CN112112618A - Fracturing well selection and layer selection method and system based on flow process - Google Patents
Fracturing well selection and layer selection method and system based on flow process Download PDFInfo
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Abstract
The invention belongs to the technical field of well selection and stratum selection of oil fields, and discloses a fracturing well selection and stratum selection method and system based on a process, wherein the fracturing well selection and stratum selection system based on the process comprises the following steps: the device comprises a reservoir thickness detection module, a pore detection module, a permeability detection module, a gas saturation detection module, a mud content detection module, a central processing module, a database establishment module, a fracturing influence analysis module, a fracturing comprehensive evaluation module, a fracturing effect prediction module, a signal transmission module, a mobile terminal and a display module. The fracturing well selection and stratum selection method based on the process can acquire various data related to oil and gas wells, and improve the effective rate and the success rate of fracturing; meanwhile, the fracturing influence analysis module analyzes the fracturing influence factors according to the data in the database; the fracturing comprehensive evaluation module determines a fracturing comprehensive evaluation result according to the fracturing influence factors; the method can also carry out effective and correct evaluation on fracturing well selection in all aspects.
Description
Technical Field
The invention belongs to the technical field of well selection and stratum selection of oil fields, and particularly relates to a fracturing well selection and stratum selection method and system based on flow.
Background
Currently, an oil and gas field refers to the sum of an oil reservoir, a gas reservoir, and an oil and gas reservoir within the same area controlled by a single local structural unit. If only oil reservoirs exist in the local construction range, the local construction range is called an oil field; only the reservoir is known as the field. Fracturing is a main measure for realizing yield increase of oil and gas fields, and is a system engineering, and comprises fracturing well selection, stratum evaluation before fracturing, fracturing optimization design, after fracturing effect prediction and the like. Many studies have been made on pre-fracturing formation evaluation, fracture optimization design, and post-fracturing effect prediction, creating a variety of models.
The good or bad fracturing well selection is the precondition of successful and effective fracturing of the oil-gas field, and plays a key role in improving the effective rate and the success rate of fracturing. The fracturing needs to obtain a good effect, and a proper well layer is selected firstly, so that the yield can be increased after the construction, and good economic benefit is obtained. However, the fracturing effect is affected by various factors, such as the effective thickness and the effective permeability of the fracturing layer, the relationship between various factors and the fracturing effect is complex, and different factors have different influences on the fracturing effect. However, the existing fracturing well selection layer selection method cannot acquire comprehensive data, so that the accuracy of fracturing well selection is reduced, and comprehensive evaluation of fracturing is influenced.
Through the above analysis, the problems and defects of the prior art are as follows: the existing fracturing well selection layer selection method cannot acquire comprehensive data, so that the accuracy of fracturing well selection is reduced, and comprehensive evaluation of fracturing is influenced.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a fracturing well selection layer selection method and system based on flow.
