Method for representing balanced extension degree of horizontal well staged multi-cluster fracturing fractures

Abstract

The application discloses a method for representing balanced extension degree of segmented multi-cluster fracturing cracks of a horizontal well, and is specifically implemented according to the following steps: step 1, obtaining reservoir geological parameters, obtaining fracturing design parameters or obtaining liquid inflow and sand inflow according to working conditions, and then obtaining the maximum value MAX of single-cluster crack length, the minimum value MIN of single-cluster crack length and the average value AVERAGE of crack length in each segment fracturing; step 2, respectively calculating the non-uniformity index Mi of each segment fracturing; and step 3, obtaining the balanced extension degree M of the segmented multi-cluster fracturing cracks of the whole horizontal well according to the non-uniformity index Mi of the single segment fracturing obtained in step 2 ， The method can quantitatively evaluate the balanced extension degree of the multi-cluster fracturing cracks, and has high accuracy.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of oil and gas field exploration and development, and particularly relates to a method for characterizing the balanced extension degree of horizontal well staged multi-cluster fracturing fractures. BACKGROUND

[0002] Horizontal well staged multi-cluster fracturing is a major technical means for the reconstruction of difficult-to-produce reservoirs such as low-permeability, tight oil and shale oil, and the balanced extension degree of multi-cluster fractures is crucial to the evaluation of the reconstruction effect. At present, there are mainly two methods for evaluating the balanced extension degree of multi-cluster fractures. One is to use professional fracturing simulation software to simulate staged multi-cluster fracturing to obtain the fracture length of each cluster, and to show the fracture extension by the fracture length of each cluster, but there is no quantitative index for evaluating the overall balanced extension degree, and the evaluation accuracy is poor. The other is to use a distributed optical fiber monitoring system to real-time quantitatively interpret the liquid and sand injection amounts of each cluster under the condition of single-stage multi-cluster combined fracturing, and to show the fracture extension of each cluster by the values of the liquid and sand injection amounts. The limitation of this method is that even if the liquid and sand injection amounts of each cluster are obtained, there is still no quantitative index for evaluating the overall balanced extension degree. In addition, due to the influence of reservoir heterogeneity, the amount of liquid and sand injection of each cluster cannot accurately reflect the size of the fracture length of each cluster, so this method is not reliable and the evaluation accuracy is poor. SUMMARY

[0003] The purpose of the present application is to provide a method for characterizing the balanced extension degree of horizontal well staged multi-cluster fracturing fractures, which can quantitatively evaluate the balanced extension degree of multi-cluster fracturing fractures with high accuracy.

[0004] The technical solution adopted by the present application is a method for characterizing the balanced extension degree of horizontal well staged multi-cluster fracturing fractures, which is implemented according to the following steps:

[0005] Step 1: Obtain the reservoir geological parameters, and obtain the fracturing design parameters or the liquid and sand injection amounts according to the working conditions, and then obtain the maximum value MAX of the single-cluster fracture length, the minimum value MIN of the single-cluster fracture length and the average value AVERAGE of the fracture length of each cluster in each stage fracturing;

[0006] Step 2: Calculate the non-uniformity index Mi of each stage fracturing respectively;

[0007] Step 3: Obtain the balanced extension degree M' of the staged multi-cluster fracturing fractures of the whole horizontal well according to the non-uniformity index Mi of the single-stage fracturing obtained in step 2.

[0008] The present application is characterized in that,

[0009] In step 1, the working conditions include horizontal wells without optical fiber testing during fracturing and horizontal wells with optical fiber testing during fracturing.

[0010] When the horizontal well is not matched with the optical fiber test in the fracturing process, the reservoir geological parameters and the fracturing design parameters of the fracturing well are inputted through the professional fracturing simulation software, then the fracture lengths of all clusters in each section are obtained by carrying out the segmented multi-cluster fracturing simulation, and then the maximum value MAX of the single cluster fracture length, the minimum value MIN of the single cluster fracture length and the average value AVERAGE of the cluster fracture length in each section are obtained.

