OPTIMIZATION OF A DEVELOPMENT MODEL FOR BLOCK 64 UNDER UNCERTAINTY

被引:0
|
作者
Huerta Quinones, Victor A. [1 ]
机构
[1] PERUPETRO SA, Dept Desarrollo & Prod, Lima, Peru
来源
FUENTES EL REVENTION ENERGETICO | 2014年 / 12卷 / 02期
关键词
Optimization; Development; numerical Simulation; range of uncertainty;
D O I
暂无
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
The optimization of field development is the most important and complex tasks in the Oil & Gas Industry from the fact that technical and economic aspects should be considered to maximize the value of assets. Usually, there are estimated three (03) scenes of technically recoverable volumes, under determinative and probabilistics methods, and a case is in use base on which a forecast of production is elaborated, and eventually, an economic evaluation, with some analysis of sensibility. The complexity in the optimization of the development in a field is tied to all the sources of uncertainty that usually they present at the same time, such as a strong correlation between the variation of prices, the technically recoverable volumes, the number of wells of development, the investments of the capital and the operative costs. In consequence, the uncertainty and dependence between the variables of entry of a model might not be shaped by conventional tool. Proposes a new probabilistic tool to integrate the estimation of technically recoverable volumes and the prediction of the productive behavior. The volumes of hydrocarbons are estimated by means of a volumetric equation, which parameters have been defined to Monte-Carlo simulation; thousands of accomplishments are captured and expressed as a curve of expectation of recoverable hydrocarbons The second part of the model allows to predict the performance of the field, by means of you curl type suitably fitted to the analogous behavior of neighboring fields and the results of a numerical conceptual simulation; every curve of production will answer to a volumetric accomplishment, with which it is possible to obtain the whole range of forecasts associated with his degree of uncertainty (expressed by means of percentiles).
引用
收藏
页码:15 / 23
页数:9
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