The invention is realized in such a way that the fracturing well selection layer selection method based on the process comprises the following steps:
the method comprises the following steps that firstly, rock stratum characteristics are obtained and the thickness of a reservoir stratum is determined through a reservoir stratum thickness detection module by utilizing a reservoir stratum thickness detection device according to logging data; detecting the porosity of the wellhead pressing by using a sound wave detector through a pore detection module;
secondly, determining the permeability of the rock stratum by using permeability detection equipment through a permeability detection module under certain pressure of the fluid; detecting the natural gas saturation in the rock layer by using resistivity detection equipment through a gas saturation detection module;
thirdly, detecting the shale content in the rock by using a special flexibility detection device through a shale content detection module; the normal operation of each module of the fracturing well selection and stratum selection system based on the process is coordinated and controlled by a central processing module through a central processor;
step four, a database building module builds a corresponding database according to the detected data by using a database building program, and stores the corresponding data;
step five, optimizing the fracturing well layers by adopting a fuzzy decision method, measuring each index of each well layer, and determining fracturing influence factors according to the sequence of candidate well layers according to actual conditions and specific requirements and the quality; the fracture influencing factors include: well pattern defects, small reservoir thickness, large water content in rock strata;
step six, selecting a variable to be analyzed each time, carrying out sensitivity analysis on fracturing influence factors by utilizing an influence analysis program through a fracturing influence analysis module according to data in a database, selecting a well with complete data as a sample, establishing a relational expression of analysis variables and independent variables, inspecting the relation between the analysis variables and the single variables, and determining main factors influencing the fracturing effect;
step seven, performing normalization treatment on the main factors of each fracturing effect by using a comprehensive evaluation program through a fracturing comprehensive evaluation module, calculating an evaluation matrix and the weight of each fracturing influence factor, and calculating to obtain a fracturing comprehensive evaluation result;
step eight, acquiring prediction data of the repeated fracturing effect of each well layer based on Meyer software simulation; accumulating the plurality of influence factor data sequences and the prediction data sequences for a plurality of times respectively to obtain monotonously rising accumulated influence factor data sequences and accumulated prediction data sequences with exponential characteristics respectively;
step nine, constructing a data prediction model combining a fracturing comprehensive evaluation result and main influence factors by using a data mining algorithm based on a grey theory, a numerical differentiation method and a least square method according to the accumulated influence factor data sequence and the accumulated prediction data sequence through a fracturing effect prediction module, and predicting the fracturing effect at the later stage by using the data prediction model;
step ten, transmitting the detected data to the mobile terminal by using a signal transmitter through a signal transmission module; realizing the remote monitoring data by using the mobile terminal through the terminal module;
and eleventh, displaying the detected real-time data of the reservoir thickness, the pore space, the permeability, the gas saturation, the shale content, the fracturing influence analysis result, the fracturing comprehensive evaluation result and the fracturing effect prediction information by using a display through a display module.
Further, in the first step, the method for determining the reservoir thickness by the reservoir thickness detection module is as follows: detecting data of a wellhead stratum and determining characteristics of the stratum; and determining the thickness of the reservoir according to the characteristics of the rock stratum and the oil and gas standard.
Further, in the first step, the method for detecting the porosity of the wellhead by the pore detection module by using the acoustic wave detector comprises:
(i) sending out ultrasonic waves at different angles by using a sound wave probe;
(ii) and comparing the amplitudes of the scattering signals at different angles at the vertical position with the minimum amplitudes at other angles to establish the relation between the ratio and the porosity.
Further, in the third step, the method for classifying the rocks according to the hardness of the rocks in the process that the shale content detection module detects the shale content in the rocks by using the special flexibility detection equipment comprises the following steps:
15-20 parts of extremely firm rock f, firm granite, limestone and quartzite;
hard rock f is 8-10, not firm granite and firm sandstone;
medium firm rock f is 4-6, common sandstone and iron ore;
and (3) the weak rock f is 0.8-3, and loess.
Further, in the seventh step, the method for calculating the evaluation matrix by normalizing the main factors of each fracturing effect by the fracturing comprehensive evaluation module by using the comprehensive evaluation program comprises the following steps:
(I) normalization of the index system, due to Bi∈[Ai，Ci]The larger the index is, the better the type is, the following are:
the smaller the index, the better the type, the following are:
wherein, i-index number, i ═ 1, 2.., n;
(II) calculating an evaluation level vector V:
V＝[v1，v2，v3，......，vm]2；
wherein j represents the number of evaluation levels, and j is 1, 2.
Calculating an evaluation matrix R:
wherein r isijIndicates the likelihood that an item is evaluated for index i only, the item belongs to level j, rij＝1-|xi-vjL, |; i represents the index number, i is 1, 2. j represents the number of evaluation levels, and j is 1, 2.
Further, in the seventh step, the method for calculating the weight of each fracturing influence factor and simultaneously calculating the comprehensive fracturing evaluation result includes:
multiplying the weight vector W by an evaluation matrix R to obtain an evaluation vector S:
S＝W·R＝[s1，s2，s3，...，sm]T；
wherein S isiRepresenting an evaluation vector;
j＝1，2，...，m；
according to the evaluation level vector V ═ V1，v2，v3，......，vm]TAnd the evaluation vector S ═ S1，s2，s3，...，sm]TAnd obtaining a comprehensive evaluation result D by the following calculation formula:
and the interval where the D value is located is the fracturing comprehensive evaluation result.