[0011] When the horizontal well is matched with the optical fiber test in the fracturing process, based on the optical fiber monitoring interpretation result, the fracture liquid inflow and the sand inflow of each cluster in each section are inputted in the fracturing software by inputting the reservoir geological parameters and the optical fiber monitoring interpretation of the fracturing well, then the fracture lengths of all clusters in each section are obtained by simulation, and then the maximum value MAX of the single cluster fracture length, the minimum value MIN of the single cluster fracture length and the average value AVERAGE of the cluster fracture length in each section are obtained.

[0012] In step 2, the expression of the non-uniformity index Mi of each section is:

[0013] Mi=(MAX-MIN) / AVERAGE, i=1, 2, …, n

[0014] In the formula, MAX is the maximum value of the single cluster fracture length in the section, MIN is the minimum value of the single cluster fracture length in the section, AVERAGE is the average value of the cluster fracture length in the section, and i represents the number of fracturing sections.

[0015] In step 3, the expression of the segmented multi-cluster fracturing crack expansion balance degree M' of the whole horizontal well is:

[0016] M'=(M1+M2+…+Mn) / n

[0017] In the formula, n is the total number of sections of the horizontal well fracturing reconstruction.

[0018] In step 3, when M'≤0.8, it indicates that the crack expansion of the horizontal well after fracturing is relatively balanced, and the reservoir reconstruction is relatively sufficient; when 0.8

[0019] The beneficial effects of the present application are that the characterization method of the segmented multi-cluster fracturing crack expansion balance degree of the horizontal well can objectively and quantitatively reflect the segmented multi-cluster fracturing crack expansion balance degree of the horizontal well, the characterization result has high accuracy and strong reliability, and a new evaluation method is added for the effect evaluation of the segmented multi-cluster fracturing of the horizontal well. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1A flow chart of the method for representing the balanced extension degree of fractures of the segmented multi-cluster fracturing of the horizontal well according to the present application;

[0021] Figure 2 A simulation diagram of the multi-cluster fracture extension of the second segment of the segmented multi-cluster fracturing of the horizontal well in Embodiment 4 of the present application. DETAILED DESCRIPTION

[0022] The present application will be described in detail below in combination with the drawings and specific embodiments.

[0023] Embodiment 1

[0024] The method for representing the balanced extension degree of fractures of the segmented multi-cluster fracturing of the horizontal well according to the present application is specifically implemented according to the following steps as shown in the figure: Figure 1

[0025] Step 1, obtain the reservoir geological parameters, obtain the fracturing design parameters or obtain the liquid injection volume and sand injection volume according to the working conditions, and then obtain the maximum value MAX of the single-cluster fracture length, the minimum value MIN of the single-cluster fracture length and the average value AVERAGE of the cluster fracture length in each segment of fracturing;

[0026] The working conditions include the horizontal well without matching optical fiber testing in the fracturing process and the horizontal well with matching optical fiber testing in the fracturing process.

[0027] When it is the horizontal well without matching optical fiber testing in the fracturing process, the reservoir geological parameters and the fracturing design parameters of the fracturing well are inputted through professional fracturing simulation software (such as Kinetix shale fracturing simulation software), and then the fracture length of all clusters in each segment of fracturing is obtained through segmented multi-cluster fracturing simulation, and then the maximum value MAX of the single-cluster fracture length, the minimum value MIN of the single-cluster fracture length and the average value AVERAGE of the cluster fracture length in each segment of fracturing are obtained.

[0028] When it is the horizontal well with matching optical fiber testing in the fracturing process, the liquid injection volume and sand injection volume of each cluster in each segment of fracturing obtained through optical fiber monitoring interpretation are inputted in the fracturing software (such as Kinetix shale fracturing simulation software) based on the optical fiber monitoring interpretation results, and then the fracture length of all clusters in each segment of fracturing is simulated, and then the maximum value MAX of the single-cluster fracture length, the minimum value MIN of the single-cluster fracture length and the average value AVERAGE of the cluster fracture length in each segment of fracturing are obtained.

