Method for evaluating the effect of long-term augmented injection process

Abstract

The application discloses a long-acting injection-increasing process effect evaluation method, and specific steps are as follows: step 1, obtaining the original porosity and the porosity after acidification, the original permeability and the permeability after acidification, the wellbore radius and the reservoir injection unit radius according to geological data, and calculating the porosity variation amplitude and the permeability variation amplitude; step 2, measuring the water absorption index before acidification and the water absorption index after acidification, calculating the injection-increasing multiple and the skin factor after acidification, determining the injection well pressure drop index IPI and the effective days of acidification measures; step 3, performing dimensionless processing on the parameters obtained in step 1 and step 2; step 4, calculating the grey correlation coefficient and the correlation degree; and step 5, calculating the weight coefficient and the decision factor. The method solves the problems that the quantitative evaluation method of the injection-increasing process effect in the prior art is complex and the evaluation parameters are difficult to obtain.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of oilfield water injection well acidizing and plugging removal, and particularly relates to a long-acting injection increasing process effect evaluation method. BACKGROUND

[0002] In the water injection development process, with the extension of water injection time, the injection capacity of most water injection wells tends to decrease. For water injection wells in ultra-low permeability reservoirs, this phenomenon is particularly prominent, and some water injection wells in individual blocks have high-pressure under-injection or even cannot inject water. In view of this problem, a long-acting injection increasing acidizing process for water injection wells is developed on the market, which solves the problem of high-pressure under-injection or non-injection of water injection wells by combining local pressure increase with acidizing, so as to achieve the purpose of comprehensive treatment and increasing the injected water volume.

[0003] At present, there are few quantitative evaluation methods for the effect of long-acting injection increasing process. The patent with the patent name of "a biological nano pressure reduction and injection increasing technology effect evaluation method" (CN114109376A) mainly quantitatively evaluates the effect of biological nano pressure reduction and injection increasing technology, but the calculation method is too complex and the evaluation parameters are difficult to obtain. The remaining methods are only limited to judging whether it is effective through the changes of wellhead pressure and injection volume, and cannot quantitatively evaluate the improvement effect.

[0004] Therefore, how to quantitatively evaluate the effect of long-acting injection increasing process simply and easily is a technical problem to be solved by those skilled in the art. SUMMARY

[0005] The purpose of the present application is to provide a long-acting injection increasing process effect evaluation method, which solves the problem of complex quantitative evaluation method of injection increasing process effect and difficult to obtain evaluation parameters in the prior art.

[0006] The technical solution adopted by the present application is a long-acting injection increasing process effect evaluation method, and the specific steps are as follows:

[0007] Step 1: obtaining the original porosity of the water injection well according to the geological data and the porosity after acidizing the original permeability K0 and the permeability K1 after acidizing, the wellbore radius r w and the reservoir water injection unit radius r e , calculating the porosity change amplitude the permeability change amplitude K Z ;

[0008] Step 2: measuring the water absorption index I before acidizing of the water injection well w1 and the water absorption index I after acidizing w2 and calculating the injection increasing multiple Z and the skin factor S after acidizing, determining the water injection well pressure drop index IPI and the effective days T of acidizing measures;

[0009] Step 3, the parameters obtained in step 1 and step 2 are dimensionless processed;

[0010] Step 4, the grey correlation coefficient ξ is calculated i , the correlation degree γ is calculated i ;

[0011] Step 5, the weight coefficient α i and the decision factor D are calculated.

[0012] The present application is also characterized in that,

[0013] In step 1, the expression of the porosity variation amplitude K is:

[0014]

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

[0016] In step 1, the expression of the permeability variation amplitude K Z is:

[0017]

[0018] In the formula, K0 is the original permeability of the injection well, with the unit of 10 -3 μm 2 ; K1 is the permeability of the injection well after acidification, with the unit of 10 -3 μm 2 .

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

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

[0021]

[0022] In the formula, I w1 is the water absorption index before acidification of the injection well, with the unit of m 3 / (dMPa); I w2 is the water absorption index after acidification of the injection well, with the unit of 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 injection index before acidizing the injection well, with the unit of m 3 / (d MPa); I w2 is the water injection index after acidizing the injection well, with the unit of m 3 / (d MPa); r e is the radius of the water injection unit of the oil reservoir, with the unit of m; r w is the radius of the wellbore of the injection well, with the unit of m.

[0026] In step 2, the injection well pressure drop index IPI can be obtained from the wellhead pressure drop curve after acidizing the injection well, which is measured by a wellhead automatic pressure recorder.

[0027] In step 3, the expression for the dimensionless treatment of the parameters is as follows:

[0028]

[0029] In the formula, x i is each evaluation parameter, and i is the serial number of the evaluation parameter; x i is the dimensionless evaluation parameter; x min is the minimum value of the same type of evaluation parameter; and x max is the maximum value of the same type of evaluation parameter.

[0030] In step 4, the expression for the grey correlation coefficient ξ i is as follows:

[0031]

[0032] In the formula, X0 is the reference sequence, X i is the comparison sequence; |X i (k)-X0(k)| represents the absolute value of the kth point of the sequence X i and X0; represents the two-pole minimum absolute value of the two sequences; represents the two-pole maximum absolute value of the two sequences; and p is the resolution coefficient, generally taken as 0.5.

