Effect evaluation method for long-acting augmented injection process

Abstract

The invention discloses a long-acting augmented injection process effect evaluation method which comprises the following specific steps: step 1, acquiring the original porosity, post-acidification porosity, original permeability and post-acidification permeability of a water injection well, the radius of a shaft and the radius of an oil reservoir water injection unit according to geological data, and calculating the porosity change amplitude and the permeability change amplitude; 2, the water absorption index before acidification and the water absorption index after acidification of the water injection well are measured, the injection increasing multiple and the skin coefficient after acidification are calculated, and the pressure drop index IPI of the water injection well and the effective day number of acidification measures are determined; step 3, performing dimensionless processing on the parameters obtained in the step 1 and the step 2; 4, calculating a grey correlation coefficient, and calculating correlation degree; and 5, calculating a weight coefficient and a decision factor. The method solves the problems that in the prior art, an augmented injection process effect quantitative evaluation method is complex, and evaluation parameters are difficult to obtain.

Description

Technical Field

[0001] The invention belongs to the technical field of acidizing and plugging removal of oilfield water injection wells, and particularly relates to a method for evaluating the effect of a long-term injection process. Background Art

[0002] During the water injection development process, as the water injection time increases, most water injection wells often experience a decrease in water injection capacity. This phenomenon is particularly prominent for water injection wells in ultra-low permeability reservoirs. Water injection wells in some blocks have experienced high-pressure under-injection or even no water injection. To address this problem, a long-term injection acidification process for water injection wells has been developed on the market. By combining local pressure increase with acidification, it solves the problem of high-pressure under-injection or no water injection in water injection wells, achieving comprehensive management and increasing the amount of injected water.

[0003] At present, there are few quantitative evaluation methods for the effect of long-term injection technology. The publication number is CN114109376A, and the patent name is: A method for evaluating the effect of bio-nano pressure reduction and injection enhancement technology. This patent mainly conducts a quantitative evaluation of the effect of bio-nano pressure reduction and injection enhancement technology, but its calculation method is too complicated and the evaluation parameters are difficult to obtain. Most of the other methods are limited to judging whether they are effective based on the two factors of wellhead pressure change and injection volume, and cannot quantitatively evaluate the improvement effect.

[0004] Therefore, how to conduct a simple and easy quantitative evaluation of the effect of the long-term injection process is a technical problem to be solved by those skilled in the art. Summary of the invention

[0005] The purpose of the present invention is to provide a method for evaluating the effect of long-term injection enhancement technology, which solves the problem that the quantitative evaluation method of the injection enhancement technology effect in the prior art is complicated and the evaluation parameters are difficult to obtain.

[0006] The technical solution adopted by the present invention is a method for evaluating the effect of long-term injection technology, and the specific steps are as follows:

[0007] Step 1: Obtain the original porosity of the injection well based on geological data and porosity after acidification Original permeability K 0 and permeability after acidification K 1 , wellbore radius r w and the radius of the reservoir injection unit r e , calculate the porosity variation Permeability change range K Z ;

[0008] Step 2: Determine the water absorption index I before acidification of the injection well w1 and water absorption index I after acidification w2And calculate the injection multiple Z and the skin factor S after acidification, determine the injection well pressure drop index IPI and the effective days T of acidification measures;

[0009] Step 3, performing dimensionless processing on the parameters obtained in step 1 and step 2;

[0010] Step 4: Calculate the grey relational coefficient ξ i , calculate the correlation γ i ;

[0011] Step 5: Calculate the weight coefficient α i and decision factor D.

[0012] The present invention is also characterized in that:

[0013] In step 1, the porosity variation The expression is:

[0014]

[0015] In the formula, is the original porosity of the injection well, in %; It is the porosity of the injection well after acidification, in %.

[0016] In step 1, the permeability change range K Z The expression is:

[0017]

[0018] In the formula, K 0 is the original permeability of the injection well, in units of 10 -3 μm 2 ; K 1 is the permeability of the injection well after acidification, in units of 10 -3 μm 2 .

[0019] In step 2, the water absorption index I before acidification of the injection well w1 and water absorption index I after acidification w2 They are all daily water injection volumes under unit pressure difference, which can be obtained through the curve of wellhead pressure changing with daily water injection volume.

