CN111291981B - Oil reservoir well pattern injection and production well group perfection evaluation method - Google Patents

Oil reservoir well pattern injection and production well group perfection evaluation method Download PDF

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CN111291981B
CN111291981B CN202010069970.2A CN202010069970A CN111291981B CN 111291981 B CN111291981 B CN 111291981B CN 202010069970 A CN202010069970 A CN 202010069970A CN 111291981 B CN111291981 B CN 111291981B
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郭文敏
吕爱华
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Abstract

The invention provides an oil reservoir well pattern injection and production well group perfection evaluation method which comprises the steps of establishing a characteristic injection and production well group effective direction evaluation factor X (1), a characteristic injection and production well group control area roundness evaluation factor X (2), a characteristic injection and production well group injection and production vectorization evaluation factor X (3), a characteristic injection and production well group vector control reserve evaluation factor X (4), a characteristic injection and production well group area control rate evaluation factor X (5) and a characteristic injection and production well group reserve control rate evaluation factor X (6), performing association degree calculation on all well groups of an oil reservoir block by utilizing a multi-parameter gray association evaluation principle, and sequencing according to association degree, wherein the higher the association degree is, the higher the injection and production well group perfection is, and the better the well pattern perfection is. The method solves the problem of the well pattern injection and production well group perfection evaluation method of the oil reservoir in the high water content stage, and has very important practical significance for comprehensively evaluating the matching and perfection of the injection and production relation of each well group of the current well pattern and the residual oil.

