(Planning and Design Institute of Northwest Petroleum Bureau of Urumqi 8300 1 1)
Trap evaluation aims to reduce the risk of oil and gas exploration and improve the success rate of drilling. There are many methods in trap evaluation, which can be summarized as: comprehensive qualitative queuing method, scoring method, probability statistics method, multi-information superposition evaluation method, grey system theory and fuzzy mathematics evaluation method. The application of "fuzzy mathematics evaluation method" in the comprehensive evaluation of traps in Tarim basin has achieved good results.
Tarim basin; Fuzzy mathematics weight; Fuzzy evaluation value; trap evaluation
1 principle
1. 1 fuzzy mathematical concept
American control expert L.A.Zaden first put forward the concept of "fuzzy mathematics" in 1965, which is a theory and method to study and deal with the regularity of fuzzy systems, that is, to extend the characteristic function of universal set theory with only 0 or 1 two values to the membership function with values in the range of [0, 1]. Evaluation methods such as "Good", "Good", "Medium", "Poor" and "Poor" are commonly used in trap evaluation, which are more suitable for comprehensive evaluation of hydrocarbon-bearing properties of traps with fuzzy mathematics.
1.2 Basic concepts and methods of fuzzy comprehensive evaluation
The so-called fuzzy comprehensive evaluation refers to the comprehensive processing of the evaluation results of multiple factors, and finally get the membership degree of a decision.
There are many geological factors that determine whether a trap (local structure) is a reservoir, such as reservoir, caprock and oil source. Consider μ 1, μ2, …, μ. These n evaluation trap factors thus constitute a factor set u:
U={μ 1，μ2…μm}
In the evaluation, we can divide the factors participating in the evaluation into m grades (such as I, II, III or good, medium and poor). Commonly used in evaluation), thus forming an evaluation set v:
V={V 1，V2…Vm}
Factors in factor set U have different functions in trap (local structure) accumulation, so in trap (local structure) evaluation, we should give different weight coefficients to each evaluation factor according to our understanding of trap (local structure) accumulation law, thus forming a weight distribution set A:
A={A 1，A2…An}
The value here must be equal to 1. In the process of assignment, for the sake of convenience, only the relative relationship between evaluation factors is considered, and the Ai value is not considered, so as to meet the value redistribution in the operation process.
Essays on exploration and development of oil and gas fields in northern Tarim basin
In order to comprehensively judge the hydrocarbon-bearing property of traps (local structures), that is, which level they belong to, it is necessary to establish a fuzzy transformation relationship r between factor set U and comment set V.
Essays on exploration and development of oil and gas fields in northern Tarim basin
Where r is the score of a factor of an object (here refers to the trap or local structure) about each category, that is, the membership degree. Therefore, R is also called single factor evaluation matrix.
The combination of weight a and fuzzy transformation matrix r constitutes trap comprehensive evaluation matrix b;
B=AR
Finally, the comprehensive evaluation value d of each trap (local structure) is obtained by the following formula:
D = BC
Where c is the transposed matrix of the grade matrix, and the evaluation grade is divided into good and good grades. The value of c is (-2,-1, 0, 1, 2), and Rnm can be determined according to table 1. When the evaluation grade is divided into three grades: good, medium and poor, the value of c is (-1, 0, 1), and r can be determined according to Table 2.
Table 1 five-level comment table 1 five-level comment table
Table 2 Evaluation of Three Grades Table 2 Evaluation of Three Grades in Table 2
After calculating the comprehensive evaluation value d of each trap, the evaluated traps (local structures) are queued according to the value d, and the optimized traps (local structures) are obtained for exploration and deployment. 1.3 on fuzzy operation
There are many algorithms defined in fuzzy mathematics with different meanings. According to the characteristics of trap (local structure) evaluation, the following four types are adopted this time:
(1) Take the minimum solution:
The methods of taking the minimum and the maximum are abbreviated as (∨, ∧) respectively, and the algorithm of synthesizing the element bj in matrix B is as follows:
Essays on exploration and development of oil and gas fields in northern Tarim basin
② Small sum method
Taking the small sum method as (∧, ⊕) respectively, the algorithm for synthesizing the element bj in matrix B is as follows:
Essays on exploration and development of oil and gas fields in northern Tarim basin
③ product maximization method
The multiplication methods are abbreviated as (,v) respectively, and the algorithm for synthesizing the element bj in matrix B is as follows:
Essays on exploration and development of oil and gas fields in northern Tarim basin
④ product summation method
The product summation method is the key algorithm for evaluation, which is called (,⊕) respectively. The algorithm for synthesizing the element bj in matrix B is as follows:
Essays on exploration and development of oil and gas fields in northern Tarim basin
2 trap evaluation parameters and scoring standards
There are many geological factors that affect the hydrocarbon-bearing property of traps. Combined with the actual exploration situation in Tarim basin, five geological factors, such as trap implementation degree, reservoir conditions, caprock conditions, oil source conditions, and the configuration relationship between oil and gas generation period and structure formation period (circle-row relationship), are mainly considered. According to the law of oil and gas accumulation in this area, the weight coefficient of each geological factor is determined, as shown in Table 3.
Table 3 Geological factors and weight coefficient of trap evaluation Table 3 Geological factors and potential decisive coefficient of trap evaluation
When evaluating the hydrocarbon-bearing grade of traps, it is divided into five grades: good, good, medium, poor and poor. The evaluation and assignment criteria of geological factors are determined according to the data provided by each project team.