Further, in the ninth step, the fracturing effect prediction module constructs a data prediction model combining a fracturing comprehensive evaluation result and main influence factors according to the accumulated influence factor data sequence and the accumulated prediction data sequence by using a data mining algorithm based on a gray theory, a numerical differentiation method and a least square method, wherein the accumulated influence factor data sequence and the prediction data sequence are as follows:
wherein x isi (J)(nk) For the predicted data sequence after J times of accumulation, ul (J)(nk) For the predicted data sequence after J times of accumulation, nkThe k-th influencing factor data or the predicted data, s is a unit, I is 1,2, …, I; k is 1,2, …, K; 1,2, …, L;
the data prediction model combining the comprehensive fracturing evaluation result and the main influence factors is as follows:
X(J)(nk+1)＝A1X(J)(nk)+BU(J)(nk+1)；
wherein, X(J)(nk+1) And X(J)(n) is k +1 and the fracturing effect output value at the moment k, A1Is a matrix of n times n orders, B is a matrix of m times n orders, U(J)(nk+1) Is an input value of a fracturing effect influence factor at the k +1 moment, nk+1Representing the (k + 1) th influencing factor data or prediction data, nkRepresenting the kth influencing factor data or the prediction data.
Another object of the present invention is to provide a fracturing well selection system based on a process for implementing the fracturing well selection method based on a process, which includes:
the reservoir thickness detection module is connected with the central processing module and used for obtaining rock stratum characteristics and determining reservoir thickness according to the logging data through the reservoir thickness detection device;
the pore detection module is connected with the central processing module and is used for detecting the porosity of the wellhead pressing through the acoustic detector;
the permeability detection module is connected with the central processing module and is used for measuring the permeability of the rock stratum through permeability detection equipment under certain pressure of fluid;
the gas saturation detection module is connected with the central processing module and used for detecting the natural gas saturation in the rock stratum through the resistivity detection equipment;
the mud content detection module is connected with the central processing module and is used for detecting the mud content in the rock through special flexibility detection equipment;
the central processing module is respectively connected with the reservoir thickness detection module, the pore detection module, the permeability detection module, the gas saturation detection module, the mud content detection module, the database establishment module, the fracturing influence analysis module, the fracturing comprehensive evaluation module, the fracturing effect prediction module, the signal transmission module, the mobile terminal and the display module, and is used for coordinating and controlling the normal operation of each module of the fracturing well selection and stratum selection system based on the process through the central processing unit;
the database establishing module is connected with the central processing module and used for establishing a corresponding database according to the detected data through a database establishing program and storing the corresponding data;
the fracturing influence analysis module is connected with the central processing module and used for analyzing the fracturing influence factors according to the data in the database through an influence analysis program;
the comprehensive fracturing evaluation module is connected with the central processing module and used for determining a comprehensive fracturing evaluation result according to fracturing influence factors through a comprehensive evaluation program;
the fracturing effect prediction module is connected with the central processing module and used for predicting the fracturing effect in the later period through an effect prediction program according to the data in the database, the fracturing influence factors and the fracturing comprehensive evaluation;
the signal transmission module is connected with the central processing module and is used for transmitting the detected data to the mobile terminal through the signal transmitter;
the terminal module is connected with the central processing module and used for realizing the remote monitoring data through the mobile terminal;
and the display module is connected with the central processing module and used for displaying the detected real-time data of the reservoir thickness, the pore space, the permeability, the gas saturation, the shale content, the fracturing influence analysis result, the fracturing comprehensive evaluation result and the fracturing effect prediction information through the display.
It is another object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the method for selecting a well based on a flow process when executed on an electronic device.
It is another object of the present invention to provide a computer readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method for selecting a well based on a flow process.
