CN111832951A - Method and system for evaluating oil reservoir development value of small fault block ultra-low permeability reservoir - Google Patents
Method and system for evaluating oil reservoir development value of small fault block ultra-low permeability reservoir Download PDFInfo
- Publication number
- CN111832951A CN111832951A CN202010694422.9A CN202010694422A CN111832951A CN 111832951 A CN111832951 A CN 111832951A CN 202010694422 A CN202010694422 A CN 202010694422A CN 111832951 A CN111832951 A CN 111832951A
- Authority
- CN
- China
- Prior art keywords
- parameter
- reservoir
- evaluation
- determining
- low permeability
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Mining
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Agronomy & Crop Science (AREA)
- Primary Health Care (AREA)
- Mining & Mineral Resources (AREA)
- Animal Husbandry (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Marine Sciences & Fisheries (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention discloses a method for evaluating the oil reservoir development value of a small fault block ultra-low permeability reservoir, which comprises the following steps: determining parameters related to the oil reservoir of the small fault block ultra-low permeability reservoir, and establishing an evaluation parameter index system, wherein the evaluation parameter index system comprises the following steps: an oil deposit parameter index, a reservoir layer parameter index and a productivity parameter index; determining the evaluation standard of the parameters and the weight of each parameter; obtaining an evaluation matrix of the parameters of the block to be evaluated according to the evaluation standard and the actual values of the parameters of the block to be evaluated of the small fault block ultra-low permeability reservoir oil deposit; and obtaining the evaluation result of the small fault block ultra-low permeability reservoir oil deposit according to the weight of each parameter and the evaluation matrix of the parameter. And judging the development value of the oil reservoir of the small fault block ultra-low permeability reservoir according to the evaluation result. The ordered utilization of the small fault block ultra-low permeability reservoir is effectively guided, and the development level and the benefit are improved.
Description
Technical Field
The invention belongs to the technical field of oil and gas field development, and particularly relates to a method and a system for evaluating the oil reservoir development value of a small fault block ultra-low permeability reservoir.
Background
Currently, evaluation research on ultra-low permeability reservoirs mainly comprises two aspects, namely, the first aspect relates to comprehensive evaluation of reservoir logging, which is based on logging information and combines reservoir analysis information to evaluate the reservoir macroscopically. The corresponding relation between the four-sex relations is mainly considered to change along with the change of the lithology. Therefore, corresponding parameter interpretation models are mostly established aiming at different lithologies, and finally, comprehensive evaluation of the reservoir is realized. From the evaluation result, the micro seepage characteristics are considered less from the macroscopic perspective, the evaluation is not fine enough, and the requirement on effective evaluation of the low-permeability compact reservoir can not be met.
The second aspect relates to comprehensive evaluation of reservoir geology, which is based on physical property characteristic parameters, micro-pore structure parameters and petrology characteristic parameters and carries out comprehensive evaluation on a reservoir by using a fuzzy comprehensive evaluation and cluster analysis method. The evaluation result is relatively reliable from the aspects of the quality of the reservoir, but for the complex small fault block oil reservoir, the evaluation method is far from meeting the requirement of oil field development exploitation decision.
The productivity and the permeability of a common oil reservoir have better correlation, the permeability is high, the productivity is high, and the quality of the reservoir can be generally clearly divided through physical properties. However, for two oil reservoirs with similar permeability in an ultra-low permeability reservoir, the productivity of the oil reservoirs is likely to have larger difference, even the oil reservoirs with relatively low permeability are still higher in productivity, and the development effect is still better, which indicates that for the ultra-low permeability reservoir, the relative quality of the reservoir is difficult to judge only by physical parameters, and multi-parameter comprehensive evaluation is needed to guide the effective utilization of the reserves.
From the current research conditions at home and abroad, the comprehensive reservoir evaluation technical method is relatively mature from the perspective of reservoir evaluation, and the quality of the reservoir can be judged to a certain extent. However, reservoirs are finally developed, whether the reservoirs are effective or not after development is good or not is judged, and from the viewpoint, the representativeness of evaluation parameter selection is not comprehensive, and the parameters are not brought into research at present.
The evaluation parameter selection is not comprehensive enough. The comprehensive evaluation of the reservoir involves many parameters, and many factors have a complex relationship, and the factors are not independent from each other, and there is an influence of uncertainty among them, so it is difficult to quantitatively characterize with a fine linear mathematical method. The choice of parameters may vary greatly from station to station. From the current technical research situation, the method mainly considers more geological factors, does not consider the scale effect and economic effect of the oil reservoir, and cannot make quick judgment on whether the oil reservoir of the reservoir can be used economically and effectively or not.
Disclosure of Invention
The present invention is directed to solving, at least in part, some of the problems in the related art. Therefore, the first purpose of the invention is to provide a method for evaluating the oil reservoir development value of a small-fault-block ultra-low permeability reservoir, and establish a set of multi-parameter reservoir comprehensive evaluation judgment technology aiming at whether the oil reservoir can be used economically and effectively. The technology selects parameters with relatively complete representativeness such as an oil deposit macroscopic parameter, a reservoir macroscopic characteristic parameter, a reservoir microscopic seepage characteristic parameter, a petrology parameter, an initial productivity parameter and the like to establish an index system for the comprehensive evaluation of the ultra-low permeability sandstone reservoir, and the evaluation result can provide a direct reference basis for whether the oil deposit can effectively move or not; the technical effect of effectively judging the oil reservoir development value of the small-fault-block ultra-low permeability reservoir is achieved.