Description

Oil reservoir well pattern injection and production well group perfection evaluation method
Technical Field
The invention relates to the field of oil field comprehensive adjustment injection well pattern evaluation, in particular to an oil reservoir well pattern injection well pattern perfection evaluation method.
Background
In the development process of the oil field, the oil field is influenced by the reservoir plane, longitudinal heterogeneity and well pattern pitch, after the oil field enters a high water content stage, the difference between well groups and between water injection wells in the well groups gradually increases, the water injection utilization rate is low, the invalid water circulation is serious, the well pattern adjustment is one of the important methods for improving the recovery technology by changing the flow direction of the hydrodynamics, the well group perfection evaluation is the premise of determining the well group contradiction and developing the well pattern adjustment, and the development of the well pattern perfection evaluation has very important engineering practical significance for the discovery of the injection and production well group contradiction and the determination of the later well pattern adjustment mode.
The perfection of the well pattern depends on the matching relation between the form of the well pattern and the residual oil, and the core of the perfection is the actual control condition of the injected water in the area surrounded by the well pattern, the higher the control degree of the injected water on the residual oil is, the smaller the contradiction of the well pattern is, the better the perfection of the well pattern is, and the worse the perfection of the opposite well pattern is, the more injection and production adjustment is needed.
The difficulty in well group perfection evaluation is how to quantitatively describe and evaluate the injection and production control conditions inside the well group and among the well groups according to the static heterogeneous state of the reservoir and the complex distribution of underground residual oil, and how to quantitatively analyze and evaluate the injection and production forms of the central well and surrounding corresponding wells and whether the injection and production well spacing can meet the requirement of multi-directional equalization of injection and production from the aspect of the coupling between the injection and production well network and the geological characteristics.
Disclosure of Invention
The invention aims to solve the technical problems that: in order to overcome the existing difficulties, the invention provides an oil reservoir well pattern injection and production well group perfection evaluation method, which aims to solve the problems of excavation, perfection evaluation and next well pattern adjustment direction of the existing well pattern contradiction, and solves the technical difficulties of the well pattern perfection evaluation method in the high water content stage from the rational matching angle of reservoir static and well pattern well spacing.
The technical scheme adopted for solving the technical problems is as follows: according to the method for evaluating the perfection of the oil reservoir well pattern injection and production well groups, the association degree calculation is carried out on all well groups of an oil reservoir block by utilizing a multi-parameter gray association evaluation principle, the well patterns are ranked according to the association degree, and the higher the association degree is, the higher the perfection of the injection and production well groups is, and the better the well pattern perfection is; the evaluation factors for the multi-parameter gray correlation evaluation comprise an evaluation factor X (1) for representing the effective direction of the injection well group, an evaluation factor X (2) for representing the roundness of the control area of the injection well group, an evaluation factor X (3) for representing the injection well group injection and production vectorization, an evaluation factor X (4) for representing the vector control reserve of the injection well group, an evaluation factor X (5) for representing the area control rate of the injection well group and an evaluation factor X (6) for representing the reserve control rate of the injection well group.
The characteristic injection well group effective direction evaluation factor X (1) is specifically as follows:
wherein: the angle APB, the angle BPC, the angle CPD and the angle DPA are respectively included angles formed by a central well P and surrounding corresponding wells A, B, C, D;
in the corresponding first-line well around the central well, the ratio of the minimum value to the maximum value, namely the angle level difference, of the included angles formed by two adjacent wells and the central well is smaller, the smaller the effective direction evaluation factor X (1) of the injection well group is, the worse the well pattern plane perfection is, the larger the value of the evaluation factor X (1) is seen to be, and the better the well pattern perfection is, namely the larger the evaluation factor X (1) is, the better the well pattern perfection is.
The roundness evaluation factor X (2) of the control area of the characterization injection well group is specifically as follows:
wherein: dis (Dis) AP 、Dis BP 、Dis CP 、Dis DP The distances from the central well to surrounding corresponding wells are respectively; a is that P Controlling the area for the central well; r is R STD Is area A P Is equal to the equivalent circle radius of the steel plate;
area A of the zone controlled by the centerwell P Equivalent radius R STD Calculating the distance between each well and the central well, and comparing the calculated distance with R STD Dividing, and taking the reciprocal of the calculated result when the calculated result is greater than 1; the arithmetic average value obtained by adding all calculation results is the evaluation factor X (2), and the larger the value is, the better the regularity of the well pattern on the plane is indicated, the smaller the value is, the worse the plane regularity of the well pattern is indicated, namely, the larger the evaluation factor X (2) is, the better the model is.
The characteristic injection and production well group injection and production vectoring evaluation factor X (3) is specifically:
