A method for identifying ineffective injection circulation zones using dynamic production data

Abstract

The present invention relates to a method for identifying invalid injection circulation zones using dynamic production data, and belongs to the field of oil and gas field development. The method of the present invention is based on the production dynamic data of injection and production wells, takes into account the time lag effect of injection signals on site in the formation propagation process of the oil field, and uses a modified multivariate linear regression model to calculate the connectivity coefficient between injection and production wells to determine the development direction of the invalid injection circulation zone.

Description

Technical Field

[0001] The invention belongs to the technical field of oilfield development, and in particular relates to a method for identifying an invalid injection circulation layer zone by utilizing dynamic production data. Background Art

[0002] The formation of ineffective injection circulation zones exacerbates reservoir heterogeneity and displacement imbalance. Injected water easily flows along the ineffective injection circulation zones, seriously affecting the sweep range of the injected water and worsening the development effect of the oilfield. Therefore, how to quickly and effectively identify ineffective injection circulation zones is one of the important issues that need to be urgently addressed in medium- and high-water-cut oilfields.

[0003] The identification method of ineffective injection circulation zones in conventional oil reservoirs is mainly based on single well point dynamic monitoring data and dynamic analysis. It has many subjective factors, high costs, and few well points. It is difficult to fully promote it, which restricts the adjustment of injection-production structure to improve development effects. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed to provide a method for identifying a dominant seepage channel that overcomes the above problems or at least partially solves the above problems.

[0005] The present invention provides a method for identifying an invalid injection circulation zone using dynamic production data, comprising:

[0006] Step 1: Obtain monthly injection volume data of water injection wells and monthly liquid production data of production wells from the monthly production report of the oil field;

[0007] Step 2: Calculate the dynamic connectivity coefficients between each well group using the modified connectivity calculation model based on the injection-production development data;

[0008] During the reservoir displacement process, there is a time lag and attenuation of the injection signal. When the fluid energy propagates in the medium, it will be lost due to the existence of resistance. Therefore, considering the impact of the time lag and attenuation of the injection signal on the calculation results, the loss value should be corrected to achieve better calculation results and thus better obtain the real well connectivity information.

[0009] Because factors such as the compression coefficient lead to the dissipation of the injection volume during the driving process, within a certain time interval, the sum of the effects of the injection signals of all water injection wells jointly affects the effect of the production well liquid production. The injection signal is discretized into 12 discrete pulse signals over 12 months. The ratio of the injection signal at each discrete time step to the total injection signal is called the filtering coefficient or nonlinear diffusion coefficient, that is:

[0010]

[0011] Where: α (k)——Filter coefficient, the proportion of injection excitation in each time period after discretization, %;

[0012] Δq——The change in production output of the production well caused by the change in water injection volume of the injection well, m 3 / s;

[0013] t – time step;

[0014] k——The time sequence number of the filter coefficient.

[0015] The greater the loss of the fluid flowing in the oil layer due to factors such as the comprehensive compression coefficient of the formation, the greater the α (k) Therefore, under normal use conditions, take α (k) =12 can meet the correction requirements. By correcting the injection signal between the injection and production wells through the filter coefficient, the calculation result can effectively reduce the deviation caused by the attenuation and time lag of the injection signal, that is:

[0016]

[0017] Among them, i i is the injection volume of the i-th injection well;

[0018] The revised connectivity calculation model is:

[0019]

[0020] in, is the liquid production of the jth production well at time step t, m 3 / d;

[0021] β oj is a constant term, i.e., the injection-production imbalance constant of the water-flooding reservoir;

[0022] β ij is the multivariate linear regression weight of the j-th production well and the i-th injection well, that is, the dynamic connectivity coefficient;

[0023] i ii c (t) is the corrected injection volume of the i-th injection well at time step n, m 3 / d;

[0024] Step 3: Further, based on the oil field report obtained in step 1, select the production data of the production wells associated with the same water injection well, bring the water injection volume data of the water injection wells and the liquid production data of the production wells into the connectivity calculation model modified in step 2, and calculate the dynamic connectivity coefficient β between each injection and production well group. ijThe connectivity coefficient indicates the degree of connectivity between production wells and injection wells. The greater the connectivity, the easier it is for fluid to flow into the pathways of that well group, and the more likely it is to create an ineffective injection circulation zone. Comparing the calculated connectivity coefficients between injection-production well groups, the well groups with the largest connectivity coefficients are most likely to have ineffective injection circulation zones.