The second purpose of the invention is to provide a system for evaluating the development value of the small fault block ultra-low-permeability reservoir.
A third object of the invention is to propose a non-transitory computer-readable storage medium.
In order to achieve the above object, an embodiment of the first aspect of the present invention provides a method for evaluating the development value of a small-fault block ultra-low permeability reservoir, comprising: determining parameters related to the oil reservoir of the small fault block ultra-low permeability reservoir, and establishing an evaluation parameter index system, wherein the evaluation parameter index system comprises the following steps: an oil deposit parameter index, a reservoir layer parameter index and a productivity parameter index; determining the evaluation standard of the parameters and the weight of each parameter; obtaining an evaluation matrix of the parameters of the block to be evaluated according to the evaluation standard and the actual values of the parameters of the block to be evaluated of the small fault block ultra-low permeability reservoir oil deposit; and obtaining the evaluation result of the small fault block ultra-low permeability reservoir oil deposit according to the weight of each parameter and the evaluation matrix of the parameter.
According to one embodiment of the invention, the reservoir parameter indicators include: reserve scale, reserve abundance, reservoir burial depth, ground crude oil viscosity and recovery ratio; the reservoir parameter indicators include: effective porosity, mainstream throat radius, mobile fluid percentage, sensitivity, start-up pressure gradient; the productivity parameter indexes comprise: producing oil at kilometer well depth daily.
According to an embodiment of the present invention, the determining the evaluation criterion of the parameter includes: determining an evaluation criterion for the parameter from the data for the parameter includes setting the evaluation criterion to five levels from the data for the parameter.
According to an embodiment of the present invention, the determining the weights of the parameters includes: determining the weight of each parameter by adopting an analytic hierarchy process, wherein the method comprises the following steps:
s31: and respectively determining the weights of the oil deposit parameter index, the reservoir layer parameter index and the productivity parameter index by adopting an analytic hierarchy process.
S32: determining the weight of each parameter of the oil deposit parameter index by adopting an analytic hierarchy process; determining the weight of each parameter of the reservoir parameter index by adopting an analytic hierarchy process; and determining the weight of each parameter of the productivity parameter index by adopting an analytic hierarchy process.
According to an embodiment of the invention, the method further comprises: and judging the development value of the oil reservoir of the small fault block ultra-low permeability reservoir according to the evaluation result.
In order to achieve the above object, an embodiment of a second aspect of the present invention provides a system for evaluating the development value of a small-fault block ultra-low permeability reservoir, the system comprising:
the first determination module is used for determining parameters related to the oil reservoir of the small fault block ultra-low permeability reservoir and establishing an evaluation parameter index system, wherein the evaluation parameter index system comprises: oil deposit parameter index, reservoir layer parameter index and productivity parameter index.
And the second determination module is used for determining the evaluation standard of the parameter.
And the third determining module is used for determining the weight of each parameter.
And the first calculation module is used for obtaining an evaluation matrix of the parameters of the block to be evaluated according to the evaluation standard and the actual values of the parameters of the block to be evaluated of the small fault block ultra-low permeability reservoir oil deposit.
And the second calculation module is used for obtaining the evaluation result of the oil reservoir of the small fault block ultra-low permeability reservoir according to the weight of each parameter and the evaluation matrix of the parameter.
According to one embodiment of the invention, the reservoir parameter indicators include: reserve scale, reserve abundance, reservoir burial depth, ground crude oil viscosity and recovery ratio; the reservoir parameter indicators include: effective porosity, mainstream throat radius, mobile fluid percentage, sensitivity, start-up pressure gradient; the productivity parameter indexes comprise: producing oil at kilometer well depth daily.
According to an embodiment of the invention, the third determining module comprises:
and the first sub-determination module is used for respectively determining the weights of the oil deposit parameter index, the reservoir layer parameter index and the productivity parameter index.
The second sub-determining module is used for determining the weight of each parameter of the oil reservoir parameter index according to the oil reservoir parameter index weight; the reservoir parameter index weight determining unit is used for determining each parameter weight of the reservoir parameter index according to the reservoir parameter index weight; and the system is used for determining the weight of each parameter of the productivity parameter index according to the weight of the productivity parameter index.
According to one embodiment of the invention, the system further comprises: and the fourth determination module is used for judging the development value of the small fault block ultra-low permeability reservoir oil deposit according to the evaluation result.
In order to achieve the above object, a fifth aspect embodiment of the present invention provides a non-transitory computer readable storage medium, on which a computer program is stored, the computer program, when executed by a processor, implementing the above-described method for evaluating the development value of a small-fault block ultra-low permeability reservoir.