By combining all the technical schemes, the invention has the advantages and positive effects that: according to the fracturing well selection and stratum selection system based on the process, rock stratum characteristics are obtained through the data of well logging through the reservoir stratum thickness detection module, and the reservoir stratum thickness is determined. The pore detection module detects the porosity of the wellhead pressing through the acoustic detector. The permeability detection module measures permeability of the formation through the fluid under a certain pressure. The gas saturation detection module detects the natural gas saturation in the rock layer by using resistivity detection equipment. The argillaceous content detection module utilizes special flexibility check out test set to detect the argillaceous content in the rock. The invention can obtain various data related to oil and gas wells, and improves the effective rate and the success rate of fracturing. Meanwhile, the database establishing module establishes a corresponding database according to the detected data. And the fracturing influence analysis module analyzes the fracturing influence factors according to the data in the database. And the fracturing comprehensive evaluation module determines a fracturing comprehensive evaluation result according to the fracturing influence factors. And the fracturing effect prediction module predicts the later fracturing effect according to the data in the database, the fracturing influence factors and the fracturing comprehensive evaluation. Meanwhile, the method can carry out effective and correct evaluation on the fracturing well selection in all aspects.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flow chart of a fracturing well selection method based on flow chart according to an embodiment of the invention.
FIG. 2 is a block diagram of a flow-based fracturing well selection layer system according to an embodiment of the present invention;
in the figure: 1. a reservoir thickness detection module; 2. a pore detection module; 3. a permeability detection module; 4. a gas saturation detection module; 5. a argillaceous content detection module; 6. a central processing module; 7. a database establishing module; 8. a fracture impact analysis module; 9. a comprehensive fracturing evaluation module; 10. a fracturing effect prediction module; 11. a signal transmission module; 12. a mobile terminal; 13. and a display module.
FIG. 3 is a flow chart of a method for detecting the porosity of a wellhead by a pore detection module using an acoustic detector according to an embodiment of the invention.
Fig. 4 is a flowchart of a method for analyzing the fracture influence factor according to the data in the database by using an influence analysis program through the fracture influence analysis module according to an embodiment of the present invention.
Fig. 5 is a flowchart of a method for predicting a later-stage fracturing effect according to data in a database, fracturing influencing factors and fracturing comprehensive evaluation by using an effect prediction program through a fracturing effect prediction module according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In view of the problems in the prior art, the present invention provides a fracturing well-selecting layer-selecting system and method based on flow process, which will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, a fracturing well selection method based on a flow process provided by an embodiment of the present invention includes the following steps:
s101, obtaining rock stratum characteristics and determining reservoir thickness by a reservoir thickness detection module through a reservoir thickness detection device according to logging data; detecting the porosity of the wellhead pressing by using a sound wave detector through a pore detection module;
s102, under a certain pressure, determining the permeability of the rock stratum by a permeability detection module by using permeability detection equipment; detecting the natural gas saturation in the rock layer by using resistivity detection equipment through a gas saturation detection module;
s103, detecting the shale content in the rock by using a special flexibility detection device through a shale content detection module; the normal operation of each module of the fracturing well selection and stratum selection system based on the process is coordinated and controlled by a central processing module through a central processor;
s104, establishing a corresponding database according to the detected data by using a database establishing program through a database establishing module, and storing the corresponding data; analyzing the fracturing influence factors according to the data in the database by utilizing an influence analysis program through a fracturing influence analysis module;
s105, determining a fracturing comprehensive evaluation result according to fracturing influence factors by utilizing a fracturing comprehensive evaluation module through a comprehensive evaluation program;
s106, predicting the fracturing effect at the later stage by using an effect prediction program through a fracturing effect prediction module according to the data in the database, the fracturing influence factors and the fracturing comprehensive evaluation;
s107, transmitting the detected data to the mobile terminal by using the signal transmitter through the signal transmission module; realizing the remote monitoring data by using the mobile terminal through the terminal module;
and S108, displaying the detected real-time data of the reservoir thickness, the pore space, the permeability, the gas saturation, the shale content, the fracturing influence analysis result, the fracturing comprehensive evaluation result and the fracturing effect prediction information by using a display through a display module.