[0025] Step 4: Based on the well group that is most likely to have an invalid injection circulation zone determined in step 3, select injection and production development data of different time periods in chronological order from the oil field report of this well group, and bring it into the modified connectivity calculation model in step 2 above to calculate the connectivity coefficients between different time periods, and calculate the connectivity dispersion rate of the dynamic connectivity coefficient within the well group:

[0026] The calculation formula of connectivity dispersion ratio (Dr) is:

[0027]

[0028] Where: β i ——Dynamic connectivity coefficient within the same well group in each time period;

[0029] i——represents the number of the injection well and each production well group;

[0030] n——number of selected time periods;

[0031] ——Average value of dynamic connectivity coefficient;

[0032] By comparing the connectivity dispersion rate of the dynamic connectivity coefficient of the same injection well group in different time periods, the quantitative identification of the development of the ineffective injection circulation zone between the injection and production well groups can be achieved. The connectivity dispersion rate can represent the degree of dispersion of the connectivity coefficient in each time period. When D r When it is >15%, it means that the connectivity between well groups has changed significantly during the selected time period, and an ineffective injection zone has developed. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Various other advantages and benefits will become apparent to those skilled in the art by reading the following detailed description of the preferred embodiment.The accompanying drawings are only for the purpose of illustrating the preferred embodiment and are not to be considered as limiting the present invention.

[0034] In the attached figure:

[0035] Figure 1 Flowchart of the present invention. DETAILED DESCRIPTION

[0036] The present invention will be described in detail below in conjunction with specific embodiments and examples, and the advantages and various effects of the present invention will be more clearly presented. It should be understood by those skilled in the art that these specific embodiments and examples are for illustrating the present invention, rather than for limiting the present invention.

[0037] Throughout this specification, unless otherwise specified, the terms used herein should be understood as having the same meaning as commonly used in the art. Therefore, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. In the event of any conflict, the present specification shall take precedence.

[0038] This application provides a method for identifying invalid injection circulation zones using dynamic production data, such as Figure 1 The process shown includes:

[0039] The monthly injection volume data of water injection wells and monthly liquid production data of production wells were obtained from the monthly production report of the 1-2 sand group of the second section of the Shengtuo Oilfield;

[0040] Table 1

[0041] Connectivity coefficient ST2-3-182 ST2-4-159 ST2-4-174 ST2-4X191 ST2-4X199 0.29 0.40 0.32 0.34

[0042] Table 2

[0043] years 1992-1997 1997-2002 2002-2007 2007-2012 2012-2017 Connectivity coefficient 0.24 0.27 0.31 0.38 0.41

[0044] Table 3

[0045] Production well number Tracer output ratio ST2-3-182 8.46％ ST2-4-159 59.62％ ST2-4-174 14.31％ ST2-4X191 17.61

[0046] Based on the oilfield reports obtained above, we selected production data from four production wells (ST2-3-182, ST2-4-159, ST2-4-174, and ST2-4X191) associated with the same injection well (ST2-4X199). We then applied the injection rate data of the injection wells and the liquid production data of the production wells to the revised connectivity calculation model to calculate the dynamic connectivity coefficients between each injection-production well group (Appendix 1). Comparing the calculated connectivity coefficients between the various injection-production well groups revealed that the well group with the largest connectivity coefficient was most likely to contain an ineffective injection circulation zone.