[0029] Step 2, calculate the non-uniformity index Mi of each segment of fracturing respectively;

[0030] The expression of the non-uniformity index Mi of each segment of fracturing is:

[0031] Mi = (MAX-MIN) / AVERAGE, i = 1, 2, …, n

[0032] ​In the formula, MAX is the maximum value of the single cluster fracture length in the section of the fracturing; MIN is the minimum value of the single cluster fracture length in the section of the fracturing; AVERAGE is the average value of the cluster fracture length in the section of the fracturing; and i represents the number of the fracturing sections.

[0033] Step 3, obtaining the balance degree M' of the fracture extension of the segmented multi-cluster fracturing of the horizontal well as a whole according to the non-uniformity index Mi of the single-section fracturing obtained in Step 2;

[0034] The expression of the balance degree M' of the fracture extension of the segmented multi-cluster fracturing of the horizontal well as a whole is as follows:

[0035] M' = (M1+ M2+ … + Mn) / n

[0036] In the formula, n is the total number of the sections of the horizontal well fracturing reconstruction.

[0037] When M' ≤ 0.8, it is indicated that the fracture extension after the horizontal well fracturing is relatively balanced, and the reservoir reconstruction is relatively sufficient; when 0.8 < M' ≤ 1.2, it is indicated that the balance degree of the fracture extension after the horizontal well fracturing is at a medium level; and when M' > 1.2, it is indicated that the balance degree of the fracture extension after the horizontal well fracturing is poor, and the reservoir reconstruction is insufficient.

[0038] Example 2

[0039] The characterization method of the balance degree of the fracture extension of the segmented multi-cluster fracturing of the horizontal well is implemented according to the following steps:

[0040] Step 1, a shale oil reservoir is developed by using a horizontal well, and the reservoir geological parameters are as follows: reservoir permeability 0.1 millidarcy, porosity 8.5%, Young's modulus 24000 MPa, Poisson's ratio 0.21, horizontal maximum principal stress 33 MPa, horizontal minimum principal stress 28 MPa, and vertical stress 42 MPa.

[0041] The horizontal well is not matched with the optical fiber testing in the fracturing process, and the fracturing design parameters of the well are as follows: the average single-well horizontal section length of the horizontal well used for developing the oil reservoir is 1200 meters, the oil reservoir drilling rate is 88.3%, the design adopts the segmented multi-cluster fracturing reconstruction mode, the average single-well fracturing is 10 sections, the single section is perforated 10 clusters, each section is combined with 10 clusters, the sanding intensity is 3.5 tons / meter, the liquid injection intensity is 20 cubic meters / meter, and the injection displacement is 14 cubic meters / minute; the reservoir geological parameters and the fracturing design parameters of the fracturing well are input through the professional fracturing simulation software, then the segmented multi-cluster fracturing simulation is performed to obtain the fracture lengths of all clusters in each section of the fracturing, and then the maximum value MAX of the single cluster fracture length, the minimum value MIN of the single cluster fracture length, and the average value AVERAGE of the cluster fracture length in each section of the fracturing are obtained, as shown in the following table. Figure 2As shown, for example, in paragraph 2, the paragraph has a total of 10 clusters, wherein the maximum value MAX of the single cluster seam length is 270 meters, the minimum value MIN of the single cluster seam length is 126 meters, and the average value AVERAGE of the cluster seam length is 185 meters.

[0042] Step 2, calculate the non-uniformity index M2 of the fracture of paragraph 2 = (270-126) / 185 = 0.78, and the non-uniformity index of the fracture of the 10 paragraphs of the horizontal well is calculated by the formula respectively as 0.93, 0.78, 1.12, 1.05, 1.25, 1.38, 1.24, 0.66, 1.48, 0.75.

