阅读说明：本技术 一种压裂缝内支撑剂铺置效果综合评价方法 (Comprehensive evaluation method for proppant laying effect in fracturing ) 是由 李小刚 陈浩 杨兆中 廖梓佳 朱静怡 杜博迪 于 2021-08-06 设计创作，主要内容包括：本发明公开了一种压裂缝内支撑剂铺置效果综合评价方法,包括如下步骤：利用平板狭缝输砂装置对不同实验参数下支撑剂铺置形态进行模拟,获取支撑剂铺置效果评价参数；建立层次结构模型及判断矩阵A(I)；引入转移矩阵D,获得一致性优化判断矩阵A(II)；计算权重向量ω并进行一致性检验；建立因素集U、评价集V；建立铺置效果评价模糊矩阵A(Ⅲ)；建立缝内支撑剂铺置效果综合评价模型,对平板狭缝输砂实验条件下缝内支撑剂铺置效果进行综合评价。本发明基于改进层次分析法构建支撑剂铺置效果综合评价模型,可定量表征平板狭缝输砂实验中支撑剂铺置效果,为支撑剂材料优选及施工参数优化提供一定的参考。(The invention discloses a comprehensive evaluation method for the laying effect of a propping agent in a fracturing fracture, which comprises the following steps: simulating the laying form of the proppant under different experimental parameters by using a flat slit sand conveying device to obtain the evaluation parameters of the laying effect of the proppant; establishing a hierarchical structure model and a judgment matrix A (I); introducing a transfer matrix D to obtain a consistency optimization judgment matrix A (II); calculating a weight vector omega and carrying out consistency check; establishing a factor set U and an evaluation set V; establishing a paving effect evaluation fuzzy matrix A (III); and establishing a comprehensive evaluation model of the paving effect of the intra-slit proppant, and comprehensively evaluating the paving effect of the intra-slit proppant under the flat plate slit sand conveying experiment condition. The comprehensive evaluation model for the spreading effect of the proppant is constructed based on the improved analytic hierarchy process, the spreading effect of the proppant in the flat plate slit sand conveying experiment can be quantitatively represented, and certain reference is provided for the optimization of proppant materials and the optimization of construction parameters.)

1. A comprehensive evaluation method for the laying effect of a propping agent in a fracturing fracture is characterized by comprising the following steps:

s10, simulating the laying form of the proppant under different experimental parameters by using a flat slit sand conveying device to obtain the evaluation parameters of the laying effect of the proppant;

step S20, establishing a hierarchical structure model and a judgment matrix A (I);

step S30, introducing a transfer matrix D to obtain a consistency optimization judgment matrix A (II);

step S40, calculating a weight vector omega and carrying out consistency check;

step S50, establishing a factor set U and an evaluation set V;

step S60, establishing a paving effect evaluation fuzzy matrix A (III);

and S70, establishing a comprehensive evaluation model of the paving effect of the intra-slit proppant, and comprehensively evaluating the paving effect of the intra-slit proppant under the flat plate slit sand conveying experiment condition.

2. The method for comprehensively evaluating the proppant placement effect in the fracturing according to claim 1, wherein the evaluation parameters in the step S10 include: the distance of the front edge of the sand bank, the gradient of the front edge of the sand bank, the length of the sand bank and the height of the sand bank; the acquisition method comprises the following steps: the method comprises the steps of video recording of a flat plate slit sand conveying experiment process, intercepting of a balance time characteristic image, binarization processing of the balance time characteristic image to obtain a propping agent laying form gray level image, guiding of the gray level image into graphic processing software, extraction of a sand bank outline by means of a spline curve, calculation and statistics of evaluation parameter values.

3. The method for comprehensively evaluating the proppant placement effect in a fracture according to claim 1, wherein the judgment matrix a (i) in step S20 is:

in the formula: a (I) represents a judgment matrix; a is_ijRepresenting the relative importance of the evaluation parameter i relative to the evaluation parameter j; i. j sequentially represents the length of the sand bank, the height of the sand bank, the distance of the front edge of the sand bank and the gradient of the front edge of the sand bank.

4. The method for comprehensively evaluating the proppant placement effect in a fracture according to claim 1, wherein the transfer matrix D and the consistency optimization judgment matrix a (ii) in step S30 are:

in the formula: d represents a transition matrix; d_ijRepresenting elements in a transition matrix; a is_ik，a_jkRepresenting that k corresponds to elements in the judgment matrix A (I) when k takes different values; a (II) represents a consistency optimization judgment matrix;representing the relative importance of the evaluation parameter i relative to the evaluation parameter j after consistency optimization; i. j sequentially represents the length of the sand bank, the height of the sand bank, the distance of the front edge of the sand bank and the gradient of the front edge of the sand bank.