wherein: k (K) AP 、K BP 、K CP 、K DP Average permeability of the connecting lines of the central well and the surrounding corresponding wells; kru AP (So AP )、Kru BP (So BP )、Kru CP (So CP )、Kru DP (So DP ) Respectively the sum of average oil-water mobility of the connecting lines of the central well and the surrounding corresponding wells;
in the high water content stage, the plane seepage difference results in poor bursting balance of the injected water, and the evaluation factor X (3) is smaller, so that the seepage resistance in all directions is the same in the optimal state under the ideal vector well pattern condition, i.e. the larger the evaluation factor X (3) is, the better the injection is.
The characteristic injection well group vector control reserve evaluation factor X (4) is specifically:
wherein: CL (CL) AP 、CL BP 、CL CP 、CL DP The visual movable reserves are respectively connected with the central well and the surrounding corresponding wells;the average thickness of the reservoir layers connected with the central well and the surrounding corresponding wells respectively;
calculating the inter-well connection line vision control movable reserves of the central well and the surrounding corresponding wells, and if the difference of the vector control reserves of each direction of the well group is larger, indicating that the difference of the displacement effect of each direction in the well group is larger, namely the ratio of the minimum value to the maximum value of the control reserves of each direction is smaller, the inter-well contradiction in the well group is larger, namely the evaluation factor X (4) is larger and is more optimal.
The characteristic injection well group area control rate evaluation factor X (5) is specifically as follows:
total control area of the well P
A C =A C (1)∪A C (2)∪…∪A C (n)
Wherein: θ i Is the included angle between the ith well and the x axis; dis (i) is the distance between the ith well and the center well; a is that C (i) The control area formed by any two water injection wells and production wells; n is the number of corresponding total wells around the central well;
inside the central well group, taking a static control area surrounded by a line well connecting line around the central well as a base number, and the area percentage under the actual control of the injection and production wells in all directions; in an ideal state, the static control area of the well control should be controlled by the injection well entirely, i.e. the area control rate evaluation factor is 1, i.e. the larger and more optimal the evaluation factor X (5).
The characteristic injection well group reserve control rate evaluation factor X (6) is specifically:
wherein:is the injection and production area A C ∩A P A movable reserve under control; />Controlling total area A for a centerwell P Lower movable reserves;
and in the central well group, taking the total movable reserve under the static control area surrounded by the line connection of the first-line wells around the central well as a base, and the movable reserve percentage under the actual control of the injection and production well in each direction, wherein the maximum value of the reserve control rate evaluation factor is 1, namely the larger and the more optimal the evaluation factor X (6) is.
Based on the scheme, the evaluation factors of each well group are calculated firstly
X (1), X (2), X (3), X (4), X (5) and X (6) to construct an initial sequence data factor set; secondly, carrying out normalization processing on the factor set data, and constructing a difference sequence; calculating the association coefficient matrix and calculating the weight value again; and finally, well pattern perfection association degree calculation under the multi-factor parameters is carried out, and well pattern perfection evaluation is carried out on each injection and production well group by using the association degree coefficient.
The method for evaluating the perfection of the oil reservoir well pattern injection and production well groups has the advantages that a plurality of evaluation factors are established from the static characteristics of the well pattern and the seepage resistance between the injection and production wells, the gray correlation principle is adopted to comprehensively evaluate each well group in an oil reservoir block, the evaluation result of the injection and production well group with lower correlation degree is poor, the optimization of the injection and production relationship of the well pattern or the well distance is required, and the method has extremely important theoretical and practical significance for finding contradiction of the oil field well pattern and implementing suggestions of next field measures.
Drawings
The invention will be further described with reference to the drawings and examples.
Fig. 1 is a schematic flow chart of the present invention.
Fig. 2 is a schematic diagram of the effective direction of the injection well group.
Fig. 3 is a schematic diagram of injection well group control radius calculation.
FIG. 4 is a schematic illustration of a calculation of a control area for a central well.
Fig. 5 is a schematic diagram of an injection and production control area region of an injection and production well.
Detailed Description
The invention will now be described in further detail with reference to the accompanying drawings. The drawings are simplified schematic representations which merely illustrate the basic structure of the invention and therefore show only the structures which are relevant to the invention.
The method for evaluating the perfection of the oil reservoir well pattern injection and production well group shown in fig. 1 comprises the following steps:
step one, calculating an evaluation factor of the effective direction of the injection well group
For the large-area self-contained oil reservoir, the method for evaluating the injection and production perfection of the central well group is established as shown in fig. 2, wherein ABCD … is a first-line well corresponding to the periphery of the central well, letter numbers are arranged in a counterclockwise order, P is the position of the central well, and angles ++APB, ++BPC, ++CPD and++DPA corresponding to the central well and the peripheral well are calculated respectively.
Calculating the evaluation factor of the effective direction of the injection well group, namely the angle level difference:
calculating roundness evaluation factors of control areas of injection well groups
