{"title":"Decline Line Analysis DLA: A Method for Forecasting Cumulative Production for Solution-Gas Drive Reservoirs Based on Fetkovich Type Curve Approach","authors":"Omaga Sumaila","doi":"10.2118/198734-MS","DOIUrl":null,"url":null,"abstract":"\n A conventional method for DCA for a solution-gas drive reservoir is the Arp's Approach. Another approach, an improved approach, is the Fetkovich Type Curve Approach which involves the combination of rate equation and material balance equation for finite systems to obtain rate-time equations for solution-gas drive reservoir using backpressure exponent(n) in place of Arp's decline exponent(b). This improved approach, however, has a number of limitations. First, it is difficult to judge which type curve production data match. It has a lower resolution. Also, the developed cumulative-rate model for the material balance equation form: PR2is linear with Np, tends to give inaccurate result.\n This paper, first, presents a cumulative-rate model using a mathematical approach. Then, the Fetkovich rate-time relationships for both the material balance equation forms: PR2is linear with Np, PR is linear with Np, are transferred into linear relationships(in a log-log plot) by finding the derivative of the natural logarithm of the dimensionless rate(qDd) with respect to the dimensionless time(tDd). Consequently, the type lines are generated and upon about fifty (50) trials, conditions required for optimum workability are presented.\n The developed cumulative-rate model was validated with field data from a reservoir in the Niger Delta. The correlation between forecasted cumulative production and actual production data is 0.99988. Thus, indicating high positive correlation. Also, the linearized models were validated with production data from Arbuckle Lime, Kansas. The correlation too, is as high as 0.99988. Thereafter, a user-friendly Microsoft Excel spreadsheet application for computing cumulative production given rate is created using Excel VBA.","PeriodicalId":11110,"journal":{"name":"Day 2 Tue, August 06, 2019","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Tue, August 06, 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/198734-MS","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A conventional method for DCA for a solution-gas drive reservoir is the Arp's Approach. Another approach, an improved approach, is the Fetkovich Type Curve Approach which involves the combination of rate equation and material balance equation for finite systems to obtain rate-time equations for solution-gas drive reservoir using backpressure exponent(n) in place of Arp's decline exponent(b). This improved approach, however, has a number of limitations. First, it is difficult to judge which type curve production data match. It has a lower resolution. Also, the developed cumulative-rate model for the material balance equation form: PR2is linear with Np, tends to give inaccurate result.
This paper, first, presents a cumulative-rate model using a mathematical approach. Then, the Fetkovich rate-time relationships for both the material balance equation forms: PR2is linear with Np, PR is linear with Np, are transferred into linear relationships(in a log-log plot) by finding the derivative of the natural logarithm of the dimensionless rate(qDd) with respect to the dimensionless time(tDd). Consequently, the type lines are generated and upon about fifty (50) trials, conditions required for optimum workability are presented.
The developed cumulative-rate model was validated with field data from a reservoir in the Niger Delta. The correlation between forecasted cumulative production and actual production data is 0.99988. Thus, indicating high positive correlation. Also, the linearized models were validated with production data from Arbuckle Lime, Kansas. The correlation too, is as high as 0.99988. Thereafter, a user-friendly Microsoft Excel spreadsheet application for computing cumulative production given rate is created using Excel VBA.