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Method of oil well classification and oil reservoir zoning based on SPSS(statistic package for social science)

A technology of oil reservoirs and oil wells, applied in the field of oil well classification and reservoir zoning based on SPSS, can solve the problems of lack of verification, time-consuming and laborious zoning rationality, etc., to improve work efficiency, save work time, and be operable strong effect

Inactive Publication Date: 2017-06-13
朱亚婷 +1
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AI Technical Summary

Problems solved by technology

[0017] A SPSS-based oil well classification and reservoir zoning method proposed by the present invention can solve the technical problems that traditional correlation research methods are time-consuming and laborious and the rationality of zoning cannot be verified

Method used

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  • Method of oil well classification and oil reservoir zoning based on SPSS(statistic package for social science)
  • Method of oil well classification and oil reservoir zoning based on SPSS(statistic package for social science)
  • Method of oil well classification and oil reservoir zoning based on SPSS(statistic package for social science)

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0056] An oil reservoir in Shinan: oil well classification

[0057]The data of normal production wells put into large-scale production in this reservoir are as follows:

[0058] Table 2-1 Basic parameters of normal production wells in reservoirs

[0059]

[0060] The results of SPSS principal factor analysis are shown in Table 2-2~2-4:

[0061] Table 2-2 Total Variance Table Explained

[0062]

[0063]

[0064] Table 2-3 Rotation component matrix (rotation method: Orthogonal rotation method with Kaiser normalization)

[0065]

[0066] Table 2-4 Principal component analysis result table

[0067] factor name Eigenvalues variance cumulative variance F1 thickness factor 3.687 46.033 46.033 F2 permeability factor 1.861 33.233 79.265

[0068] The analysis results show that there are two main components of factors affecting oil wells in this reservoir: thickness factor f1 and permeability factor f2. Obtained through the compone...

Embodiment 2

[0082] A Oil Reservoir in Shinan: Plane Division

[0083] After principal factor analysis, the parameters with the highest correlation coefficient in Table 2-3 of the rotating component matrix are effective thickness, permeability and porosity, and the established data table is shown in Table 2-8:

[0084] Table 2-8 Parameter table of normal production wells used to establish partition coefficient

[0085]

[0086] Using SPSS software data mining to calculate the weight with the goal of accumulating oil volume, the results are as follows Figure 4 .

[0087] Therefore, the partition coefficient f model is: f=0.6h+0.34φ+0.05k

[0088] Calculate the partition coefficient value of each single well in the reservoir through the partition coefficient, according to the plane equivalent map of the numerical value (see Figure 5 ), combined with the understanding of the reservoir, effective partitioning can be carried out.

[0089] It can be seen from the zoning comparison with ...

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Abstract

Provided is a method of oil well classification and oil reservoir zoning based on SPSS(statistic package for social science). The method of oil well classification and reservoir zoning based on SPSS can solve the technical problems that the traditional correlation research methods are time-consuming and laborious, and the rationality of the subarea is not verified. The method of oil well classification and reservoir zoning comprises the following steps: step one, principal component analysis is carried out; the principal component analysis is to use the Bartlett sphericity test or KMO method to determine whether the factors are suitable for factor analysis; step two, the principal component factor is extracted and determined by using SPSS software; step three: the oil well is classified according to the determined principal component factor; step four: the principal component factor weights are excavated by using SPSS(statistic package for social science) software, and a subarea coefficient model is established to partition the reservoir according to the determined partition coefficients. The method is implemented by SPSS software analysis, a zone coefficient model is established to partition the reservoir according to the determined partition coefficients; the workload of the original 3 or 4 weeks is shortened to 2 or 3 days, which not only improves the work efficiency and operability, but also facilitates the popularization and application of the method, besides, the method of oil well classification is more scientific.

Description

technical field [0001] The invention relates to the petroleum field, in particular to a SPSS-based method for classifying oil wells and partitioning oil reservoirs. Background technique [0002] Due to the influence of the heterogeneity of the plane section, the production of oil wells in water injection reservoirs often has great differences. Generally, reservoir managers roughly divide them according to the reservoir geography and closed boundaries, production, water cut and pressure. , but there will be an image of different types of wells intersecting, which will bring inconvenience to production and management; as the reservoir gradually enters the high water cut stage, the remaining oil on the plane will be scattered, and the fine control of the plane and section will be more and more demanding, and the plane will be accurately partitioned more and more important. Therefore, relevant trial calculation analysis of different influencing factors has appeared, which is ti...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06K9/62G06Q50/02
CPCG06Q50/02G06F30/20G06F18/2135G06F18/24
Inventor 朱亚婷周玉辉王晓光蒋志斌苏海滨程宏杰钱川川陈玉琨张强张记刚邹玮刘振平祁丽莎冯利娟冷润熙
Owner 朱亚婷
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