
In one embodiment, the fracture data screening apparatus may further include the following units. The method comprises a crack number determining unit; the system is used for determining the number range of cracks communicating the target well group according to geological data; a set length determination unit; a set length range for determining the set of sub-fracture data sets from the number range of fractures; wherein, in the range of the number of the cracks, each number of the cracks corresponds to one set length; the set length is the number of fracture data in the sub-fracture data set; a first screening unit; and the sub-crack data set is used for selecting the sub-crack data set with the corresponding set length from the crack data set, and screening the sub-crack data set which is corresponding to each crack number and enables the objective function value to be minimum within the range of the crack number according to the simulated annealing rule. A weight assignment unit; the fracture data processing system is used for assigning a weight value to the fracture data according to the distance between the fracture and the target well group, wherein the weight value is in inverse proportion to the distance between the fracture and the target well group, and the weight values of all the fracture data are added to be 1; a second screening unit; and the fracture data average weight is used for calculating the fracture data average weight of the sub-fracture data set corresponding to each fracture number and enabling the objective function value to be minimum, and screening out the sub-fracture data set with the maximum average weight.
The apparatuses or units illustrated in the above embodiments may be specifically implemented by a computer chip or an entity, or an article with some functions. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the various modules may be implemented in the same one or more software and/or hardware implementations of the present description.
Those of skill would further appreciate that the various illustrative logical blocks, modules, and steps described in connection with the embodiments disclosed herein may be implemented as hardware, software, or combinations of both. Whether implemented in hardware or software depends upon the particular application and design requirements of the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The various illustrative modules described in this specification may be implemented or operated by a general purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array or other programmable logic device, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or other similar configuration.
Embodiments of the present specification also provide a storage medium storing computer program instructions that, when executed, implement: calculating to obtain the amount of the simulated produced tracer according to one sub-fracture data set in the fracture data sets among the target well groups and well site tracer experiment data; wherein the fracture data is used to represent the orientation and attributes of fractures between a target well group; generating a target function according to the amount of the real produced tracer and the amount of the simulated produced tracer; the target function is used for expressing the ratio of the area enclosed by the variation curve of the actually-extracted tracer quantity and the variation curve of the simulated-extracted tracer quantity within a certain time range to the area enclosed by the variation curve of the actually-extracted tracer quantity in a coordinate system; changing the sub-fracture data set to obtain the minimum value of the objective function; and taking the sub-fracture data set corresponding to the minimum value as a fracture screening result.
The functions and effects of the storage medium provided in this embodiment, which are realized when the program instructions thereof are executed, can be explained with reference to other embodiments.
In this embodiment, the storage medium includes, but is not limited to, a Random Access Memory (RAM), a Read-Only Memory (ROM), a Cache (Cache), a Hard Disk Drive (HDD), or a Memory Card (Memory Card).
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may be stored in RAM memory, flash memory, ROM memory, EPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The functions described in the embodiments of the present specification may be implemented in hardware, software, firmware, or any combination of the three. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, such computer-readable media can include, but is not limited to, RAM, ROM, EPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store program code in the form of instructions or data structures and which can be read by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Additionally, any connection is properly termed a computer-readable medium, and, thus, is included if the software is transmitted from a website, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, digital Subscriber Line (DSL), or wirelessly, e.g., infrared, radio, and microwave. Such disks and discs include compact discs, laser discs, optical discs, DVDs, floppy disks and blu-ray discs where disks usually reproduce data magnetically, while disks usually reproduce data optically with lasers. Combinations of the above may also be included in the computer-readable medium.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the device and storage medium embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference may be made to the description of the method embodiments for relevant points.
While the specification has been described with examples, those skilled in the art will appreciate that there are numerous variations and permutations of the specification that do not depart from the spirit of the specification, and it is intended that the appended claims include such variations and modifications that do not depart from the spirit of the specification.
Claims (14)
1. A method of screening fracture data, comprising:
calculating to obtain the amount of the simulated production tracer according to one sub-fracture data set in the fracture data sets among the target well groups and well site tracer experiment data; wherein the fracture data is used to represent the orientation and attributes of fractures between a target well group;
generating a target function according to the amount of the real produced tracer and the amount of the simulated produced tracer; the target function is used for expressing the ratio of the area enclosed by the variation curve of the actually-extracted tracer quantity and the variation curve of the simulated-extracted tracer quantity within a certain time range to the area enclosed by the variation curve of the actually-extracted tracer quantity in a coordinate system;
changing the sub-fracture data set to obtain the minimum value of the objective function; and taking the sub-fracture data set corresponding to the minimum value as a fracture data screening result.
2. The method of claim 1, further comprising:
comparing the well spacing between the target groups of wells to fracture lengths represented by fracture data in the fracture data set;
and extending the fractures with the length of the concentrated fractures being smaller than the well spacing so that the fracture length is larger than the well spacing.
3. The method of claim 1, further comprising screening out fractures from the fracture data that can connect a target well group by spatial movement.
