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A perforation scheme optimization method based on gray relational clustering

A scheme optimization and gray correlation technology, applied in design optimization/simulation, special data processing applications, complex mathematical operations, etc., can solve problems such as reducing the subjective influence of scheme decision makers and the uncertainty of decision-making schemes

Active Publication Date: 2017-11-24
XI'AN PETROLEUM UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In order to solve technical problems such as the uncertainty of existing decision-making schemes, the purpose of the present invention is to provide a perforating scheme optimization method based on gray relational clustering, which uses fuzzy clustering to analyze the perforating gun type, perforating bullet type, etc. The influence of factors such as hole depth, hole density, hole diameter, and phase on the productivity ratio and casing strength reduction coefficient can be obtained to obtain the optimal perforation parameter plan. This method reduces the subjective influence of plan decision makers and reasonably quantifies the optimal The best perforation scheme saves a lot of manpower, material resources and time costs, and is a new method to obtain perforation construction parameters

Method used

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  • A perforation scheme optimization method based on gray relational clustering
  • A perforation scheme optimization method based on gray relational clustering
  • A perforation scheme optimization method based on gray relational clustering

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0108] Well Bai 152 in Changqing Oilfield, the depth of the middle part of the oil layer is 1884.5m, the total thickness of the pay zone is 9.5m, the thickness of the perforated interval is 3.0m, the formation porosity is 13.41%, the drainage radius of the pay zone is 200m, the radius of the wellbore is 0.111m, the formation The pressure is 13.073MPa, the saturation pressure of crude oil is 9.86MPa, the drilling pollution depth is 69.5mm, the drilling pollution degree is 0.6, the anti-extrusion strength of the casing is 47.8MPa, the heterogeneity of the pay zone is 0.7 vertical permeability / horizontal permeability, water cut The saturation is 30.21%, the Poisson's ratio of rock is 0.5, the well deviation is 5°, and the viscosity of crude oil in the formation is 1.03MPa.S. The perforation optimization scheme shown in Table 1 is obtained.

[0109] Table 1 Perforation scheme of Well Bai 152

[0110]

[0111]

[0112] From the above table 1, the following initial feature mat...

Embodiment 2

[0125]Well Bai 124 in Changqing Oilfield, the depth of the middle part of the oil layer is 1891.5m, the total thickness of the pay zone is 4.1m, the thickness of the perforated interval is 3.0m, the formation porosity is 6.0%, the drainage radius of the pay zone is 200m, the radius of the wellbore is 0.111m, the formation The pressure is 13.073MPa, the saturation pressure of crude oil is 9.86MPa, the drilling pollution depth is 66.7mm, the drilling pollution degree is 0.6, the anti-extrusion strength of the casing is 47.8MPa, the heterogeneity of the production layer is 0.7 vertical permeability / horizontal permeability, water cut The saturation is 21.83%, the Poisson's ratio of rock is 0.21, the well deviation is 5°, and the viscosity of crude oil in the formation is 1.03MPa.S. The perforation optimization scheme shown in Table 2 is obtained.

[0126] Table 2 Perforation scheme of Well Bai 124

[0127]

[0128] From the above table 2, the following initial feature matrix D=...

Embodiment 3

[0141] In Well Bai 138 in Changqing Oilfield, the middle depth of the oil layer is 1930.3m, the total thickness of the pay zone is 2.7m, the thickness of the perforated interval is 2.0m, the porosity is 14.67%, the drainage radius of the pay zone is 200m, the radius of the wellbore is 0.111m, and the formation pressure 13.073MPa, crude oil saturation pressure 9.86MPa, drilling pollution depth 70.7mm, drilling pollution degree 0.6, casing anti-extrusion strength of 47.8MPa, production layer heterogeneity 0.7, water saturation 20.93%, rock Poisson's ratio 0.21, well deviation 5°, formation crude oil viscosity 1.03MPa.S, the perforation optimization scheme shown in Table 3 is obtained.

[0142] Table 3 Perforation scheme of Well Bai 138

[0143]

[0144] From the above table 3, the following initial feature matrix D=(x ij ) 6×24 :

[0145]

[0146] Transform the initial feature matrix D into feature object matrix R=(r ij ) 6×24

[0147]

[0148] The correlation mat...

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Abstract

A perforation scheme optimization method based on gray relational clustering, which establishes perforation parameters and oil well productivity models, and uses fuzzy clustering to analyze factors such as perforating gun type, perforating bullet type, hole depth, hole density, hole diameter, phase, etc. The influence of production rate and casing strength reduction coefficient is obtained to obtain the optimal plan of perforation parameters. This method reduces the subjective influence of plan decision makers, quantifies the optimal perforation plan reasonably, and saves a lot of manpower, material resources and Time cost is a new method to obtain parameters of perforation construction operation.

Description

technical field [0001] The invention relates to the technical field of oil and gas well perforation operations, in particular to a perforation scheme optimization method based on gray relational clustering. technical background [0002] Perforation completion is the use of perforators to establish passages for material circulation between oil, gas, water and other layers and the wellbore. wellbore to form a smooth channel. In oil and gas wells with perforated completion, the research and application of perforation technology and perforation bullet selection, perforation damage mechanism, and optimal design of perforation parameters directly affect the gas production status of oil wells. [0003] Different perforation parameters in perforation operations have different effects on the productivity of oil and gas wells. Through the research on the relationship between each parameter and productivity of perforation operations, a quantitative regression calculation model for the...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/50G06F17/18G06K9/62
CPCG06F17/18G06F30/23G06F18/2321
Inventor 薛继军爨莹
Owner XI'AN PETROLEUM UNIVERSITY