[0047] Based on the previous step, the well group (ST2-4X199 and ST2-4-159) that is most likely to have an invalid injection circulation zone is identified. 25 years of injection and production development data are selected from the oil field report of this well group in chronological order from 1992 with a step length of 5 years. The data are introduced into the modified connectivity calculation model to calculate the connectivity coefficients between different time periods (Appendix 2), and the connectivity dispersion rate D of the dynamic connectivity coefficient within the well group is calculated. r=19.57%>15%, indicating that the well group has developed an invalid injection zone. Compared with the oil field tracer test results (Appendix Table 3), it is basically consistent with the calculation results of this method.

Claims

1. A method for identifying ineffective injection circulation zones using dynamic production data, characterized in that: The following steps are involved: Step 1: Obtain dynamic production data from the oil field monthly production report, namely, monthly injection volume data of water injection wells and monthly liquid production data of production wells; Step 2: Calculate the dynamic connectivity coefficients between each well group using the modified connectivity calculation model based on the dynamic production data; Step 3: Based on the oilfield report obtained in step 1, select the production data of the production wells associated with the same water injection well, and bring the water injection volume data of the water injection wells and the liquid production data of the production wells into the connectivity calculation model modified in step 2 to calculate the dynamic connectivity coefficient β between each injection and production well group. ij , comparing the calculated connectivity coefficients between the injection and production well groups, the well group with the largest connectivity coefficient is most likely to have an invalid injection circulation zone; Step 4: Based on the well group that is most likely to have an invalid injection circulation zone determined in step 3, select the injection and production development data of different time periods in the oil field report of the well group in chronological order, and bring it into the modified connectivity calculation model in step 2 above to calculate the connectivity coefficients between different time periods, and calculate the connectivity dispersion rate of the dynamic connectivity coefficient within the well group. ; Connectivity dispersion rate The calculation formula is: ， Where: β i ——Dynamic connectivity coefficient within the same well group in each time period; i ——Numbers representing injection wells and production well groups; n ——Number of selected time periods; ——Average value of dynamic connectivity coefficient; The connectivity dispersion rate represents the degree of dispersion of the connectivity coefficient in each period. When it is >15%, it means that the connectivity between well groups has changed during the selected time period, and an ineffective injection zone has developed; By comparing the connectivity discrete rates of the dynamic connectivity coefficients of the same injection well group at different time periods, the development of ineffective injection circulation zones between injection and production well groups can be quantitatively identified.

2. The method for identifying ineffective injection circulation zones using dynamic production data according to claim 1, characterized in that: In step 2, the injection signal is discretized into 12 discrete pulse signals over 12 months. The ratio of the injection signal at each discrete time step to the total injection signal is called the filter coefficient or nonlinear diffusion coefficient, that is: ， Where: α (k) ——Filter coefficient, the proportion of injection excitation in each time period after discretization, %; Δq——The change in production output of the production well caused by the change in water injection volume of the injection well, m 3 / s; t — time step; k ——Time sequence number of the filter coefficient; By correcting the injection signal between the injection and production wells through the filter coefficient, the calculation results effectively reduce the deviation caused by the attenuation and time lag of the injection signal, that is: ， Among them, i i ——No. i The injection volume of the water injection wells; The revised connectivity calculation model is: ， in, ——No. j Production wells at time step t Liquid production, m 3 / d; β 0j ——Constant term, i.e., injection-production imbalance constant of water-flooded reservoir; β ij ——No. j Production well and i The multiple linear regression weight of the injection wells is the dynamic connectivity coefficient; i ii c (t)——No. i The injection well is at time step n The corrected injection volume, m 3 / d.

3. The method for identifying ineffective injection circulation zones using dynamic production data according to claim 2, characterized in that: Take α (k) =12 meets the correction requirements.

4. The method for identifying ineffective injection circulation zones using dynamic production data according to claim 1, characterized in that: In step three, the connectivity coefficient indicates the degree of connectivity between the production wells and the injection wells. The greater the connectivity, the easier it is for the fluid to flow toward the channel of the well group, and the easier it is to produce an ineffective injection circulation zone.

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