The invention achieves the technical effects that: a set of multi-parameter reservoir comprehensive evaluation determination technology is established for judging whether an oil reservoir can be used economically and effectively. The technology selects parameters with relatively complete representativeness such as oil deposit macroscopic parameters, reservoir macroscopic characteristic parameters, reservoir microscopic seepage characteristic parameters, petrology parameters, initial productivity parameters and the like to establish an index system for comprehensive evaluation of the ultra-low permeability sandstone reservoir, and the evaluation result can provide direct reference basis for effective utilization of the oil deposit, thereby achieving the technical effect of effectively evaluating the oil deposit development value of the small-block ultra-low permeability reservoir.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method for evaluating the development value of a small-fault block ultra-low permeability reservoir disclosed by an embodiment of the invention;
FIG. 2 is a block diagram of a system for evaluating the development value of a reservoir of a small fault block ultra-low permeability reservoir, as disclosed in an embodiment of the invention.
FIG. 3 is a flow chart of yet another method for evaluating the development value of a small-fault block ultra-low permeability reservoir disclosed by an embodiment of the invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. All other examples, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of the present invention.
The invention discloses a multi-parameter evaluation method for a small-fault-block ultra-low-permeability reservoir oil deposit, which is characterized in that a geological index parameter of an ultra-low-permeability reservoir block is found as a basis, a related existing geological industry standard is combined, each parameter index standard is determined, multi-parameter comprehensive evaluation is carried out on the reservoir by utilizing fuzzy comprehensive judgment, the requirement of oil field development utilization decision is met, a data basis is provided for whether the ultra-low-permeability reservoir oil deposit can be developed and used, and whether the ultra-low-permeability reservoir oil deposit can be effectively developed and used is effectively judged.
The invention aims to establish a set of multi-parameter reservoir comprehensive evaluation judgment technology for judging whether an ultra-low permeability reservoir oil reservoir can be used economically and effectively. The technology selects parameters with relatively complete representativeness such as oil deposit macroscopic parameters, reservoir macroscopic characteristic parameters, reservoir microscopic seepage characteristic parameters, petrology parameters, initial capacity parameters and the like to establish an index system for the comprehensive evaluation of the ultra-low permeability sandstone reservoir, and the evaluation result can provide a direct reference basis for judging whether the ultra-low permeability reservoir can be effectively used.
The invention discloses a small-fault-block ultra-low-permeability reservoir oil deposit multi-parameter comprehensive evaluation method, which is characterized in that the geological index parameters of the ultra-low-permeability reservoir blocks are found as the basis, the relevant existing geological industry standards are combined, the parameter index standards are determined, and the multi-parameter comprehensive evaluation is carried out on the reservoir by utilizing fuzzy comprehensive evaluation.
Firstly, optimizing key parameters by combining the oil reservoir characteristics, reservoir characteristics and productivity characteristics of a complex small fault block low-permeability tight sandstone reservoir in a certain area to form an index system for comprehensive evaluation of the low-permeability tight sandstone reservoir; secondly, determining each parameter index standard by taking geological index parameters of a dense oil reservoir block found in Jiangsu oil field as a basis and combining with related existing geological industry standards. And then determining the weight of each parameter by adopting an analytic hierarchy process, and finally performing comprehensive evaluation on the reservoir by using the most commonly used main factor determinant operator in the fuzzy algorithm.
The working principle of the method is that on the basis of obtaining relevant data of the oil reservoir, the fuzzy evaluation method is utilized to realize comprehensive evaluation of the oil reservoir of the small fault block ultra-low permeability reservoir. The specific process, as shown in fig. 1, is a method for evaluating the oil reservoir development value of a small fault block ultra-low permeability reservoir, comprising the following steps:
s1: determining parameters related to the small fault block ultra-low permeability reservoir oil deposit, and establishing an evaluation parameter index system, wherein the evaluation parameter index system comprises: an oil deposit parameter index, a reservoir layer parameter index and a productivity parameter index; establishing an evaluation parameter index system: selecting macroscopic evaluation parameters such as porosity, permeability and the like from indexes which are the most basic for evaluating the quality of a reservoir; selecting microscopic evaluation parameters such as throat radius, movable fluid percentage, sensitivity and the like from key indexes influencing the seepage capacity; and selecting corresponding evaluation parameters such as reserve scale, burial depth, recoverable reserve and the like from the consideration of the development benefit of the small fault block oil reservoir. And finally, optimizing 12 more key parameters by combining the oil reservoir characteristics, the reservoir characteristics and the productivity characteristics of the complicated small fault block low-permeability tight sandstone reservoir in Jiangsu, and forming an index system for comprehensive evaluation of the low-permeability tight sandstone reservoir.
S2: determining the evaluation standard of the parameter, namely determining an evaluation parameter index standard: the method is characterized in that geological index parameters of a dense oil reservoir block found in an oil field in a certain area are taken as a basis, and 12 parameter index standards are determined by combining related existing geological industry standards. And obtaining a single-factor evaluation matrix of each index of each block to be evaluated by using a ridge type distribution function according to the reservoir characteristic geological value and the corresponding parameter evaluation standard.