2. 1 trap realization degree
It is mainly realized by seismic data, such as whether there is three-dimensional control, the number of two-dimensional seismic lines of traps, and the evaluation of trap closure amplitude (see Table 4).
2.2 Reservoir conditions
Table 4 Evaluation of the Implementation Degree of Trap Table 4 Evaluation of the Practical Degree of Trap
The heterogeneity of carbonate reservoir is very obvious. Yakela-Luntai area is mainly Cambrian and Ordovician dolomite, which has experienced long-term paleokarst and the reservoir physical properties are generally medium-good. The Ordovician limestone is dominant in Tahe oil region, and the reservoir physical properties are poor. Due to the development of pores, fractures and caves, the overall physical properties of the reservoir have been obviously improved. See Table 5 for the division table.
Clastic rocks are mainly evaluated by porosity and permeability, and the criteria for dividing different zones are slightly different. The results are shown in Table 6.
2.3 caprock conditions
Table 5 Opinions on Carbonate Reservoir Table 5 Opinions on Carbonate Reservoir
Table 6 Opinions on Clastic Reservoir Division Table 6 Opinions on Clastic Reservoir Division
The analysis parameters of caprock in Aaron and Bamai Industrial Zone are incomplete. The evaluation of trap caprock is mainly based on the comprehensive research results in this area. For traps (fault nose, fault block, etc. ) It is considered that the lithology on both sides of the fault should be considered only by relying on the fault as lateral sealing. If the reservoirs on both sides of the fault butt against the caprock, the evaluation is good, the butt against the sandstone-mudstone interlayer is good-medium, and the butt against the reservoir is poor-poor. See Table 7 for the standard of caprock division in Aisan work area.
2.4 Oil source conditions
Table 7 Evaluation of Cover Conditions in Aisan Industrial Zone Table 7 Evaluation of Cover Conditions in Aisheke-Santamu Industrial Zone
Mainly consider the distance between trap and source sag and oil and gas migration channel.
For continental oil and gas, the distance between trap and source depression and the relationship between fault development and reservoir are mainly considered. If the fault breaks to the unconformity surface and reaches the reservoir, the fault distance is taken as the evaluation standard (Table 8).
Table 8 Review of continental hydrocarbon source conditions Table 8 Review of continental hydrocarbon origin
For marine oil and gas, besides whether faults connect source rocks and reservoir rocks, we should also consider the abundance of oil and gas resources and whether structural zones are in the direction of oil and gas migration. The evaluation criteria are shown in Table 9.
Table 9 Evaluation of Marine Oil and Gas Source Conditions Table 9 Evaluation of Marine Oil and Gas Genesis
2.5 Circle Row Relationship
Circle-row relationship refers to the configuration relationship between trap formation period and oil generation peak period. The structural formation period is better than the peak oil generation period, and both are rated as good-medium, while the structural formation period after the peak oil generation period is poor-poor.
3 trap evaluation results and queuing
According to the above-mentioned evaluation criteria, we comprehensively evaluate the oil-gas bearing capacity of the designated trap by using fuzzy mathematics for the undiscovered 184 geological evaluation factors in trap evaluation. According to the fuzzy evaluation value d, the hydrocarbon-bearing capacity of traps can be divided into Grade I (D≥ 1), Grade II, Grade III (D≤0.5 < D < 1) and Grade III (D≤0). For the selected type I trap, some relevant factors that can reflect the economic benefits are properly considered, such as exploration well cost and important parameter resources that affect the benefits. See table 10 for specific parameters.
Table 10 comprehensive evaluation parameters of local structure and standard table 10 comprehensive evaluation parameters and standards of local structure
According to the actual exploration situation in this area, each trap layer and each evaluation factor are given different weight coefficients (table 1 1 and 12).
Table 1 1 trap layer weight coefficient table 1 1 trap layer provisional cruelty coefficient
Table 12 distribution table of potential key coefficients for local structure judgment
The structural evaluation value is determined by the following formula
Essays on exploration and development of oil and gas fields in northern Tarim basin
Structure D is the fuzzy value of structure evaluation, and E is the weight coefficient of trap layer, which is the maximum value of trap fuzzy evaluation in trap layer system.
Fuzzy mathematics is used to comprehensively evaluate the oil-gas bearing capacity of the designated local structure, and the comprehensive evaluation value of the local structure is obtained. The oil-gas bearing capacity of the local structure is divided into ⅰ(D comprehensive ≥0.28) and ⅱ(0. 17.
refer to
[1] Zhang Yue et al. Fuzzy mathematics method and its application. Beijing: Coal Industry Press, 1992.
Zhao xuche. Introduction to petroleum mathematical geology. Beijing: Petroleum Industry Press, 1992.
Application of Fuzzy Mathematics in trap evaluation of Tarim Basin
Yuan Luying Northeast Tiger Beichen
Planning and Design Institute of Northwest Petroleum Geology Bureau? Urumqi 8300 1 1)
Abstract: The purpose of trap evaluation is to reduce the risk of oil and gas exploration and improve the success rate of drilling. There are six methods to evaluate traps: multiple judgment queuing method, comparative evaluation method, probability statistics method, multiple information evaluation method, graph theory, fuzzy mathematics evaluation method and so on. The application of fuzzy mathematics evaluation method to the evaluation of traps in Tarim basin has achieved satisfactory results.
Keywords: trap evaluation, a fuzzy mathematical method in Tarim Basin