Calculating the area controlled by the center well P, assuming that S is any point on the inter-well arc, the distance Dis between the APs AP The included angle between the AP and the anticlockwise direction of the x axis is +.APX; distance Dis between BP BP The included angle between BP and the anticlockwise direction of the x-axis is BPX; the distance between any points SP is Dis SP The included angle between SP and the anticlockwise direction of the x axis is SPX.
Assuming that the AB arc radius satisfies a linear relationship, the distance Dis from point S to P SP As shown in fig. 3, it is specifically expressed as:
for the infinitesimal area dA P As shown in fig. 4, can be equivalently reduced to an equilateral triangle, in which:
the arc length of the infinitesimal body: ds=dis SP ·dθ
Then:
thereby respectively calculating an AB arc line, a BC arc line, a CD arc line and a DA arc line to obtain the total area A of the area controlled by the central well P P
For a gridded geologic model, its area A P Is the sum of the grid areas enclosed by the areas.
Area A controlled by the center well P P Will A P Equivalent to a central circle, i.e. radius R STD
And (3) calculating:
calculating a roundness evaluation factor of the oil well pattern:
step three, calculating injection and production vectoring evaluation factors of injection and production well groups
For the inside of the injection and production well group, the injection and production well distance in each direction is Dis AP 、Dis BP 、Dis CP 、Dis DP Average residual oil saturation of corresponding connection is So AP 、So BP 、So CP 、So DP The average permeability of the corresponding connection line is K AP 、K BP 、K CP 、K DP Wherein:
according to the relative permeability curve, respectively calculating average oil and water relative permeability under average residual oil saturation on each injection and production line, and calculating the sum Kru of oil-water fluidity AP (So AP )、Kru BP (So BP )、Kru CP (So CP )、Kru DP (So DP )
Fluidity of oil and water:
thus obtaining the well group injection and production well pattern vectorization evaluation factor:
calculating a vector control reserve evaluation factor of the injection well group
And (5) calculating the inter-well visual control movable reserves in the control range of the injection and production well group:
wherein: CL (CL) AP 、CL BP 、CL CP 、CL DP The visual movable reserves are respectively connected with the central well and the surrounding corresponding wells;the average thickness of the reservoir layers is respectively the connection line between the central well and the surrounding corresponding wells.
Step five, calculating an area control rate evaluation factor of the injection well group
The method for determining the control area of the injection well is a circular area formed by connecting injection wells, namely the control area A of two injection wells C The two lines of the injection well can be approximately considered as circular areas of diameter, as shown in fig. 5.
Control area A formed by any two water injection wells and production well C (i):
Wherein: θ i Is the included angle between the ith well and the x axis; dis (i) is the distance between the ith well and the center well; a is that C (i) The control area formed by any two water injection wells and production wells; n is the number of total wells around the center well.
Total injection and production control area A C
A C =A C (1)∪A C (2)∪…∪A C (n)
Injection well group area control rate evaluation factor is with regional area A of injection well control C Area A controlled by production well P P Is a cross-over area A of (2) C ∩A P Area A controlled by production well P P The ratio is expressed as:
step six, calculating the reserve control rate evaluation factor of the injection well group
According to the method for evaluating the area control rate of the injection well group, the injection well group injection and production control area A is calculated respectively C ∩A P Lower movable reserveAnd the total control area A of the central well P Lower movable reserve->And (3) an injection well group reserve control rate evaluation factor X (6):
seventh, well group multi-parameter grey correlation evaluation calculation
(1) Construction of initial sequence data factor set
Calculating parameters in the control range of each well group by taking each central well of the block as a core to form a comparison sequence: factor sets of X (i) = { X (1), X (2), X (3), X (4), X (5), X (6) }.
Since the meaning of the representation of the respective variables is different, the data size among the independent variables is not comparable, and therefore, the normalization processing needs to be performed on the original data, specifically as follows:
(1) the bigger and the more optimal:
(2) smaller and more optimal:
thereby obtaining a function matrix R
R=|b ik | (m+1)×n
(2) Difference sequence calculation
The difference sequence is the difference between the calculated reference sequence and the comparison sequence, and is represented by the following formula:
Δ 0i (k)=|x 0 (k)-x i (k)|
wherein: x is x 0 (k) Is the kth column maximum of the original data.
(3) Calculating a correlation coefficient matrix
The association coefficient is the association degree of the comparison sequence and the reference sequence, and the specific formula is as follows:
wherein: ρ is a resolution factor, and the interval is [0,1], typically 0.5.
(4) Calculating weight value
Weight coefficient:
after W (k) normalization:
(5) Correlation degree determination
Wherein: gamma ray i W (k) is a gray correlation value and a weight coefficient of each factor.
And (3) calculating the relevance of all well groups of the whole block, and sorting according to the relevance, wherein the higher the relevance is, the higher the perfection of the injection and production well groups is.
According to the evaluation method, taking a water injection well group in the center of a certain block as an example, evaluation calculation is performed, and the evaluation results are shown in table 1:
table 1, well group perfection evaluation results table for central water injection well of certain area
With the above-described preferred embodiments according to the present invention as an illustration, the above-described descriptions can be used by persons skilled in the relevant art to make various changes and modifications without departing from the scope of the technical idea of the present invention. The technical scope of the present invention is not limited to the description, but must be determined according to the scope of claims.