As shown in fig. 2, a fracturing well selection system based on flow process provided by an embodiment of the present invention includes: the device comprises a reservoir thickness detection module 1, a pore detection module 2, a permeability detection module 3, a gas saturation detection module 4, a mud content detection module 5, a central processing module 6, a database establishment module 7, a fracturing influence analysis module 8, a fracturing comprehensive evaluation module 9, a fracturing effect prediction module 10, a signal transmission module 11, a mobile terminal 12 and a display module 13.
The reservoir thickness detection module 1 is connected with the central processing module 6 and used for obtaining rock stratum characteristics and determining reservoir thickness according to the logging data through a reservoir thickness detection device;
the pore detection module 2 is connected with the central processing module 6 and is used for detecting the porosity of the wellhead pressing through the acoustic detector;
the permeability detection module 3 is connected with the central processing module 6 and is used for measuring the permeability of the rock stratum through permeability detection equipment under certain pressure of fluid;
the gas saturation detection module 4 is connected with the central processing module 6 and used for detecting the natural gas saturation in the rock stratum through resistivity detection equipment;
the argillaceous content detection module 5 is connected with the central processing module 6 and is used for detecting the argillaceous content in the rock through special flexibility detection equipment;
the central processing module 6 is respectively connected with the reservoir thickness detection module 1, the pore detection module 2, the permeability detection module 3, the gas saturation detection module 4, the mud content detection module 5, the database establishment module 7, the fracturing influence analysis module 8, the fracturing comprehensive evaluation module 9, the fracturing effect prediction module 10, the signal transmission module 11, the mobile terminal 12 and the display module 13, and is used for coordinating and controlling the normal operation of each module of the fracturing well selection and stratum selection system based on the process through a central processing unit;
the database establishing module 7 is connected with the central processing module 6 and used for establishing a corresponding database according to the detected data through a database establishing program and storing the corresponding data;
the fracturing influence analysis module 8 is connected with the central processing module 6 and is used for analyzing the fracturing influence factors according to the data in the database through an influence analysis program;
the fracturing comprehensive evaluation module 9 is connected with the central processing module 6 and used for determining a fracturing comprehensive evaluation result according to fracturing influence factors through a comprehensive evaluation program;
the fracturing effect prediction module 10 is connected with the central processing module 6 and used for predicting the fracturing effect in the later period through an effect prediction program according to the data in the database, the fracturing influence factors and the fracturing comprehensive evaluation;
the signal transmission module 11 is connected with the central processing module 6 and used for transmitting the detected data to the mobile terminal through the signal transmitter;
the terminal module 12 is connected with the central processing module 6 and used for realizing the remote monitoring data through the mobile terminal;
and the display module 13 is connected with the central processing module 6 and used for displaying the detected real-time data of the reservoir thickness, the pore space, the permeability, the gas saturation, the shale content, the fracturing influence analysis result, the fracturing comprehensive evaluation result and the fracturing effect prediction information through a display.
The technical solution of the present invention is further described with reference to the following specific examples.
Example 1
As shown in fig. 1 and fig. 3 as a preferred embodiment, the method for detecting the porosity of a fracture well by using an acoustic detector through a pore detection module according to an embodiment of the present invention includes:
s201, sending out ultrasonic waves at different angles by using an acoustic wave probe;
s202, comparing the amplitudes of the scattered signals at different angles at the vertical position with the minimum amplitudes at other angles, and establishing the relation between the ratio and the porosity.
Example 2
The fracturing well selection and stratum selection method based on the process is shown in fig. 1, as a preferred embodiment, as shown in fig. 4, the method for analyzing the fracturing influence factors by using the influence analysis program through the fracturing influence analysis module according to the data in the database includes:
s301, optimizing the fracturing well layers by adopting a fuzzy decision method, measuring each index of each well layer, and determining fracturing influence factors according to the sequence of candidate well layers according to actual conditions and specific requirements;
s302, selecting a variable to be analyzed each time, and carrying out sensitivity analysis on fracture influence factors by utilizing an influence analysis program through a fracture influence analysis module according to data in a database;
and S303, selecting a well with complete data as a sample, establishing a relational expression of analysis variables and independent variables, inspecting the relation between the analysis variables and a single variable, and determining main factors influencing the fracturing effect.