[0020] In step 2, the expression of the injection multiple Z is:

[0021]

[0022] In the formula, I w1 is the water absorption index of the injection well before acidification, in m 3 / (dMPa);I w2 is the water absorption index of the injection well after acidification, in m 3 / (dMPa).

[0023] In step 2, the expression of the skin factor S after acidification is:

[0024]

[0025] In the formula, I w1 is the water absorption index of the injection well before acidification, in m 3 / (d MPa);I w2 is the water absorption index of the injection well after acidification, in m 3 / (dMPa);r e is the radius of the reservoir water injection unit, in m; r w is the radius of the injection wellbore, in m.

[0026] In step 2, the water injection well pressure drop index IPI can be obtained through the wellhead pressure drop curve of the water injection well after acidification, and the wellhead pressure drop curve of the water injection well after acidification is measured by a wellhead automatic pressure recorder.

[0027] In step 3, the dimensionless expression of the parameter is:

[0028]

[0029] In the formula, x i are the evaluation parameters, i is the evaluation parameter number; X i is the dimensionless evaluation parameter; x min is the minimum value of the same evaluation parameter; x max It is the maximum value of the same type of evaluation parameters.

[0030] In step 4, the grey relational coefficient ξ i The expression is:

[0031]

[0032] In the formula, X 0 is the reference sequence, X i is a comparison sequence; |X i (k)-X 0 (k)| represents the sequence X i With X 0 The absolute value at the kth point; Represents the minimum absolute value of the two extremes of the two sequences; It represents the maximum absolute value of the two poles of the two sequences; ρ is the resolution coefficient, which is generally taken as 0.5;

[0033] Among them, the reference sequence is a sequence composed of the optimal combination of each evaluation parameter;

[0034] Correlation γ iThe expression is:

[0035]

[0036] In step 5, the weight coefficient α i The expression is:

[0037]

[0038] The expression of decision factor D is:

[0039]

[0040] The beneficial effects of the present invention are as follows: the method for evaluating the effect of long-term injection technology of the present invention only needs to determine the porosity, permeability, water absorption index of the formation before and after acidification, the IPI value of the pressure drop curve after acidification, and the effective days of the measure, and only a few parameters are needed to achieve quantitative evaluation of the effect of the injection technology, and the required evaluation parameters are easy to obtain, the calculation method and implementation process are simple, and there is a corresponding evaluation theoretical basis. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The water injection well indicator curve before and after the well acidification in Example 4 of the method of the present invention;

[0042] Figure 2 The wellhead pressure drop curve after acidizing of the well in Example 4 of the method of the present invention;

[0043] Figure 3 This is the cumulative probability diagram of decision factors in Example 4 of the method of the present invention. DETAILED DESCRIPTION

[0044] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] Example 1

[0046] The present invention provides a method for evaluating the effect of a long-term injection process, which is specifically implemented according to the following steps:

[0047] Step 1: Obtain the original porosity of the injection well based on geological data and porosity after acidification Original permeability K 0 and permeability after acidification K 1 , wellbore radius r w and the radius of the reservoir injection unit r e , calculate the porosity variation Permeability change range K Z ;

[0048] Step 2: Determine the water absorption index I before acidification of the injection well w1and water absorption index I after acidification w2 And calculate the injection multiple Z and the skin factor S after acidification, determine the injection well pressure drop index IPI and determine the effective days T of acidification measures based on production data;

[0049] Step 3: Dimensionless processing is performed on the parameters obtained in step 1 and step 2. The dimensionless processing parameters include the porosity variation range. Permeability change range K Z , injection multiple Z, skin factor S after acidification, injection well pressure drop index IPI, effective days of acidification measures T;

[0050] Step 4: Calculate the grey relational coefficient ξ i , calculate the correlation γ i ;

[0051] Step 5: Calculate the weight coefficient α i And the decision factor D, according to which the effect of the augmentation process is evaluated.

[0052] The method for evaluating the effect of long-term injection technology of the present invention only needs to determine the porosity, permeability, water absorption index of the formation before and after acidification, the IPI value of the pressure drop curve after acidification, and the effective days of the measure, so as to achieve quantitative evaluation of the effect of the injection technology. The required evaluation parameters are easy to obtain, the parameters involved are few, and there is a corresponding evaluation theoretical basis.