[0033] In the formula, the reference sequence is a sequence formed by the optimal combination of the evaluation parameters;

[0034] The expression for the correlation degree γ i is as follows:

[0035]

[0036] In step 5, the expression for the weight coefficient a i is as follows:

[0037]

[0038] Expression of decision factor D:

[0039]

[0040] The beneficial effects of the present application are: the long-acting injection process effect evaluation method only needs to determine the porosity, permeability, water absorption index before and after acidizing the formation, the pressure drop curve IPI value after acidizing and the effective days of the measures, etc. The quantitative evaluation of the injection process effect can be realized only with a few parameters, and the required evaluation parameters are easy to obtain, the calculation method and implementation process are simple, and there is corresponding evaluation theoretical basis. BRIEF DESCRIPTION OF DRAWINGS

[0041] Figure 1 The injection well indicator curve before and after well acidizing in the method embodiment 4 of the present application;

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

[0043] Figure 3 The decision factor cumulative probability graph in the method embodiment 4 of the present application. DETAILED DESCRIPTION

[0044] The present application will be described in detail below in combination with the drawings and specific embodiments.

[0045] Embodiment 1

[0046] The present application provides a long-acting injection process effect evaluation method, which is specifically implemented according to the following steps:

[0047] Step 1, obtaining the original porosity of the injection well according to the geological data and the porosity after acidizing The original permeability K0 and the permeability K1 after acidizing, the wellbore radius r w and the oil reservoir injection unit radius r e , calculating the porosity change amplitude The permeability change amplitude K Z ;

[0048] Step 2, determining the water absorption index I before acidizing the injection well w1 and the water absorption index I after acidizing w2 and calculating the injection multiple Z and the skin factor S after acidizing, determining the injection well pressure drop index IPI and the effective days T of the acidizing measures according to the production data;

[0049] Step 3, the parameters obtained in step 1 and step 2 are dimensionless, and the dimensionless parameters include the porosity variation amplitude The permeability variation amplitude K Z , the injection multiple Z, the skin factor S after acidification, the injection well pressure drop index IPI, and the effective days T of acidification measures.

[0050] Step 4, the grey correlation coefficient ξ is calculated i , and the correlation degree γ is calculated i .

[0051] Step 5, the weight coefficient α i and the decision factor D are calculated, and the injection process effect is evaluated according to the decision factor D.

[0052] The long-acting injection process effect evaluation method can realize quantitative evaluation of the injection process effect by determining the porosity, the permeability, the water absorption index before and after acidification, the IPI value of the pressure drop curve after acidification, and the effective days of measures, the required evaluation parameters are easy to obtain, and the parameters involved are few and have corresponding evaluation theoretical basis.

[0053] Example 2

[0054] On the basis of example 1, in step 1, the porosity variation amplitude is expressed as:

[0055]

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

[0057] The permeability variation amplitude K Z is expressed as:

[0058]

[0059] In the formula, K0 is the original permeability of the injection well, and the unit is 10 -3 μm 2 ; K1 is the permeability of the injection well after acidification, and the unit is 10 -3 μm 2 .

[0060] On the basis of example 1, in step 2, the water absorption index I w1 before acidification of the injection well and the water absorption index I w2 after acidification are both daily water injection amounts under unit pressure difference, which can be obtained through the change curve of the wellhead pressure with the daily water injection amount, or the water absorption index I w1 before acidification of the injection well and the water absorption index Iw2 All are apparent water absorption indexes, and the apparent water absorption index is a derivative of a slope of a wellhead pressure curve with respect to a daily injection volume;

[0061] The expression of the injection multiple Z is:

[0062]

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

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

[0065]

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

[0067] The injection well pressure drawdown index IPI can be obtained from a wellhead pressure drawdown curve after acidification of the injection well, and the wellhead pressure drawdown curve after acidification of the injection well is measured by using a wellhead automatic pressure recorder.

[0068] In step 3, the expression of the parameter for non-dimensional processing is:

[0069]

[0070] In the formula, x i is each evaluation parameter, and i is the evaluation parameter serial number; X i is the non-dimensionalized evaluation parameter; x min is a minimum value of the same type of evaluation parameter; x max is a maximum value of the same type of evaluation parameter;

[0071] In step 4, the expression of the grey correlation coefficient ξ i is:

[0072]

[0073] In the formula, X0 is a reference sequence, and X i is a comparison sequence; |X i(k) -X0(k) | represents the absolute value of sequence X at the kth point i the absolute value of X0 at the kth point; represents the two-pole minimum absolute value of two sequences; represents the two-pole maximum absolute value of two sequences; p is a resolution coefficient, generally 0.5;

[0074] wherein the reference sequence is a sequence formed by the optimal parameter combination in each evaluation parameter, and the comparison sequence is a sequence formed by each parameter combination participating in evaluation;

[0075] correlation degree γ i The expression of is:

[0076]

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

[0078]

[0079] The expression of decision factor D is:

[0080]

[0081] Finally, the effect of augmented injection is classified according to the inflection point of the cumulative probability curve by making the cumulative probability graph of the decision factor.