The fracturing influencing factors provided by the embodiment of the invention comprise: well pattern defects, small reservoir thickness, and large water content in the rock stratum.
Example 3
The fracturing well selection and layer selection method based on the process is shown in fig. 1, as a preferred embodiment, as shown in fig. 5, the method for predicting the fracturing effect at the later stage by using an effect prediction program through a fracturing effect prediction module according to data, fracturing influence factors and fracturing comprehensive evaluation in a database comprises the following steps:
s401, collecting prediction data of the repeated fracturing effect of each well layer based on Meyer software simulation; accumulating the plurality of influence factor data sequences and the prediction data sequences for a plurality of times respectively to obtain monotonously rising accumulated influence factor data sequences and accumulated prediction data sequences with exponential characteristics respectively;
s402, constructing a data prediction model combining a fracturing comprehensive evaluation result and main influence factors by using a data mining algorithm based on a grey theory, a numerical differentiation method and a least square method according to the accumulated influence factor data sequence and the accumulated prediction data sequence through a fracturing effect prediction module, and predicting the fracturing effect in the later period by using the data prediction model.
The accumulated data sequence of the influence factors and the data sequence of the prediction provided by the embodiment of the invention are as follows:
wherein x isi (J)(nk) For the predicted data sequence after J times of accumulation, ul (J)(nk) For the predicted data sequence after J times of accumulation, nkThe k-th influencing factor data or the predicted data, s is a unit, I is 1,2, …, I; k is 1,2, …, K; l ═ 1,2, …, L.
The data prediction model combining the fracturing comprehensive evaluation result and the main influence factors provided by the embodiment of the invention is as follows:
X(J)(nk+1)＝A1X(J)(nk)+BU(J)(nk+1)；
wherein, X(J)(nk+1) And X(J)(n) is k +1 and the fracturing effect output value at the moment k, A1Is a matrix of n times n orders, B is a matrix of m times n orders, U(J)(nk+1) Is an input value of a fracturing effect influence factor at the k +1 moment, nk+1Representing the (k + 1) th influencing factor data or prediction data, nkRepresenting the kth influencing factor data or the prediction data.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. The fracturing well selection layer selection method based on the process is characterized by comprising the following steps of:
the method comprises the following steps that firstly, rock stratum characteristics are obtained and the thickness of a reservoir stratum is determined through a reservoir stratum thickness detection module by utilizing a reservoir stratum thickness detection device according to logging data; detecting the porosity of the wellhead pressing by using a sound wave detector through a pore detection module;
secondly, determining the permeability of the rock stratum by using permeability detection equipment through a permeability detection module under certain pressure of the fluid; detecting the natural gas saturation in the rock layer by using resistivity detection equipment through a gas saturation detection module;
thirdly, detecting the shale content in the rock by using a special flexibility detection device through a shale content detection module; the normal operation of each module of the fracturing well selection and stratum selection system based on the process is coordinated and controlled by a central processing module through a central processor;
step four, a database building module builds a corresponding database according to the detected data by using a database building program, and stores the corresponding data;
step five, optimizing the fracturing well layers by adopting a fuzzy decision method, measuring each index of each well layer, and determining fracturing influence factors according to the sequence of candidate well layers according to actual conditions and specific requirements and the quality; the fracture influencing factors include: well pattern defects, small reservoir thickness, large water content in rock strata;
step six, selecting a variable to be analyzed each time, carrying out sensitivity analysis on fracturing influence factors by utilizing an influence analysis program through a fracturing influence analysis module according to data in a database, selecting a well with complete data as a sample, establishing a relational expression of analysis variables and independent variables, inspecting the relation between the analysis variables and the single variables, and determining main factors influencing the fracturing effect;