Claims (1)

1. A method for evaluating the perfection of an oil reservoir well pattern injection and production well group is characterized by comprising the following steps: calculating the association degree of all well groups of the oil reservoir block by utilizing a multi-parameter gray association evaluation principle, and sequencing according to the association degree; the evaluation factors for multi-parameter gray correlation evaluation comprise an evaluation factor X (1) for representing the effective direction of the injection well group, an evaluation factor X (2) for representing the roundness of the control area of the injection well group, an evaluation factor X (3) for representing the injection well group injection and production vectorization, an evaluation factor X (4) for representing the vector control reserve of the injection well group, an evaluation factor X (5) for representing the area control rate of the injection well group and an evaluation factor X (6) for representing the reserve control rate of the injection well group;
the characteristic injection well group effective direction evaluation factor X (1) is specifically as follows:
wherein: the angle APB, the angle BPC, the angle CPD and the angle DPA are respectively included angles formed by a central well P and surrounding corresponding wells A, B, C, D;
in the corresponding first-line well around the central well, the ratio of the minimum value to the maximum value, namely the angle level difference, of the included angles formed by two adjacent wells and the central well is that the smaller the effective direction evaluation factor X (1) of the injection and production well group is, the worse the well pattern plane perfection is, and for a homogeneous regular well pattern, the maximum value of the evaluation factor X (1) is 1, the larger the value of the evaluation factor X (1) is, the better the well pattern perfection is, namely the larger and the better the evaluation factor X (1) is;
the roundness evaluation factor X (2) of the control area of the characterization injection well group is specifically as follows:
wherein: dis (Dis) AP 、Dis BP 、Dis CP 、Dis DP The distances from the central well to surrounding corresponding wells are respectively; r is R STD The equivalent circle radius of the control area for the central well;
calculating roundness evaluation factors of the control area of the injection well group: calculating the area controlled by the center well P, assuming that S is any point on the inter-well arc, the distance Dis between the APs AP The included angle between the AP and the anticlockwise direction of the x axis is +.APX; distance Dis between BP BP The included angle between BP and the anticlockwise direction of the x-axis is BPX; the distance between any points SP is Dis SP The included angle between the SP and the anticlockwise direction of the x axis is SPX;
assuming that the AB arc radius satisfies a linear relationship, the distance Dis from point S to P SP Expressed as:
for the infinitesimal area dA P Can be equivalently reduced to an equilateral triangle, wherein:
the arc length of the infinitesimal body: ds=dis SP ·dθ
Then:
thereby respectively calculating an AB arc line, a BC arc line, a CD arc line and a DA arc line to obtain the total area A of the area controlled by the central well P P
For a gridded geologic model, its area A P Is the sum of the grid areas surrounded by the areas,
area A controlled by the center well P P Will A P Equivalent to a central circle, i.e. radius R STD
Area A of the zone controlled by the centerwell P Equivalent radius R STD Calculating the distance between each well and the central well, and comparing the calculated distance with R STD Dividing, and taking the reciprocal of the calculated result when the calculated result is greater than 1; the arithmetic mean value calculated by adding all calculation results is an evaluation factor X (2), and the larger the value is, the better the regularity of the well pattern on the plane is indicated, the smaller the value is, the worse the regularity of the plane of the well pattern is indicated, and the larger and the better the evaluation factor X (2) is;
the characteristic injection and production well group injection and production vectoring evaluation factor X (3) is specifically:
wherein: k (K) AP 、K BP 、K CP 、K DP Average permeability of the connecting lines of the central well and the surrounding corresponding wells; kru AP (So AP )、Kru BP (So BP )、Kru CP (So CP )、Kru DP (So DP ) Respectively the sum of average oil-water mobility of the connecting lines of the central well and the surrounding corresponding wells;
for the inside of the injection and production well group, the injection and production well distance in each direction is Dis AP 、Dis BP 、Dis CP 、Dis DP Average residual oil saturation of corresponding connection is So AP 、So BP 、So CP 、So DP The average permeability of the corresponding connection line is K AP 、K BP 、K CP 、K DP Wherein:
according to the relative permeability curve, respectively calculating average oil and water relative permeability under average residual oil saturation on each injection and production line, and calculating the sum Kr of oil-water fluidityu AP (So AP )、Kru BP (So BP )、Kru CP (So CP )、Kru DP (So DP )
Fluidity of oil and water:
the ratio of the minimum value to the maximum value of the seepage resistance of the central well to the corresponding wells around the central well, the plane seepage difference, the sudden inflow balance of the injected water is poor in the high water content stage, the evaluation factor X (3) is small, and in order to realize balanced injection and production, under the ideal vector well pattern condition, the seepage resistance in all directions is the same as the optimal state, and the evaluation factor X (3) is larger and more optimal;
the characteristic injection well group vector control reserve evaluation factor X (4) is specifically:
wherein: CL (CL) AP 、CL BP 、CL CP 、CL DP The visual movable reserves are respectively connected with the central well and the surrounding corresponding wells;the average thickness of the reservoir layers connected with the central well and the surrounding corresponding wells respectively; s is S or Average remaining oil saturation for the centerwell;
calculating inter-well connection line visual control movable reserves of a central well and surrounding corresponding wells, wherein if the difference of vector control reserves of each direction of the well group is larger, the difference of displacement effects of each direction in the well group is larger, namely the ratio of the minimum value to the maximum value of the control reserves of each direction is smaller, the inter-well contradiction in the well group is larger, and the evaluation factor X (4) is larger and is more optimal;
the characteristic injection well group area control rate evaluation factor X (5) is specifically as follows:
total control area of the well P
A C =A C (1)∪A C (2)∪···∪A C (n)
Wherein: θ i Is the included angle between the ith well and the x axis; dis (i) is the distance between the ith well and the center well; a is that C (i) The control area formed by any two water injection wells and production wells; n is the number of corresponding total wells around the central well;
inside the central well group, taking a static control area surrounded by a line well connecting line around the central well as a base number, and the area percentage under the actual control of the injection and production wells in all directions; under ideal conditions, the static control area of the control of the central well is controlled by the injection well, namely, the area control rate evaluation factor is 1, and the larger and the more optimal the evaluation factor X (5) is;
the characteristic injection well group reserve control rate evaluation factor X (6) is specifically:
wherein:is the injection and production area A C ∩A P A movable reserve under control; />Controlling total area A for a centerwell P Lower movable reserves;
and in the central well group, taking the total movable reserve under the static control area surrounded by the line connection of the first line well around the central well as a base, wherein the movable reserve percentage under the actual control of the injection well in each direction is 1, and the maximum value of the reserve control rate evaluation factor is 1, and the larger and the more optimal the evaluation factor X (6) is.
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012134497A1 (en) * 2011-04-01 2012-10-04 QRI Group, LLC Method for dynamically assessing petroleum reservoir competency and increasing production and recovery through asymmetric analysis of performance metrics
CN102930345A (en) * 2012-10-12 2013-02-13 中国石油大学(华东) Self-adaptive well pattern optimization method based on gradient algorithm
CN103422849A (en) * 2013-07-18 2013-12-04 中国石油天然气股份有限公司 Well pattern rebuilding method and device for water-injection development of old oil field
CN105401927A (en) * 2015-11-27 2016-03-16 中国石油天然气股份有限公司 Method and device for determining well pattern and well spacing of oil reservoir
CN105626055A (en) * 2014-11-07 2016-06-01 中国石油化工股份有限公司 Evaluation method for oil reservoir reserve utilization quality in ultrahigh water-cut stage
CN106894800A (en) * 2017-02-23 2017-06-27 中国海洋石油总公司 A kind of profile control well selection decision-making technique suitable for Offshore Heavy Oil Field oil reservoir
CN107829718A (en) * 2017-02-10 2018-03-23 中国石油化工股份有限公司 Oil reservoir well pattern and injection-production program Optimization Design based on balanced water drive theory