[0053] Example 2

[0054] Based on Example 1, in step 1, the porosity variation range The expression is:

[0055]

[0056] In the formula, is the original porosity of the injection well, in %; is the porosity of the injection well after acidification, in %;

[0057] Permeability change range K Z The expression is:

[0058]

[0059] In the formula, K 0 is the original permeability of the injection well, in units of 10 -3 μm 2 ; K 1 is the permeability of the injection well after acidification, in units of 10 -3 μm 2 .

[0060] Based on Example 1, in step 2, the water absorption index I before acidification of the injection well w1 and water absorption index I after acidification w2 The daily water injection volume under unit pressure difference can be obtained through the curve of wellhead pressure changing with daily water injection volume, or the water absorption index I before acidification of the injection well w1 and water absorption index I after acidification w2 They are all apparent water absorption index, which is the derivative of the slope of the curve of wellhead pressure changing with daily water injection volume;

[0061] The expression of injection multiple Z is:

[0062]

[0063] In the formula, I w1 is the water absorption index of the injection well before acidification, in m 3 / (dMPa);I w2 is the water absorption index of the injection well after acidification, in m 3 / (dMPa);

[0064] The expression of the skin factor S after acidification is:

[0065]

[0066] In the formula, I w1 is the water absorption index of the injection well before acidification, in m 3 / (d MPa);I w2 is the water absorption index of the injection well after acidification, in m 3 / (d MPa); r e is the radius of the reservoir water injection unit, in m; r w is the radius of the injection wellbore, in m;

[0067] The injection well pressure drop index IPI can be obtained through the wellhead pressure drop curve after acidification of the injection well. The wellhead pressure drop curve after acidification of the injection well is measured by a wellhead automatic pressure recorder.

[0068] In step 3, the dimensionless expression of the parameter is:

[0069]

[0070] In the formula, x i are the evaluation parameters, i is the evaluation parameter number; X i is the dimensionless evaluation parameter; x min is the minimum value of the same evaluation parameter; x max It is the maximum value of the same type of evaluation parameters;

[0071] In step 4, the grey relational coefficient ξi The expression is:

[0072]

[0073] In the formula, X 0 is the reference sequence, X i is a comparison sequence; |X i (k)-X 0 (k)| represents the sequence X i With X 0 The absolute value at the kth point; Represents the minimum absolute value of the two extremes of the two sequences; It represents the maximum absolute value of the two poles of the two sequences; ρ is the resolution coefficient, which is generally taken as 0.5;

[0074] The reference sequence is a sequence formed by combining the best parameters among the evaluation parameters, and the comparison sequence is a sequence formed by combining the parameters involved in the evaluation.

[0075] Correlation γ i The expression is:

[0076]

[0077] In step 5, the weight coefficient α i The expression is:

[0078]

[0079] The expression of decision factor D is:

[0080]

[0081] Finally, by making a cumulative probability diagram of decision factors, the injection effects are classified according to the inflection points of the cumulative probability curve.

[0082] Among them, steps 3 to 5 can be automatically implemented through professional data statistical analysis software Statistical Product and Service Solutions (SPSS).

[0083] Example 3

[0084] The difference from Example 2 is that the water absorption index I before acidification of the injection well is w1 and water absorption index I after acidification w2 Both are apparent water absorption index, which is the derivative of the slope of the curve of wellhead pressure changing with daily water injection volume.

[0085] Example 4

[0086] Taking the 12 acidizing and injection wells in Block L as an example, the basic information of the 12 wells is as follows:

[0087] Table 1 Well basic information

[0088]

[0089] According to the basic information of 12 wells and Figure 1 The water injection well indicator curves before and after acidification are shown. Figure 2 The porosity variation of each well is calculated from the wellhead pressure drop curve after acidizing shown in the figure. Permeability change range K Z , water absorption index before acidification I w1 , water absorption index after acidification I w2 , injection multiple Z, skin coefficient S after acidizing and injection well pressure drop index IPI, as shown in the following table.

[0090] Table 2 Summary of calculation parameters

[0091]

[0092] The summary statistics yielded the parameters required for evaluation, as shown in the following table.