[0043] Step 3, the balance degree M' of the fracture expansion of the segmented multi-cluster fracturing of the whole horizontal well = (M1+M2+…+M10) / 10, then M' = (0.93+0.78+1.12+1.05+1.25+1.38+1.24+0.66+1.48+0.75) / 10 = 1.06, it can be known that the interval of 0.8 < M' ≤ 1.2, which indicates that the balance degree of the fracture expansion after the fracturing of the horizontal well is at a medium level, and the reservoir reconstruction degree is general.

[0044] Example 3

[0045] The characterization method for the balanced expansion degree of the horizontal well segmented multi-cluster fracturing fracture, is specifically implemented according to the following steps:

[0046] Step 1, a shale gas reservoir is developed by using a horizontal well, and the reservoir geological parameters are: reservoir permeability 0.15 millidarcy, porosity 9.2%, Young's modulus 22000 MPa, Poisson's ratio 0.22, horizontal maximum principal stress 35 MPa, horizontal minimum principal stress 31 MPa, and vertical stress 43 Mpa;

[0047] The horizontal well is not matched with an optical fiber test during the fracturing process, and the fracturing design parameters of the well are: the average single well horizontal section length of the horizontal well used for developing the reservoir is 600 meters, the oil layer drilling rate is 78.5%, the design adopts a segmented multi-cluster fracturing reconstruction mode, the average single well is fractured for 6 sections, 5 clusters per section, 5 clusters per section, the sanding intensity is 3.2 tons / meter, the liquid injection intensity is 25 cubic meters / meter, and the injection displacement is 10 cubic meters / minute; the reservoir geological parameters and the fracturing design parameters of the fracturing well are input by using a professional fracturing simulation software, then the fracture lengths of all clusters in each section are obtained by performing the segmented multi-cluster fracturing simulation, and then the maximum value MAX of the single cluster seam length, the minimum value MIN of the single cluster seam length, and the average value AVERAGE of the cluster seam length in each section are obtained, as shown in Table 1.

[0048] Step 2, the non-uniformity index Mi of each section is calculated by using the formula Mi = (MAX-MIN) / AVERAGE, i = 1, 2, …, 6.

[0049] Table 1 calculation details of non-uniformity index of each section of a certain shale gas horizontal well

[0050]

[0051] Step 3, the equalization degree M' of fracture expansion of the segmented multi-cluster fracturing of the whole horizontal well = (M1+M2+…+M6) / 6, then

[0052] M' = (0.37+0.67+0.46+0.19+0.61+0.38) / 6 = 0.45

[0053] Therefore, M' < 0.8, which indicates that the fracture expansion after fracturing of the horizontal well is relatively balanced, and the reservoir reconstruction is relatively sufficient.

[0054] Example 4

[0055] The characterization method for the equalization expansion degree of the segmented multi-cluster fracturing fracture of the horizontal well is implemented according to the following steps:

[0056] Step 1, a horizontal well is used for developing a certain ultra-low permeability reservoir, and the reservoir geological parameters are as follows: reservoir permeability 0.35 millidarcy, porosity 11.2%, Young's modulus 21500 MPa, Poisson's ratio 0.23, horizontal maximum principal stress 31 MPa, horizontal minimum principal stress 27 MPa, and vertical stress 35 MPa;

[0057] The average single well horizontal section length of the horizontal well of the reservoir is 500 meters, the oil layer drilling rate is 73.5%, the segmented multi-cluster fracturing reconstruction mode is used, the average single well is fractured 4 sections, the single section is perforated 3 clusters, and each section is combined with 3 clusters. The horizontal well is matched with optical fiber testing during fracturing, and the liquid inflow and sand inflow of each cluster fracture in each section are obtained through optical fiber monitoring interpretation. The reservoir geological parameters of the fractured well and the liquid inflow and sand inflow of each cluster fracture in each section obtained through optical fiber monitoring interpretation are input into the Kinetix fracturing software, and then the fracture lengths of all clusters in each section are simulated, and then the maximum value MAX of the single cluster fracture length, the minimum value MIN of the single cluster fracture length, and the average value AVERAGE of the cluster fracture length are obtained, as shown in Table 2.

[0058] Step 2, the non-uniformity index Mi of each section is calculated by using the formula Mi = (MAX-MIN) / AVERAGE, i = 1, 2, 3, 4.