[0082] Wherein, steps 3-5 can be automatically realized by 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 w1 and the water absorption index I w2 after acidification are apparent water absorption indexes, and the apparent water absorption index is the derivative of the slope of the wellhead pressure curve with the change of daily water injection volume.

[0085] Example 4

[0086] Taking 12 acidification augmented injection measure wells in L block as an example, the basic information of 12 wells is as follows:

[0087] Table 1 well basic information table

[0088]

[0089] According to the basic information of 12 wells and the indication curves of water injection wells before and after acidification shown in Figure 1 and Figure 2The illustrated acidizing post-wellhead pressure drop curve is calculated to obtain the porosity variation range of each well Permeability variation range K Z Water absorption index I before acidizing w1 Water absorption index I after acidizing w2 Injection multiple Z, skin factor 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 evaluation required parameters are summarized as shown in the following table.

[0093] Table 3 summary of evaluation parameters

[0094]

[0095] The final calculation of each well decision factor is as shown in Table 4 and Figure 3 ; by making the decision factor cumulative probability graph, according to the inflection point of the cumulative probability curve, the injection effect is classified, the greater the decision factor D value, the better the corresponding 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-acting injection enhancement technology, characterized in that, The specific steps are as follows: Step 1: Based on geological data, obtain the original porosity φ0 and porosity φ1 after acidizing, the original permeability K0 and permeability K1 after acidizing, and the wellbore radius r. w and the radius r of the reservoir water injection unit e Calculate the porosity variation φ Z Permeability variation K Z ; In step 1, the porosity variation φ Z The expression is: （1） In the formula, φ0 represents the original porosity of the injection well, in units of %; φ1 represents the porosity of the injection well after acidizing, in units of %. In step 1, the permeability change range K Z The expression is: （2） In the formula, K0 is the original permeability of the injection well, in units of 10. -3 μm 2 K1 represents the permeability of the injection well after acidizing, in units of 10⁻⁶. -3 μm 2 ; Step 2, determine the water absorption index I of the injection well before acidizing. w1 and the water absorption index I after acidification w2 The injection multiplier Z and the skin coefficient S after acidizing were calculated to determine the pressure drop index IPI of the injection well and the effective number of days T of the acidizing measures. Step 3: Perform 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 ; In step 4, the grey relational coefficient ξ i The expression is: （6） In the formula, As a reference sequence, For comparison sequences; Represents a sequence and In the k The absolute value of a point; This represents the two smallest absolute values ​​at their extremes; It represents the maximum absolute value at both ends of the two sequences; ρ is the resolution coefficient, which is usually taken as 0.5; Among them, the reference sequence is the sequence composed of the optimal combination of each evaluation parameter, and the comparison sequence is the sequence composed of the combination of each parameter participating in the evaluation. correlation γ i The expression is: （7）； Step 5, calculate the weighting coefficients α i And the decision factor D, by creating a cumulative probability diagram of the decision factor, 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 injection effect of the corresponding injection well.

2. The method for evaluating the effect of long-acting injection enhancement process according to claim 1, characterized in that, In step 2, the water absorption index I before acidizing the injection well w1 and the water absorption index I after acidification w2 All figures represent the daily water injection volume under unit pressure difference, obtained from the curve of wellhead pressure versus daily water injection volume.

3. The method for evaluating the effect of long-acting injection enhancement process according to claim 1, characterized in that, In step 2, the expression for the betting multiplier Z is: （3） In the formula, I w1 The water absorption index of the injection well before acidizing is expressed in meters. 3 / (d MPa); I w2 The water absorption index after acidizing the injection well is expressed in m³. 3 / (d MPa).

4. The method for evaluating the effect of long-acting injection enhancement process according to claim 1, characterized in that, In step 2, the expression for the epidermal coefficient S after acidification is: （4） In the formula, I w1 The water absorption index of the injection well before acidizing is expressed in meters. 3 / (d MPa); I w2 The water absorption index after acidizing the injection well is expressed in m³. 3 / (d MPa); r e r is the radius of the reservoir water injection unit, in meters (m). w This represents the radius of the water injection well shaft, in meters (m).

5. The method for evaluating the effect of long-acting injection enhancement process according to claim 1, characterized in that, In step 2, the injection well pressure drop index (IPI) is obtained from the wellhead pressure drop curve after acidizing the injection well. The wellhead pressure drop curve after acidizing the injection well is measured using an automatic wellhead pressure recorder.

6. The method for evaluating the effect of long-acting injection enhancement process according to claim 1, characterized in that, In step 3, the expression for dimensionless processing of the parameters is: （5） In the formula, Here are the evaluation parameters, where i is the parameter number. These are the dimensionless evaluation parameters; It is the minimum value of similar evaluation parameters; This represents the maximum value of a similar evaluation parameter.

7. The method for evaluating the effect of long-acting injection enhancement process according to claim 1, characterized in that, In step 5, the weighting coefficient α i The expression is: （8） The expression for decision factor D: （9）。

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