S3: determining the weight of each parameter: and determining the weight of each parameter by adopting an analytic hierarchy process. Firstly, establishing a hierarchical model, analyzing the relation of each factor in the system, and defining a total target required by a problem and factors influencing the total target; secondly, establishing a judgment matrix, comparing every two lower-layer factors governed by each factor, comparing the importance degrees of the factors on the upper-layer factors, and expressing the importance degrees by using numbers, thereby forming a every two judgment matrix for each upper-layer factor. And finally, solving a weight vector approximate value of the judgment matrix by using a characteristic vector method. And determining the relative importance degree of the influence of each factor on the evaluation object by using an analytic hierarchy process according to the influence of each index parameter on the evaluation effect, and determining the multi-factor weight coefficient according to the theory.
S4: obtaining an evaluation matrix of the parameters of the block to be evaluated according to the evaluation standard and the actual values of the parameters of the block to be evaluated of the small fault block ultra-low permeability reservoir oil deposit;
s5: and obtaining the evaluation result of the small fault block ultra-low permeability reservoir oil deposit according to the weight of each parameter and the evaluation matrix of the parameter.
Comprehensive evaluation of a reservoir: and (3) selecting the most commonly used 'main factor determinant' operator in the fuzzy algorithm, respectively obtaining three types of comprehensive index evaluation matrixes of an oil reservoir, a reservoir and a dynamic state according to the weight coefficient of each type of parameter index and a fuzzy comprehensive evaluation method, and comprehensively evaluating the compact oil reservoir according to the evaluation method to determine the quality of the reservoir.
The common denominator of the present application and the prior art products is that both the reservoir quality needs to be identified.
The main improvement points of the application are as follows: firstly, establishing a parameter evaluation index system considering oil deposit, reservoir, productivity and other aspects; and secondly, forming an evaluation parameter index standard of the complex small fault block ultra-low permeability compact reservoir.
The small-fault-block ultra-low-permeability reservoir oil deposit multi-parameter evaluation method is widely applied to actual production, the orderly exploitation of the small-fault-block ultra-low-permeability reservoir oil deposit is effectively guided, and the development level and the benefit are improved.
TABLE 1
Table 1 shows a small fault block ultra-low permeability reservoir oil deposit multi-parameter index standard system, and the evaluation criteria for determining the parameters include: and determining the evaluation standard of the parameter according to the data of the parameter, wherein the evaluation standard is set into five grades according to the data of the parameter, and the specific grade number can be defined according to specific engineering requirements, so that different evaluation standard grades are formulated. The following table 2 shows the weight distribution of the oil reservoir parameter indexes of the small fault block ultra-low permeability reservoir.
The oil reservoir parameter indexes comprise: reserve scale, reserve abundance, reservoir burial depth, ground crude oil viscosity and recovery ratio; the reservoir parameter indicators include: effective porosity, mainstream throat radius,
Movable fluid percentage, sensitivity, start-up pressure gradient; the productivity parameter indexes comprise: producing oil at kilometer well depth daily.
TABLE 2
First-step parameter collection: and collecting relevant parameters according to data such as actual drilling, logging, assay analysis, oil testing and production testing, reserve research and the like of each oil reservoir. Taking the h10 effective porosity data as an example, the average effective porosity value is 13%.
S4: and obtaining an evaluation matrix of the parameters of the block to be evaluated according to the evaluation standard and the actual values of the parameters of the block to be evaluated of the small fault block ultra-low permeability reservoir oil deposit.
Establishing a single-factor evaluation matrix: and obtaining a single-factor evaluation matrix of each index of each block to be evaluated by using a ridge distribution function according to each index parameter index and a corresponding parameter evaluation standard. Taking the h10 effective porosity as an example, the matrix criteria were evaluated according to the porosity, as shown in Table 3.
TABLE 3
| Comment (I) | Ultra-low | Is low in | Medium and high grade | Height of | Ultra-high |
| Range of | <8％ | 8％-12％ | 12％-15％ | 15％-20％ | >20％ |
And combining the actual value of the h10 effective porosity, and obtaining a final one-factor evaluation matrix of the effective porosity of the block according to a ridge type distribution function: effective porosity (0.083, 0.292, 0.343, 0.237, 0.046). The analysis process is as follows:
in the single-factor evaluation process, a0, a1, a2, a3, a4 and a5 respectively represent values of the evaluation standard corresponding to the index to be evaluated. And x represents the actual value of the index to be evaluated.
Wherein m11, m12, m13, m21, m22, m23, m31, m32, m33, m41, m42, m43, m51, m52, m53, k1, k2, k3, k4, k5 and the like are process parameters for calculating a distribution function, and finally a single-factor evaluation matrix of the index to be evaluated is obtained.
And respectively obtaining h10 single-factor evaluation matrixes of other parameter indexes by the same method:
reserve size (0.00391, 0.269, 0.46, 0.257, 0.011);
reserve abundance (0.0067, 0.099, 0.427, 0.375, 0.093);
reservoir burial depth (0.071, 0.454, 0.366, 0.102, 0.0067);
surface crude oil viscosity (0.059, 0.22, 0.291, 0.308, 0.122);
recovery factor (0.0056, 0.07, 0.225, 0.369, 0.329)
Permeability (0.16, 0.338, 0.279, 0.177, 0.046);
a main flow throat radius (0.074, 0.34, 0.361, 0.192, 0.033);
mobile fluid saturation (0.037, 0.211, 0.373, 0.313, 0.067);
reservoir sensitivity levels (0.011, 0.085, 0.316, 0.499, 0.089);
initiating a pressure gradient (0.034, 0.209, 0.356, 0.344, 0.057);
kilometer well depth daily oil production (0.058, 0.297, 0.382, 0.223, 0.04).