[0059] Table 2 calculation details of non-uniformity index of each section of a certain ultra-low permeability reservoir horizontal well

[0060]

[0061]

[0062] Step 3, the equalization degree of fracture propagation of the whole horizontal well M' = (M1+M2+…+M4) / 4, then M' = (1.42+1.33+1.26+0.98) / 4 = 1.25;

[0063] Therefore, M' > 1.2, indicating that the equalization degree of fracture propagation after fracturing of the horizontal well is poor, and the reservoir reconstruction is insufficient.

Claims

1. A method for characterizing the degree of uniform propagation of multi-cluster fracturing fractures in a horizontal well, characterized in that, The specific steps are as follows: Step 1: Obtain reservoir geological parameters. Based on the working conditions, obtain fracturing design parameters or obtain fluid injection and sand injection rates. Then, obtain the maximum value (MAX), minimum value (MIN), and average value (AVERAGE) of single cluster fracture length in each fracturing stage. Step 2: Calculate the non-uniformity index of each fracturing segment. Mi ; In step 2, the non-uniformity index of each fracturing segment Mi The expression is: Mi = (MAX) MIN) / AVERAGE ， i =1,2,……, n In the formula, MAX is the maximum length of a single cluster of fractures in this fracturing segment; MIN is the minimum length of a single cluster of fractures in this fracturing segment; and AVERAGE is the average length of each cluster of fractures in this fracturing segment. i Indicates the number of fracturing stages; Step 3, based on the non-uniformity index of single-stage fracturing obtained in Step 2 Mi Obtain the overall segmented multi-cluster fracturing fracture propagation uniformity of the horizontal well. M’ ; In step 3, the degree of uniformity in the propagation of segmented multi-cluster fracturing fractures throughout the horizontal well is assessed. M’ The expression is: M' = (M1 + M2 + ... + Mn) / n In the formula, n is the total number of fracturing stages in a horizontal well.

2. The method for characterizing the degree of uniform propagation of multi-cluster fracturing fractures in a horizontal well according to claim 1, characterized in that, In step 1, the operating conditions include horizontal wells without fiber optic testing during fracturing and horizontal wells with fiber optic testing during fracturing.

3. The method for characterizing the degree of uniform propagation of multi-cluster fracturing fractures in a horizontal well according to claim 2, characterized in that, When the horizontal well is not equipped with fiber optic testing during the fracturing process, the reservoir geological parameters and fracturing design parameters of the fracturing well are input into professional fracturing simulation software. Then, segmented multi-cluster fracturing simulation is performed to obtain the fracture length of all clusters in each segment of fracturing. Then, the maximum value MAX, the minimum value MIN of the single cluster fracture length, and the average value AVERAGE of the single cluster fracture length are obtained in each segment of fracturing.

4. The method for characterizing the degree of uniform propagation of multi-cluster fracturing fractures in a horizontal well according to claim 2, characterized in that, When a horizontal well is equipped with fiber optic testing during fracturing, the reservoir geological parameters of the fracturing well and the fluid and sand ingress rates of each cluster of fractures in each fracturing stage are input into the fracturing software based on the fiber optic monitoring and interpretation results. This allows for the simulation of the fracture length of all clusters in each fracturing stage, and subsequently, the maximum value (MAX), minimum value (MIN), and average value (AVERAGE) of the single cluster fracture length in each fracturing stage.

5. The method for characterizing the degree of uniform propagation of multi-cluster fracturing fractures in a horizontal well according to claim 1, characterized in that, In step 3, when M’ If the value is ≤0.8, it indicates that the fracture propagation after horizontal well fracturing is relatively balanced and the reservoir stimulation is relatively sufficient; when 0.8 < M’ ≤1.2 indicates that the degree of uniformity of fracture propagation after horizontal well fracturing is at a moderate level; when M’ A value greater than 1.2 indicates poor uniformity of fracture propagation after horizontal well fracturing and insufficient reservoir stimulation.

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