step seven, performing normalization treatment on the main factors of each fracturing effect by using a comprehensive evaluation program through a fracturing comprehensive evaluation module, calculating an evaluation matrix and the weight of each fracturing influence factor, and calculating to obtain a fracturing comprehensive evaluation result;
step eight, acquiring prediction data of the repeated fracturing effect of each well layer based on Meyer software simulation; accumulating the plurality of influence factor data sequences and the prediction data sequences for a plurality of times respectively to obtain monotonously rising accumulated influence factor data sequences and accumulated prediction data sequences with exponential characteristics respectively;
step nine, constructing a data prediction model combining a fracturing comprehensive evaluation result and main influence factors by using a data mining algorithm based on a grey theory, a numerical differentiation method and a least square method according to the accumulated influence factor data sequence and the accumulated prediction data sequence through a fracturing effect prediction module, and predicting the fracturing effect at the later stage by using the data prediction model;
step ten, transmitting the detected data to the mobile terminal by using a signal transmitter through a signal transmission module; realizing the remote monitoring data by using the mobile terminal through the terminal module;
and eleventh, displaying the detected real-time data of the reservoir thickness, the pore space, the permeability, the gas saturation, the shale content, the fracturing influence analysis result, the fracturing comprehensive evaluation result and the fracturing effect prediction information by using a display through a display module.
2. The method for selecting a well from a fracturing well based on the process flow as claimed in claim 1, wherein in the first step, the method for determining the thickness of the reservoir by the reservoir thickness detection module is as follows: detecting data of a wellhead stratum and determining characteristics of the stratum; and determining the thickness of the reservoir according to the characteristics of the rock stratum and the oil and gas standard.
3. The method for selecting a well based on the fracturing of the flow path of claim 1, wherein in the first step, the method for detecting the porosity of the well head by the pore detection module through the acoustic detector comprises the following steps:
(i) sending out ultrasonic waves at different angles by using a sound wave probe;
(ii) and comparing the amplitudes of the scattering signals at different angles at the vertical position with the minimum amplitudes at other angles to establish the relation between the ratio and the porosity.
4. The fracturing well selection layer selection method based on the flow process of claim 1, wherein in the third step, in the process of detecting the shale content in the rock by the shale content detection module by using a special flexibility detection device, the method for grading the rock according to the hardness of the rock comprises the following steps:
15-20 parts of extremely firm rock f, firm granite, limestone and quartzite;
hard rock f is 8-10, not firm granite and firm sandstone;
medium firm rock f is 4-6, common sandstone and iron ore;
and (3) the weak rock f is 0.8-3, and loess.
5. The fracturing well selection and stratum selection method based on the process flow as claimed in claim 1, wherein in the seventh step, the method for calculating the evaluation matrix by using the comprehensive evaluation program to perform normalization processing on the main factors of each fracturing effect through the comprehensive evaluation module for fracturing comprises the following steps:
(I) normalization of the index system, due to Bi∈[Ai，Ci]The larger the index is, the better the type is, the following are:
the smaller the index, the better the type, the following are:
wherein, i-index number, i is 1,2, …, n;
(II) calculating an evaluation level vector V:
V＝[v1，v2，v3，......，vm]T；
wherein j represents the number of evaluation levels, and j is 1,2, …, m;
calculating an evaluation matrix R:
wherein r isijIndicates the likelihood that an item is evaluated for index i only, the item belongs to level j, rij＝1-|xi-vjL, |; i represents the index number, i is 1,2, …, n; j represents the number of evaluation levels, and j is 1,2, …, m.
6. The fracturing well selection and layer selection method based on the process as claimed in claim 1, wherein in the seventh step, the method for calculating the weight of each fracturing influence factor and simultaneously calculating the comprehensive fracturing evaluation result comprises the following steps:
multiplying the weight vector W by an evaluation matrix R to obtain an evaluation vector S:
S＝W·R＝[s1，s2，s3，...，sm]T；
wherein S isiRepresenting an evaluation vector;
according to the evaluation level vector V ═ V1，v2，v3，......，vm]TAnd the evaluation vector S ═ S1，s2，s3，...，sm]TAnd obtaining a comprehensive evaluation result D by the following calculation formula:
and the interval where the D value is located is the fracturing comprehensive evaluation result.