4. The method of claim 1, wherein the amount of simulated production tracer is in accordance with the formula:
calculating, wherein m (t) is the tracer quantity simulated and produced on the t day; c 0 Is the initial concentration of tracer, C i The concentration of tracer A conducted to the monitoring well on the t day of the ith fracture i Denotes the cross-sectional area of the crack,. DELTA.L i Tracer slug length, V, at injection well in the target well group for ith fracture d Total injection volume of tracer in injection well for said target well group, f j The distribution coefficient of the injection water of the injection well to the monitoring well in the target well group can be calculated according to the ratio of the quality of the tracer agent produced by the monitoring well to the quality of the tracer agent injected into the injection well, L i Channel length, v, for connecting two wells of a target well group for the ith fracture i Is the average flow velocity, alpha, of the fluid in the ith fracture i Is the hydrodynamic dispersion of the tracer in the ith fracture, constant, a i The width of the ith slit; b i Opening degree of the ith crack, mu is fluid viscosity, delta P is bottom hole pressure difference between the water injection well and the monitoring well, q i The flow rate of the ith crack.
5. The method of claim 1, wherein the objective function is:
wherein m is j (t)＝C(t)q w (t), m (t) and m j (t) the tracer quantity of the simulated extraction on the t day and the tracer quantity of the real extraction on the t day are respectively; c (t) is the concentration of the actually produced tracer on the t day; q. q.s w (t) the real daily water yield of the crack on the t day; t is time.
6. The method of claim 1, wherein the altering the sub-fracture data set to minimize the objective function comprises:
setting a simulated annealing strategy according to a specified rule;
executing a simulated annealing algorithm according to the simulated annealing strategy to calculate the minimum value of the objective function; and taking the sub-fracture data set corresponding to the minimum value of the objective function as a fracture screening result.
7. The method of claim 6, further comprising:
determining the number range of cracks communicating the target well group according to geological data;
determining a set length range of the sub-fracture data set according to the number range of the fractures; wherein, in the range of the number of the cracks, each number of the cracks corresponds to one set length; the set length is the number of fracture data in the sub-fracture data set;
and selecting a sub-crack data set corresponding to the set length from the crack data set, and screening the sub-crack data set which is corresponding to each crack number and enables the objective function value to be minimum within the range of the crack number according to the simulated annealing rule.
8. The method of claim 7, further comprising:
acquiring the distance between a fracture and the target well group according to the fracture data;
giving a weight value to the fracture data according to the distance between the fracture and the target well group, wherein the weight value is in inverse proportion to the distance between the fracture and the target well group, and the weight value of each piece of fracture data is added to be 1;
and calculating the crack data average weight of the sub-crack data set corresponding to each crack number and enabling the objective function value to be minimum, and screening out the sub-crack data set with the maximum average weight.
9. The method of claim 8, wherein the weight value is according to the formula:
is given by, wherein i Weight of i-th crack, l i The distance from the ith fracture to the center of the perforation section of the target well group.
10. The method of claim 8, wherein the average fracture weight is according to the formula:
and calculating to obtain the result that, wherein,to contain n j An average fracture weight of sub-fracture data of the individual fracture data; w is a i And the weight value of the ith crack data.
11. The method of claim 1 or 8, further comprising translating fractures corresponding to fracture data in the screened sub-fracture data set to connect the target well group.
12. A fracture data screening device, comprising:
a calculation module; the method comprises the steps of calculating to obtain the amount of a simulated production tracer according to one sub-fracture data set in the fracture data sets among target well groups and well site tracer experiment data; wherein the fracture data is used to represent the orientation and attributes of fractures between a target well group;
an objective function generation module; generating an objective function according to the amount of the real produced tracer and the amount of the simulated produced tracer; the target function is used for expressing the ratio of the area enclosed by the variation curve of the actually-extracted tracer quantity and the variation curve of the simulated-extracted tracer quantity within a certain time range to the area enclosed by the variation curve of the actually-extracted tracer quantity in a coordinate system;
a fracture data screening module; for altering the sub-fracture data set to find a minimum of the objective function; and taking the sub-fracture data set corresponding to the minimum value as a fracture screening result.
13. The apparatus of claim 12, wherein the fracture data screening module further comprises:
a crack number determination unit; the system is used for determining the number range of cracks communicating the target well group according to geological data;
a set length determination unit; a set length range for determining the set of sub-fracture data sets from the number range of fractures; wherein, in the range of the number of the cracks, each number of the cracks corresponds to one set length; the set length is the number of fracture data in the sub-fracture data set;
a first screening unit; the sub-crack data sets are used for selecting the sub-crack data sets with the corresponding set lengths from the crack data sets, and the sub-crack data sets which enable the objective function value to be minimum and correspond to each crack number in the range of the crack number are screened out according to the simulated annealing rule;
a weight assignment unit; the fracture data is endowed with a weight value according to the distance between the fracture and the target well group, wherein the weight value is in inverse proportion to the distance between the fracture and the target well group, and the weight values of all the fracture data are added to be 1;
a second screening unit; and the fracture data average weight is used for calculating the fracture data average weight of the sub-fracture data set corresponding to each fracture number and enabling the objective function value to be minimum, and screening out the sub-fracture data set with the maximum average weight.
14. A storage medium storing computer program instructions that, when executed, implement:
calculating to obtain the amount of the simulated produced tracer according to one sub-fracture data set in the fracture data sets among the target well groups and well site tracer experiment data; wherein the fracture data is used to represent the orientation and attributes of the fractures between the target well groups;
generating a target function according to the amount of the real produced tracer and the amount of the simulated produced tracer; the target function is used for expressing the ratio of the area enclosed by the variation curve of the actually-extracted tracer quantity and the variation curve of the simulated-extracted tracer quantity within a certain time range to the area enclosed by the variation curve of the actually-extracted tracer quantity in a coordinate system;
changing the sub-fracture data set to obtain the minimum value of the objective function; and taking the sub-fracture data set corresponding to the minimum value as a fracture screening result.
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