Decline curve based models for predicting natural gas well performance  

作　　者：Arash Kamari Amir HMohammadi Moonyong Lee Alireza Bahadori 

机构地区：[1]Disciples of Chemical Engineering,School of Engineering,University of KwaZulu-Natal,Howard College Campus,King George V Avenue,Durban 4041,South Africa [2]Institut de Recherche en Genie Chimique et P
etrolier(IRGCP),Paris Cedex,France [3]Departement de Genie des Mines,de la Metallurgie et des Materiaux,Facult
e des Sciences et de Genie,Universite Laval,Quebec,QC G1V 0A6,Canada [4]School of Chemical Engineering,Yeungnam University,Gyeungsan,Republic of Korea [5]School of Environment,Science&Engineering,Southern Cross University,Lismore,NSW 2480,Australia [6]Australian Oil and Gas Services Pty Ltd,Lismore,NSW 2480,Australia

出　　处：《Petroleum》2017年第2期242-248,共7页油气（英文）

摘　　要：The productivity of a gas well declines over its production life as cannot cover economic policies.To overcome such problems,the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend.Therefore,reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz.the artificial neural network(ANN)modelling strategy,least square support vector machine(LSSVM)approach,adaptive neurofuzzy inference system(ANFIS),and decision tree(DT)method for the prediction of cumulative gas production as well as initial decline rate multiplied by time as a function of the Arps'decline curve exponent and ratio of initial gas flow rate over total gas flow rate.It was concluded that the results obtained based on the models developed in current study are in satisfactory agreement with the actual gas well production data.Furthermore,the results of comparative study performed demonstrates that the LSSVM strategy is superior to the other models investigated for the prediction of both cumulative gas production,and initial decline rate multiplied by time.

关 键 词：Decline curve PRODUCTION RATE Model Gas well 

分 类 号：F42[经济管理—产业经济]