Second, establishing a weight matrix, including:
s31: and respectively determining the weights of the oil deposit parameter index, the reservoir layer parameter index and the productivity parameter index by adopting an analytic hierarchy process.
S32: determining the weight of each parameter of the oil deposit parameter index by adopting an analytic hierarchy process; determining the weight of each parameter of the reservoir parameter index by adopting an analytic hierarchy process; and determining the weight of each parameter of the productivity parameter index by adopting an analytic hierarchy process.
The present application employs an analytic hierarchy process as a method of determining weights. The analytic hierarchy process is used for decision making and is roughly divided into the following 3 steps: first, a hierarchical model is built. And analyzing the relation of each factor in the system, and defining a total target required by the problem and factors influencing the total target. Second, a decision matrix is established. The factors of the lower layer governed by each factor are compared pairwise, the importance degree of the factors of the lower layer to the factors of the upper layer is compared, and the importance degree is represented by numbers, so that a pairwise judgment matrix is formed for each factor of the upper layer. Thirdly, a weight vector approximate value of the judgment matrix is obtained by applying a characteristic vector method.
The small fault block ultra-low permeability parameter is firstly divided into oil deposit, reservoir and productivity according to parameter difference, and then the weight of the sub-parameter is calculated by applying an analytic hierarchy process after the oil deposit, the reservoir and the productivity are subdivided into 6 types of parameters.
And (4) solving the application characteristic vector method by using the weight matrix. The feature vector method firstly calculates the maximum feature value of the judgment matrix, then normalizes the corresponding feature vector, and finally obtains a vector which is the approximate vector of the weight vector.
The eigenvalue obtained for any judgment matrix is not necessarily reliable, so that a matrix consistency judgment index CI needs to be introduced. According to the theory proposed by Perron, if there is a positive, real, single feature root λ 1 for any decision matrix, the modulus of other feature roots is smaller than λ 1, so that the similarity weight vector obtained by the above method is reliable, otherwise it is unreliable. Defining CI as (λ 1-n)/(n-1) as an index of consistency for R, CI can be considered as a measure of the degree of deviation of R from consistency. When CI is 0, R is uniform, and when CI value is smaller, it is indicated that R deviates from uniformity to a smaller extent. In order to measure whether the judgment matrix has satisfactory consistency at different stages, an average random consistency index RI is introduced, and the judgment matrix RI of 1-13 orders is a series of empirical constants. The ratio of CI and RI is called the random consistency ratio CR when: when CR <0.1, the judgment matrix is considered to have satisfactory consistency. Otherwise, the decision matrix is adjusted to have satisfactory consistency.
The matrix a in the example is a 6 × 6 matrix formed by weighted values evaluated by two-by-two evaluation importance of six parameters.
Wherein Eigenvals () is a matrix eigenvalue function in mathcad.
Eigenvecs () is a matrix eigenvector function in mathcad.
And ═ and ^ are general definitional symbols and integral symbols.
Sigma and the sign of summation, and min and max are the signs of solving the maximum and minimum values.
And (4) solving the application characteristic vector method by using the weight matrix. The feature vector method firstly calculates the maximum feature value of the judgment matrix, then normalizes the corresponding feature vector, and finally obtains a vector which is the approximate vector of the weight vector.
The eigenvalue obtained for any judgment matrix is not necessarily reliable, so that a matrix consistency judgment index CI needs to be introduced. According to the theory proposed by Perron, if there is a positive, real, single feature root λ 1 for any decision matrix, the modulus of other feature roots is smaller than λ 1, so that the similarity weight vector obtained by the above method is reliable, otherwise it is unreliable. Defining CI as (λ 1-n)/(n-1) as an index of consistency for R, CI can be considered as a measure of the degree of deviation of R from consistency. When CI is 0, R is uniform, and when CI value is smaller, it is indicated that R deviates from uniformity to a smaller extent. In order to measure whether the judgment matrix has satisfactory consistency at different stages, an average random consistency index RI is introduced, and the judgment matrix RI of 1-13 orders is a series of empirical constants. The ratio of CI and RI is called the random consistency ratio CR when: when CR <0.1, the judgment matrix is considered to have satisfactory consistency. Otherwise, the decision matrix is adjusted to have satisfactory consistency.
The matrix a in the example is a 6 × 6 matrix formed by weighted values evaluated by two-by-two evaluation importance of six parameters.
Taking the process of establishing a weight matrix by six types of parameters such as effective porosity in reservoir parameters as an example, a 6 × 6 matrix is formed by mutually evaluating the weight relationship one by one according to the influence of the six types of parameters such as pore space, throat and starting pressure gradient on an ultra-low permeability reservoir, and then a weight vector approximate value of a judgment matrix is obtained by using a feature vector method to obtain relatively accurate weight.
