Complicated well hole track optimization method based on fast self-adaption quantum genetic algorithm

A quantum genetic algorithm and wellbore trajectory technology, applied in the field of advanced intelligent optimization algorithms, can solve problems such as poor real-time algorithms, complex constraints, and many independent variables

Pending Publication Date: 2017-07-11
XI'AN PETROLEUM UNIVERSITY
View PDF4 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of the characteristics of many independent variables and complex constraints in the complex three-dimensional wellbore trajectory optimization problem, in order to improve the accuracy and optimization speed of the complex wellbore trajectory optimization results with m

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Complicated well hole track optimization method based on fast self-adaption quantum genetic algorithm
  • Complicated well hole track optimization method based on fast self-adaption quantum genetic algorithm
  • Complicated well hole track optimization method based on fast self-adaption quantum genetic algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0055] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0056] The complex wellbore trajectory optimization method based on fast adaptive quantum genetic algorithm includes the following steps:

[0057] (1) Analyze the characteristics of the Fibonacci sequence, generate the Fibonacci sequence, and calculate F n / F n+x .

[0058] ①If you use F n Represents the nth element in the sequence, then the Fibonacci sequence satisfies:

[0059]

[0060] In formula (19), the sequence starts from the third item, and each item is equal to the sum of the previous two items. Analyzing this series, we have:

[0061]

[0062] Taking the natural logarithm on both sides of formula (20), then:

[0063] ln(g(x))=-x*ln(1.6180340)=-0.4812x

[0064] (twenty one)

[0065] In formula (21), x=0, 1, 2.... When x=0,1,2...,15, n=15, analyze x and F n / F n+x Fitting relationship, the fitting relationship is as image 3 ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a complicated well hole track optimization method based on a fast self-adaption quantum genetic algorithm. The method comprises the following steps that through the analysis of an Fibonacci number sequence, the condition that the number sequence has a negative index characteristic is discovered, and the characteristic is introduced into a quantum rotation gate rotating angle step length updating strategy, wherein the space complexity of the algorithm is not increased, the time complexity of the algorithm is lowered, the algorithm efficiency is greatly improved, and the operation time of the algorithm is shortened; secondly, any one quantum position is enabled to be in one-to-one correspondence to points on a Bloch ball surface, so that the ergodicity of a solution is improved; finally, by aiming at a multi-target complicated three-dimensional well hole track optimization problem, under constraint conditions of each well section, casing pipe length and target vertical well depth, the FAQGA optimization is used for practically measuring the well depth TMD; a well body, a well inclined angle, a well inclination azimuth angle and well section curvature parameters are optimized, thus realizing the precise and efficient well hole track optimization.

Description

technical field [0001] The invention relates to the field of advanced intelligent optimization algorithms, in particular to a method for optimizing complex borehole trajectories based on fast self-adaptive quantum genetic algorithms. Background technique [0002] With the continuous improvement of oil and gas field development technology, the types of complex wellbore trajectories such as directional wells, ultra-deep wells, horizontal wells, extended-reach wells, sidetracking wells, lateral wells, and multi-target wells are increasing day by day. Quantity growth. Scientific wellbore trajectory design is one of the key technologies in drilling engineering. [0003] In the wellbore trajectory optimization, there are mainly two stages: one is to convert the three-dimensional wellbore trajectory optimization problem into a two-dimensional optimization problem on the plane, and use the optimization method to realize the optimization of the two-dimensional wellbore trajectory; t...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F17/50
CPCG06F30/17
Inventor 沙林秀张奇志李琳邱顺
Owner XI'AN PETROLEUM UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products