5. The method for comprehensively evaluating the proppant placement effect in the fracture according to claim 1, wherein the weight vector ω in step S40 is the maximum eigenvector of the consistency optimization judgment matrix a (ii) calculated by the sum-product method, and the consistency check equation is as follows:

in the formula: CI represents a calculation consistency index; lambda [ alpha ]_maxRepresenting the maximum eigenvalue of the judgment matrix; n represents the order of the judgment matrix; CR represents a check coefficient, with values closer to 0 indicating better consistency; RI represents a random consistency index, and when n is 4, RI is 0.9.

6. The method for comprehensively evaluating the proppant placement effect in a fracturing fracture according to claim 1, wherein the factor set U and the evaluation set V in the step S50 are as follows:

in the formula: u represents a factor set; v denotes the evaluation set.

7. The method for comprehensively evaluating the spreading effect of the proppant in the fracturing according to claim 1, wherein the fuzzy matrix A (III) of the spreading effect in the step S60 is as follows:

in the formula: a (III) represents a tiling effect fuzzy matrix; r_mjAnd representing the membership of the jth element in the factor set to the mth element in the evaluation set.

8. The comprehensive evaluation method for the proppant placement effect in the fracturing fracture according to claim 7, wherein the membership calculation equation is as follows:

in the formula: r represents a degree of membership; x represents an evaluation parameter value; x_maxRepresents the maximum value of the evaluation parameter; x_minRepresents the minimum value of the evaluation parameter.

9. The method for comprehensively evaluating the spreading effect of the proppant in the fracturing fracture according to claim 1, wherein the model for comprehensively evaluating the spreading effect of the proppant in the fracture in step S70 is:

in the formula: SI represents a sanding index which can reflect the paving effect of the proppant in the fracture; ω denotes a weight vector of the evaluation parameter.

Technical Field

The invention relates to a comprehensive evaluation method for the laying effect of a propping agent in a fracturing fracture, and relates to the technical field of oil and gas field development.

Background

Hydraulic fracturing technology is a key technical measure to achieve conventional oil and gas production and unconventional oil and gas commercial development. The fracture network formed by the fracturing is a high-speed path for the seepage of oil and gas from the formation to the wellbore. The effectiveness of hydraulic fracturing depends largely on whether the fracture is being effectively filled. Therefore, it is important to study the proppant transport in the fractured fracture. The method is an important way for researching the laying rule of the proppant in the fracturing fracture at present. The method comprises the following steps of (1) aiming at the proppant paving form evaluation in a flat slit sand conveying experiment, wherein one parameter evaluation system comprises two parameter evaluation systems, namely a single parameter evaluation system adopting sand bank balance time, balance height, sand bank length, support area, effective filling volume and the like; the other is a multi-parameter evaluation system in which single parameters are simply combined. When the proppant is laid in the seam by adopting single parameter evaluation, the evaluation result is often too one-sided; when a multi-parameter evaluation system is adopted in the same experiment, the defects that evaluation results are mutually crossed, mutually contradictory and not unique often exist.

Disclosure of Invention

In view of the above problems, an object of the present invention is to provide a comprehensive evaluation method for the proppant placement effect in a fracture. Based on an analytic hierarchy process and a fuzzy mathematical process, a comprehensive evaluation model of the spreading effect of the propping agent is established, the quantitative characterization of the spreading effect of the propping agent in a flat plate slit sand conveying experiment is realized, and a reference is provided for fracturing construction design optimization.

In order to achieve the purpose, the technical scheme adopted by the invention is as follows:

a comprehensive evaluation method for the laying effect of a propping agent in a fracturing fracture is characterized by comprising the following steps:

s10, simulating the laying form of the proppant under different experimental parameters by using a flat slit sand conveying device to obtain the evaluation parameters of the laying effect of the proppant;

step S20, establishing a hierarchical structure model and a judgment matrix A (I);

step S30, introducing a transfer matrix D to obtain a consistency optimization judgment matrix A (II);

step S40, calculating a weight vector omega and carrying out consistency check;

step S50, establishing a factor set U and an evaluation set V;

step S60, establishing a paving effect evaluation fuzzy matrix A (III);

and S70, establishing a comprehensive evaluation model of the paving effect of the intra-slit proppant, and comprehensively evaluating the paving effect of the intra-slit proppant under the flat plate slit sand conveying experiment condition.

Further, the evaluation parameters for step S10 include: the distance of the front edge of the sand bank, the gradient of the front edge of the sand bank, the length of the sand bank and the height of the sand bank; the acquisition method comprises the following steps: the method comprises the steps of video recording of a flat plate slit sand conveying experiment process, intercepting of a balance time characteristic image, binarization processing of the balance time characteristic image to obtain a propping agent laying form gray level image, guiding of the gray level image into graphic processing software, extraction of a sand bank outline by means of a spline curve, calculation and statistics of evaluation parameter values.