Namely, the weighting relation among the reservoir parameters of the effective porosity, the permeability, the sensitivity, the radius of a main flow throat, the percentage of movable fluid and the starting pressure gradient is as follows: (0.08,0.239,0.12,0.163,0.199,0.199).
S5: and obtaining the evaluation result of the small fault block ultra-low permeability reservoir oil deposit according to the weight of each parameter and the evaluation matrix of the parameter.
And (3) comprehensively evaluating the reservoir, wherein the selected fuzzy algorithm is a 'main factor determinant' operator, a comprehensive evaluation matrix is obtained by applying the fuzzy algorithm according to the determined weight coefficients of various parameter indexes and the multi-factor evaluation matrix, and by taking h10 reservoir parameter index matrices as examples, six types of single factors related to the reservoir indexes are formed into a 6 x 6 evaluation matrix, and the weight matrix is calculated by applying the fuzzy operator to obtain a final result.
The comprehensive evaluation matrix is obtained by synthesizing each single factor into an evaluation result Y of M × Q by a fuzzy transformation method when a dimensionless evaluation matrix M and a weight vector Q are obtained. Wherein, the parameters of X0, T01, R1 and the like are intermediate variable parameters in the process of the 'main factor determining' fuzzy algorithm, and finally, the comprehensive judgment index is obtained through normalization.
Namely, the h10 reservoir parameter index evaluation results are (0.173, 0.258, 0.258, 0.215, 0.096). Respectively obtaining oil deposit and dynamic comprehensive index evaluation matrixes, wherein the oil deposit parameter indexes are (0.059, 0.165, 0.264, 0.264 and 0.248); dynamic parameter index (0.153, 0.392, 0.324, 0.121, 0.011).
The final evaluation matrix is obtained by the same method: (0.129,0.26,0.241,0.186,0.184).
As shown in fig. 3, according to an embodiment of the invention, the method further comprises: and judging the development value of the oil reservoir of the small fault block ultra-low permeability reservoir according to the evaluation result.
According to the evaluation method, the potential blocks of the ultra-low permeability compact oil reservoir found in the oil field of a certain area are comprehensively evaluated to obtain a comprehensive evaluation table. From the evaluation results, the ultra-low permeability compact reservoir mainly comprises a type III reservoir and a type IV reservoir, and the development benefit is relatively poor.
The invention provides a method for evaluating the oil reservoir development value of a small-fault-block ultra-low permeability reservoir, which is used for establishing a multi-parameter reservoir comprehensive evaluation judgment technology aiming at the situation that whether an oil reservoir can be used economically and effectively. The technology selects parameters with relatively complete representativeness such as an oil deposit macroscopic parameter, a reservoir macroscopic characteristic parameter, a reservoir microscopic seepage characteristic parameter, a petrology parameter, an initial productivity parameter and the like to establish an index system for the comprehensive evaluation of the ultra-low permeability sandstone reservoir, and the evaluation result can provide a direct reference basis for whether the oil deposit can effectively move or not; the technical effect of effectively judging the oil reservoir development value of the small-fault-block ultra-low permeability reservoir is achieved.
In a second aspect, embodiments of the present invention provide a system 200 for evaluating the development value of a small-fault block ultra-low permeability reservoir, as shown in fig. 2, comprising:
a first determining module 201, configured to determine parameters related to the small-fault-block ultra-low permeability reservoir, and establish an evaluation parameter index system, where the evaluation parameter index system includes: oil deposit parameter index, reservoir layer parameter index and productivity parameter index.
A second determining module 202, configured to determine an evaluation criterion of the parameter.
A third determining module 203, configured to determine the weights of the parameters.
The first calculation module 204 is configured to obtain an evaluation matrix of the parameter of the block to be evaluated according to the evaluation criterion and the actual value of the parameter of the block to be evaluated of the small-fault ultra-low permeability reservoir.
And the second calculation module 205 is configured to obtain an evaluation result of the small fault block ultra-low permeability reservoir oil deposit according to the weight of each parameter and the evaluation matrix of the parameter.
According to one embodiment of the invention, the reservoir parameter indicators include: reserve scale, reserve abundance, reservoir burial depth, ground crude oil viscosity and recovery ratio; the reservoir parameter indicators include: effective porosity, mainstream throat radius, mobile fluid percentage, sensitivity, start-up pressure gradient; the productivity parameter indexes comprise: producing oil at kilometer well depth daily.
According to an embodiment of the present invention, the third determining module 203 includes:
and the first sub-determination module is used for respectively determining the weights of the oil deposit parameter index, the reservoir layer parameter index and the productivity parameter index.
The second sub-determining module is used for determining the weight of each parameter of the oil reservoir parameter index according to the oil reservoir parameter index weight; the reservoir parameter index weight determining unit is used for determining each parameter weight of the reservoir parameter index according to the reservoir parameter index weight; and the system is used for determining the weight of each parameter of the productivity parameter index according to the weight of the productivity parameter index.