7. The fracturing well selection and layer selection method based on the process flow of claim 1, wherein in the ninth step, the fracturing effect prediction module constructs a data prediction model combining a fracturing comprehensive evaluation result and main influence factors according to the accumulated influence factor data sequence and the accumulated prediction data sequence by using a data mining algorithm based on a gray theory, a numerical differentiation method and a least square method, wherein the accumulated influence factor data sequence and the prediction data sequence are as follows:
wherein x isi (J)(nk) For the predicted data sequence after J times of accumulation, ul (J)(nk) For the predicted data sequence after J times of accumulation, nkThe k-th influencing factor data or the predicted data, s is a unit, I is 1,2, …, I; k is 1,2, …, K; 1,2, …, L;
the data prediction model combining the comprehensive fracturing evaluation result and the main influence factors is as follows:
X(J)(nk+1)＝A1X(J)(nk)+BU(J)(nk+1)；
wherein, X(J)(nk+1) And X(J)(n) is k +1 and the fracturing effect output value at the moment k, A1Is a matrix of n times n orders, B is a matrix of m times n orders, U(J)(nk+1) Is an input value of a fracturing effect influence factor at the k +1 moment, nk+1Representing the (k + 1) th influencing factor data or prediction data, nkRepresenting the kth influencing factor data or the prediction data.
8. A flowsheet-based frac well selection system for implementing the flowsheet-based frac well selection method of any of claims 1 to 7, wherein the flowsheet-based frac well selection system comprises:
the reservoir thickness detection module is connected with the central processing module and used for obtaining rock stratum characteristics and determining reservoir thickness according to the logging data through the reservoir thickness detection device;
the pore detection module is connected with the central processing module and is used for detecting the porosity of the wellhead pressing through the acoustic detector;
the permeability detection module is connected with the central processing module and is used for measuring the permeability of the rock stratum through permeability detection equipment under certain pressure of fluid;
the gas saturation detection module is connected with the central processing module and used for detecting the natural gas saturation in the rock stratum through the resistivity detection equipment;
the mud content detection module is connected with the central processing module and is used for detecting the mud content in the rock through special flexibility detection equipment;
the central processing module is respectively connected with the reservoir thickness detection module, the pore detection module, the permeability detection module, the gas saturation detection module, the mud content detection module, the database establishment module, the fracturing influence analysis module, the fracturing comprehensive evaluation module, the fracturing effect prediction module, the signal transmission module, the mobile terminal and the display module, and is used for coordinating and controlling the normal operation of each module of the fracturing well selection and stratum selection system based on the process through the central processing unit;
the database establishing module is connected with the central processing module and used for establishing a corresponding database according to the detected data through a database establishing program and storing the corresponding data;
the fracturing influence analysis module is connected with the central processing module and used for analyzing the fracturing influence factors according to the data in the database through an influence analysis program;
the comprehensive fracturing evaluation module is connected with the central processing module and used for determining a comprehensive fracturing evaluation result according to fracturing influence factors through a comprehensive evaluation program;
the fracturing effect prediction module is connected with the central processing module and used for predicting the fracturing effect in the later period through an effect prediction program according to the data in the database, the fracturing influence factors and the fracturing comprehensive evaluation;
the signal transmission module is connected with the central processing module and is used for transmitting the detected data to the mobile terminal through the signal transmitter;
the terminal module is connected with the central processing module and used for realizing the remote monitoring data through the mobile terminal;
and the display module is connected with the central processing module and used for displaying the detected real-time data of the reservoir thickness, the pore space, the permeability, the gas saturation, the shale content, the fracturing influence analysis result, the fracturing comprehensive evaluation result and the fracturing effect prediction information through the display.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for implementing a flowsheet based fracturing well selection method as claimed in any one of claims 1 to 7 when executed on an electronic device.
10. A computer readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method of flowsheet based frac well selection as claimed in any one of claims 1 to 7.
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