Further, the determination matrix a (i) in step S20 is:

in the formula: a (I) represents a judgment matrix; a is_ijRepresenting the relative importance of the evaluation parameter i relative to the evaluation parameter j; i. j sequentially represents the length of the sand bank, the height of the sand bank, the distance of the front edge of the sand bank and the gradient of the front edge of the sand bank.

Further, the transition matrix D and the consistency optimization judgment matrix a (ii) in step S30 are:

in the formula: d represents a transition matrix; d_ijRepresenting elements in a transition matrix; a is_ik，a_jkRepresenting that k corresponds to elements in the judgment matrix A (I) when k takes different values; a (II) represents a consistency optimization judgment matrix;representing the relative importance of the evaluation parameter i relative to the evaluation parameter j after consistency optimization; i. j sequentially represents the length of the sand bank, the height of the sand bank, the distance of the front edge of the sand bank and the gradient of the front edge of the sand bank.

Further, for the weight vector ω in step S40 being the maximum feature vector of the consistency optimization judgment matrix a (ii) calculated by the sum-product method, the consistency check equation is:

in the formula: CI represents a calculation consistency index; lambda [ alpha ]_maxRepresenting the maximum eigenvalue of the judgment matrix; n represents the order of the judgment matrix; CR represents a check coefficient, with values closer to 0 indicating better consistency; RI represents a random consistency index, and when n is 4, RI is 0.9.

Further, the factor set U and the evaluation set V in step S50 are:

in the formula: u represents a factor set; v denotes the evaluation set.

Further, the paving effect blur matrix a (iii) for step S60 is:

in the formula: a (III) represents a tiling effect fuzzy matrix; r_mjAnd representing the membership of the jth element in the factor set to the mth element in the evaluation set.

Further, the membership calculation equation is as follows:

in the formula: r represents a degree of membership; x represents an evaluation parameter value; x_maxRepresents the maximum value of the evaluation parameter; x_minRepresents the minimum value of the evaluation parameter.

Further, the comprehensive evaluation model for the intra-slit proppant placement effect in step S70 is:

in the formula: SI represents a sanding index which can reflect the paving effect of the proppant in the fracture; ω denotes a weight vector of the evaluation parameter.

The invention has the beneficial effects that: the method selects the distance of the front edge of the sand bank, the gradient of the front edge of the sand bank, the height of the sand bank and the length of the sand bank as the evaluation parameters of the laying effect of the propping agent; based on an analytic hierarchy process, constructing an evaluation parameter hierarchical structure model and a judgment matrix, introducing a transfer matrix to optimize the consistency of the judgment matrix, and obtaining an evaluation parameter weight vector; based on a fuzzy mathematical method, a flat slit sand conveying experiment is used as an evaluation set, and an effect fuzzy matrix is constructed and laid. The evaluation parameter weight vector is combined with the paving effect fuzzy matrix to establish a comprehensive evaluation model of the paving effect of the supporting agent in the seam, so that the paving effect of the supporting agent in the seam in the flat plate slit sand conveying experiment can be quantitatively and comprehensively represented, and a certain reference is provided for the optimization of the material of the supporting agent in the oil field and the optimization of the construction parameters.

Drawings

FIG. 1 is a sand bank characteristic diagram at the equilibrium moment of a flat slit sand conveying experiment of the invention;

FIG. 2 is a profile view of a treated extracted sand bank of the present invention;

FIG. 3 is a hierarchical model of an evaluation parameter of the present invention;

fig. 4 is a diagram showing the results of quantitative evaluation of the placement of the intra-slit proppant of the present invention.

Detailed Description

According to the description of the invention, the effect of proppant placement in a flat plate slit experiment is taken as an example for evaluation, and the invention is further described with reference to the accompanying drawings.

The comprehensive evaluation method for the spreading effect of the proppant in the fracturing can quantitatively represent the spreading effect of the proppant in the fracture and provide reference for the optimization of fracturing construction design. The method mainly comprises the following steps:

s10, simulating the laying form of the proppant under different experimental parameters by using a flat slit sand conveying device to obtain the evaluation parameters of the laying effect of the proppant;

according to the device disclosed by the patent number CN201910898699.0, namely a fracturing propping agent conveying simulation method and experimental device with real-time variable sand ratio, fracturing fluid is prepared after a pipeline is connected, and propping agent is added into a sand storage hopper; setting simulation experiment parameters as shown in table 1; opening a centrifugal pump to inject fracturing fluid into a sand mixing barrel to be mixed with a propping agent to form sand carrying fluid; opening the screw pump, and pumping the sand-carrying liquid into the simulated crack; recording an experimental phenomenon by using a camera and intercepting a characteristic image at the equilibrium moment from the beginning of the proppant entering the simulated fracture to the end of pumping of the prepared liquid, wherein the characteristic image is shown in figure 1; carrying out binarization processing on the characteristic image at the balance moment to obtain a gray level image of the spreading form of the propping agent; importing the gray level image into graphic processing software to extract the sand bank outline by using a spline curve, as shown in FIG. 2; the values of the evaluation parameters were calculated and statistically calculated as shown in table 1.