According to one embodiment of the invention, the system further comprises: and the fourth determination module is used for judging the development value of the small fault block ultra-low permeability reservoir oil deposit according to the evaluation result.
In order to achieve the above object, a fifth aspect embodiment of the present invention provides a non-transitory computer readable storage medium, on which a computer program is stored, the computer program, when executed by a processor, implementing the above-described method for evaluating the development value of a small-fault block ultra-low permeability reservoir.
The invention achieves the technical effects that: a set of multi-parameter reservoir comprehensive evaluation determination technology is established for judging whether an oil reservoir can be used economically and effectively. The technology selects parameters with relatively complete representativeness such as oil deposit macroscopic parameters, reservoir macroscopic characteristic parameters, reservoir microscopic seepage characteristic parameters, petrology parameters, initial capacity parameters and the like to establish an index system for comprehensive evaluation of the ultra-low permeability sandstone reservoir, and the evaluation result can provide direct reference basis for effective movement of the oil deposit, thereby achieving the technical effect of effectively evaluating the development value of the oil deposit of the small-block ultra-low permeability reservoir.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
The above-described embodiments of the electronic device and the like are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may also be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the embodiments of the present invention, and are not limited thereto; although embodiments of the present invention have been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for evaluating the reservoir development value of a small-fault block ultra-low permeability reservoir, the method comprising:
determining parameters related to the small fault block ultra-low permeability reservoir oil deposit, and establishing an evaluation parameter index system, wherein the evaluation parameter index system comprises: an oil deposit parameter index, a reservoir layer parameter index and a productivity parameter index;
determining an evaluation criterion of the parameter;
determining the weight of each parameter;
determining an evaluation matrix of the parameters of the block to be evaluated according to the evaluation standard and the actual values of the parameters of the block to be evaluated of the small fault block ultra-low permeability reservoir oil deposit;
and obtaining the evaluation result of the small fault block ultra-low permeability reservoir oil deposit according to the weight of each parameter and the evaluation matrix of the parameter.
2. The method of claim 1, wherein the reservoir parameter indicators comprise: reserve scale, reserve abundance, reservoir burial depth, ground crude oil viscosity and recovery ratio; the reservoir parameter indicators include: effective porosity, mainstream throat radius, mobile fluid percentage, sensitivity, start-up pressure gradient; the productivity parameter indexes comprise: producing oil at kilometer well depth daily.
3. The method of claim 1 or 2, wherein said determining an evaluation criterion for said parameter comprises: determining an evaluation criterion for the parameter from the data for the parameter includes setting the evaluation criterion to five levels from the data for the parameter.
4. The method of claim 1 or 2, wherein said determining said respective parameter weights comprises:
s31: determining the weights of the oil deposit parameter index, the reservoir layer parameter index and the productivity parameter index by adopting an analytic hierarchy process;
s32: determining the weight of each parameter of the oil deposit parameter index by adopting an analytic hierarchy process; determining the weight of each parameter of the reservoir parameter index by adopting an analytic hierarchy process; and determining the weight of each parameter of the productivity parameter index by adopting an analytic hierarchy process.
5. The method of claim 1, further comprising:
and judging the development value of the oil reservoir of the small fault block ultra-low permeability reservoir according to the evaluation result.
6. A system for evaluating the development value of a small-fault block ultra-low permeability reservoir, the system comprising:
the first determination module is used for determining parameters related to the oil reservoir of the small fault block ultra-low permeability reservoir and establishing an evaluation parameter index system, wherein the evaluation parameter index system comprises: an oil deposit parameter index, a reservoir layer parameter index and a productivity parameter index;
the second determination module is used for determining the evaluation standard of the parameter;
a third determining module, configured to determine weights of the parameters;
the first calculation module is used for obtaining an evaluation matrix of the parameters of the block to be evaluated according to the evaluation standard and the actual values of the parameters of the block to be evaluated of the small fault block ultra-low permeability reservoir oil deposit;
and the second calculation module is used for obtaining the evaluation result of the small fault block ultra-low permeability reservoir oil deposit according to the weight of each parameter and the evaluation matrix of the parameter.
7. The system of claim 6, wherein the reservoir parameter indicators comprise: reserve scale, reserve abundance, reservoir burial depth, ground crude oil viscosity and recovery ratio; the reservoir parameter indicators include: effective porosity, mainstream throat radius, mobile fluid percentage, sensitivity, start-up pressure gradient; the productivity parameter indexes comprise: producing oil at kilometer well depth daily.
8. The system of claim 6 or 7, wherein the third determining module comprises:
the first sub-determination module is used for respectively determining the weights of the oil deposit parameter index, the reservoir layer parameter index and the productivity parameter index;
the second sub-determining module is used for determining the weight of each parameter of the oil reservoir parameter index according to the oil reservoir parameter index weight;
the reservoir parameter index weight determining unit is used for determining each parameter weight of the reservoir parameter index according to the reservoir parameter index weight;
and the system is used for determining the weight of each parameter of the productivity parameter index according to the weight of the productivity parameter index.