[0093] Table 3 Summary of evaluation parameters

[0094]

[0095] The final decision factors of each well are shown in Table 4 and Figure 3 As shown; by making a cumulative probability diagram of decision factors, the injection effect is classified according to the inflection point of the cumulative probability curve. The larger the decision factor D value, the better the corresponding water injection well injection process effect, then Class I is better than Class II, Class II is better than Class III, and Class III is better than Class IV.

[0096] Table 4 Comprehensive evaluation table of injection effect

[0097]

Claims

1. A method for evaluating the effect of long-term injection technology, characterized in that: The specific steps are as follows: Step 1: Obtain the original porosity of the injection well based on geological data and porosity after acidification Original permeability K0 and permeability after acidizing K1, wellbore radius r w and the radius of the reservoir injection unit r e , calculate the porosity variation Permeability change range K Z ; Step 2: Determine the water absorption index I before acidification of the injection well w1 and water absorption index I after acidification w2 And calculate the injection multiple Z and the skin factor S after acidification, determine the injection well pressure drop index IPI and the effective days T of acidification measures; Step 3, performing dimensionless processing on the parameters obtained in step 1 and step 2; Step 4: Calculate the grey relational coefficient ξ i , calculate the correlation γ i ; Step 5: Calculate the weight coefficient α i and decision factor D.

2. The method for evaluating the effect of long-term injection process according to claim 1, characterized in that: In step 1, the porosity variation The expression is: In the formula, is the original porosity of the injection well, in %; It is the porosity of the injection well after acidification, in %.

3. The method for evaluating the effect of long-term injection process according to claim 1, characterized in that: In step 1, the permeability change range K Z The expression is: Where K0 is the original permeability of the injection well, in units of 10 -3 μm 2 ; K1 is the permeability of the injection well after acidification, unit is 10 -3 μm 2 .

4. The method for evaluating the effect of long-term injection process according to claim 1, characterized in that: In step 2, the water absorption index I before acidification of the injection well w1 and water absorption index I after acidification w2 They are all daily water injection volumes under unit pressure difference, which can be obtained through the curve of wellhead pressure changing with daily water injection volume.

5. The method for evaluating the effect of long-term injection process according to claim 1, characterized in that: In step 2, the expression of the injection multiple Z is: In the formula, I w1 is the water absorption index of the injection well before acidification, in m 3 / (dMPa);I w2 is the water absorption index of the injection well after acidification, in m 3 / (d MPa).

6. The method for evaluating the effect of long-term injection process according to claim 1, characterized in that: In step 2, the expression of the skin factor S after acidification is: In the formula, I w1 is the water absorption index of the injection well before acidification, in m 3 / (d MPa);I w2 is the water absorption index of the injection well after acidification, in m 3 / (dMPa);r e is the radius of the reservoir water injection unit, in m; r w is the radius of the injection wellbore, in m.

7. The method for evaluating the effect of long-term injection process according to claim 1, characterized in that: In step 2, the water injection well pressure drop index IPI can be obtained through the wellhead pressure drop curve of the water injection well after acidification, and the wellhead pressure drop curve of the water injection well after acidification is measured by a wellhead automatic pressure recorder.

8. The method for evaluating the effect of long-term injection process according to claim 1, characterized in that: In step 3, the dimensionless expression of the parameter is: In the formula, x i are the evaluation parameters, i is the evaluation parameter number; X i is the dimensionless evaluation parameter; x min is the minimum value of the same evaluation parameter; x max It is the maximum value of the same type of evaluation parameters.

9. The method for evaluating the effect of long-term injection process according to claim 1, characterized in that: In step 4, the grey relational coefficient ξ i The expression is: In the formula, X0 is the reference sequence, X i is a comparison sequence; |X i (k)-X0(k)| represents the sequence X i and the absolute value of X0 at point k; Represents the minimum absolute value of the two extremes of the two sequences; It represents the maximum absolute value of the two poles of the two sequences; ρ is the resolution coefficient, which is generally taken as 0.5; Among them, the reference sequence is a sequence composed of the optimal parameters of each evaluation parameter; Correlation γ i The expression is:

10. The method for evaluating the effect of long-term injection process according to claim 1, characterized in that: In step 5, the weight coefficient α i The expression is: The expression of decision factor D is:

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