Table 1 evaluation parameter table for proppant placement effect

Step S20, establishing a hierarchical structure model and a judgment matrix A (I);

the hierarchical model is shown in fig. 3, and the judgment matrix a (i) is:

in the formula: a (I) represents a judgment matrix; a is_ijRepresenting the relative importance of the evaluation parameter i relative to the evaluation parameter j; i. j sequentially represents the length of the sand bank, the height of the sand bank, the distance of the front edge of the sand bank and the gradient of the front edge of the sand bank.

Step S30, introducing a transfer matrix D to obtain a consistency optimization judgment matrix A (II);

the transition matrix D is:

in the formula: d represents a transition matrix; d_ijRepresenting elements in a transition matrix; a is_ik，a_jkRepresenting that k corresponds to elements in the judgment matrix A (I) when k takes different values;

the consistency optimization judgment matrix A (II) is as follows:

in the formula: a (II) represents a consistency optimization judgment matrix;representing the relative importance of the evaluation parameter i relative to the evaluation parameter j after consistency optimization; i. j sequentially represents the length of the sand bank, the height of the sand bank, the distance of the front edge of the sand bank and the gradient of the front edge of the sand bank.

Step S40, calculating a weight vector omega and carrying out consistency check;

the consistency check equation is:

in the formula: CI represents a calculation consistency index; lambda [ alpha ]_maxRepresenting maximum features of decision matrixA value; n represents the order of the judgment matrix; CR represents a check coefficient, with values closer to 0 indicating better consistency; RI represents a random consistency index, and when n is 4, RI is 0.9.

The weight vector omega calculated by the judgment matrix A (I) by adopting a sum-product method and the consistency check result CR are as follows:

in the formula: omega₁Represents the weight vector corresponding to the judgment matrix A (I).

The consistency optimization judgment matrix A (II) adopts a sum-product method to calculate a weight vector omega and a consistency check result CR as follows:

in the formula: omega₂And representing the weight vector corresponding to the consistency optimization judgment matrix A (II).

The consistency check result CR of the consistency optimization judgment matrix A (II) is closer to 0 than that of the consistency optimization judgment matrix A (I), which shows that the consistency of the judgment matrix is effectively improved by introducing the transfer matrix.

Step S50, establishing a factor set U and an evaluation set V;

the factor set U is:

u-is (sand bank length, height, distance from front edge, slope of front edge)

In the formula: u represents a factor set.

The evaluation set V is:

v ═ V (experiment 1, experiment 2, experiment 3, …, experiment 7, experiment 8, experiment 9)

In the formula: v represents a set of factors.

Step S60, establishing a paving effect evaluation fuzzy matrix A (III);

the membership calculation equation is as follows:

in the formula: r represents a degree of membership; x represents an evaluation parameter value; x_maxRepresents the maximum value of the evaluation parameter; x_minRepresents the minimum value of the evaluation parameter.

The evaluation parameter membership calculation results are shown in table 2.

TABLE 2 evaluation parameter membership calculation

The paving effect fuzzy matrix A (III) is as follows:

in the formula: a (III) represents a tiling effect fuzzy matrix; r_mjAnd representing the membership of the jth element in the factor set to the mth element in the evaluation set.

And S70, establishing a comprehensive evaluation model of the paving effect of the intra-slit proppant, and comprehensively evaluating the paving effect of the intra-slit proppant under the flat plate slit sand-carrying experimental condition.

The comprehensive evaluation model of the laying effect of the intra-seam proppant comprises the following steps:

in the formula: SI represents a sanding index which can reflect the paving effect of the proppant in the fracture; ω denotes a weight vector of the evaluation parameter.

The results of quantitative evaluation of proppant placement in the seams are shown in fig. 4, and the sand placement index SI is from large to small (proppant placement effect is from good to poor): experiment 7> experiment 8> experiment 1> experiment 4> experiment 2> experiment 5> experiment 9> experiment 6> experiment 3. Therefore, under the condition of experiment 7, the propping agent is uniformly paved, the effective supporting volume is large, and the paving effect of the propping agent is good.

The above-mentioned embodiments are intended to illustrate the objects, aspects and advantages of the present invention, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the present invention in any way, and any modifications, equivalent substitutions, improvements and the like, which are within the spirit and principle of the present invention, should be included in the scope of the present invention.