9. The system of claim 6, further comprising:
and the fourth determination module is used for judging the development value of the small fault block ultra-low permeability reservoir oil deposit according to the evaluation result.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements a method for evaluating the development value of a small-fault block ultra-low permeability reservoir as claimed in any one of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010694422.9A CN111832951A (en) | 2020-07-17 | 2020-07-17 | Method and system for evaluating oil reservoir development value of small fault block ultra-low permeability reservoir |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010694422.9A CN111832951A (en) | 2020-07-17 | 2020-07-17 | Method and system for evaluating oil reservoir development value of small fault block ultra-low permeability reservoir |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111832951A true CN111832951A (en) | 2020-10-27 |
Family
ID=72923554
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010694422.9A Pending CN111832951A (en) | 2020-07-17 | 2020-07-17 | Method and system for evaluating oil reservoir development value of small fault block ultra-low permeability reservoir |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111832951A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112529443A (en) * | 2020-12-18 | 2021-03-19 | 河南理工大学 | Coal bed gas development target area optimization method based on fuzzy pattern recognition |
| CN113642656A (en) * | 2021-08-18 | 2021-11-12 | 中国石油大学(北京) | Method for determining mining mode of low-permeability sandstone reservoir and related device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101937108A (en) * | 2009-07-03 | 2011-01-05 | 中国石油天然气股份有限公司 | Determining method for surveying reserves of hypotonic clastic rock oil-gas reservoir |
| CN110644980A (en) * | 2019-09-11 | 2020-01-03 | 中国石油天然气股份有限公司 | Comprehensive classification evaluation method for ultra-low permeability oil reservoir |
-
2020
- 2020-07-17 CN CN202010694422.9A patent/CN111832951A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101937108A (en) * | 2009-07-03 | 2011-01-05 | 中国石油天然气股份有限公司 | Determining method for surveying reserves of hypotonic clastic rock oil-gas reservoir |
| CN110644980A (en) * | 2019-09-11 | 2020-01-03 | 中国石油天然气股份有限公司 | Comprehensive classification evaluation method for ultra-low permeability oil reservoir |
Non-Patent Citations (2)
| Title |
|---|
| 孙玉平等: "低渗透储层渗流能力模糊综合评价新方法", 辽宁工程技术大学学报(自然科学版), pages 2 - 3 * |
| 魏漪等: "模糊数学方法在长庆油田低渗透储层综合评价中的应用", 石油天然气学报, pages 61 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112529443A (en) * | 2020-12-18 | 2021-03-19 | 河南理工大学 | Coal bed gas development target area optimization method based on fuzzy pattern recognition |
| CN113642656A (en) * | 2021-08-18 | 2021-11-12 | 中国石油大学(北京) | Method for determining mining mode of low-permeability sandstone reservoir and related device |
| CN113642656B (en) * | 2021-08-18 | 2023-09-05 | 中国石油大学(北京) | Method and related device for determining exploitation mode of hypotonic sandstone reservoir |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109611087B (en) | Volcanic oil reservoir parameter intelligent prediction method and system | |
| CN106703776B (en) | Fracturing parameter optimization method | |
| CN109002686B (en) | Multi-grade chemical process soft measurement modeling method capable of automatically generating samples | |
| CN104134101B (en) | Low permeability reservoir Gas Productivity Forecasting Methodology | |
| CN110428175B (en) | Hot rolled strip steel plate convexity prediction method based on deep learning | |
| CN109214026A (en) | A kind of shale gas horizontal well initial productivity prediction technique | |
| CN111046341A (en) | Unconventional natural gas fracturing effect evaluation and capacity prediction method based on principal component analysis | |
| CN104933156A (en) | Collaborative filtering method based on shared neighbor clustering | |
| CN112735097A (en) | Regional landslide early warning method and system | |
| CN111832951A (en) | Method and system for evaluating oil reservoir development value of small fault block ultra-low permeability reservoir | |
| CN109184677A (en) | Reservoir evaluation methods for heterogeneous alternating layers sand body | |
| CN105678590A (en) | topN recommendation method for social network based on cloud model | |
| CN106503798A (en) | Based on rough set and the method for diagnosing faults of the pump of BP neural network | |
| CN111126865B (en) | Technology maturity judging method and system based on technology big data | |
| CN112926893A (en) | Horizontal well profile control effect evaluation method based on fuzzy comprehensive evaluation and hierarchical analysis | |
| CN103942604A (en) | Prediction method and system based on forest discrimination model | |
| CN117235510A (en) | Joint roughness prediction method and training method of joint roughness prediction model | |
| CN113641733B (en) | Real-time intelligent estimation method for river cross section flow | |
| CN116562428A (en) | Fracturing construction parameter optimization method based on machine learning | |
| CN110866694A (en) | Power grid construction project financial evaluation system and method | |
| CN110956388B (en) | Method for generating yield increasing scheme of offshore oil and gas reservoir | |
| CN114091908A (en) | Power distribution network comprehensive evaluation method, device and equipment considering multi-mode energy storage station | |
| CN106096814A (en) | Product service system Scheme Optimum Seeking Methods based on rough set theory | |
| CN115906591B (en) | XGBoost network-based oil well working fluid level calculation method | |
| CN116257765A (en) | Profile control and profile control parameter analogy recommendation method and device based on similarity calculation model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |