A genetic algorithm integrated with Monte Carlo simulation for the field layout design problem

被引：9

作者：

de Padua Agripa Sales, Leonardo ^{[1
]}

Pitombeira-Neto, Anselmo Ramalho ^{[2
]}

de Athayde Prata, Bruno ^{[2
]}

机构：

[1] Univ Fed Ceara, Operat Res Prod & Logist Lab, Campus Pici,Bl 714, BR-60440900 Fortaleza, Ceara, Brazil

[2] Univ Fed Ceara, Dept Ind Engn, Operat Res Prod & Logist Lab, Campus Pici,Bl 714, BR-60440554 Fortaleza, Ceara, Brazil

来源：

OIL AND GAS SCIENCE AND TECHNOLOGY-REVUE D IFP ENERGIES NOUVELLES | 2018年 / 73卷

关键词：

OFFSHORE PLATFORMS; SCHEDULING PROBLEM; MILP MODEL; OPTIMIZATION; PERFORMANCE; LOCATION; WELLS;

D O I：

10.2516/ogst/2018017

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Oil and gas production is moving deeper and further offshore as energy companies seek new sources, making the field layout design problem even more important. Although many optimization models are presented in the revised literature, they do not properly consider the uncertainties in well deliverability. This paper aims at presenting a Monte Carlo simulation integrated with a genetic algorithm that addresses this stochastic nature of the problem. Based on the results obtained, we conclude that the probabilistic approach brings new important perspectives to the field development engineering.

引用

页数：16

共 55 条

[21] Probabilistic Production Forecasting for Unconventional Reservoirs With Stretched Exponential Production Decline Model [J].