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105095986B (en) * 2015-06-23 2018-12-25 中国石油天然气股份有限公司 The method of stratified reservoir overall yield prediction

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012134497A1 (en) * 2011-04-01 2012-10-04 QRI Group, LLC Method for dynamically assessing petroleum reservoir competency and increasing production and recovery through asymmetric analysis of performance metrics
CN102930345A (en) * 2012-10-12 2013-02-13 中国石油大学(华东) Self-adaptive well pattern optimization method based on gradient algorithm
CN103422849A (en) * 2013-07-18 2013-12-04 中国石油天然气股份有限公司 Well pattern rebuilding method and device for water-injection development of old oil field
CN105626055A (en) * 2014-11-07 2016-06-01 中国石油化工股份有限公司 Evaluation method for oil reservoir reserve utilization quality in ultrahigh water-cut stage
CN105401927A (en) * 2015-11-27 2016-03-16 中国石油天然气股份有限公司 Method and device for determining well pattern and well spacing of oil reservoir
CN107829718A (en) * 2017-02-10 2018-03-23 中国石油化工股份有限公司 Oil reservoir well pattern and injection-production program Optimization Design based on balanced water drive theory
CN106894800A (en) * 2017-02-23 2017-06-27 中国海洋石油总公司 A kind of profile control well selection decision-making technique suitable for Offshore Heavy Oil Field oil reservoir

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
牛74块井网适应性评价及方案调整;闫文华;石晓博;杨士萍;牟勇;;科学技术与工程(第17期);95-98 *

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