Eleonora Pignotti, Salvatore Spagnolo, S. Pilone, Gianni Baldassarri, P. Cappuccio, Alberto Valente, P. Greco, Mariangela Gonzalez Zamora
{"title":"Interpreting Downhole Esp Data for Predicting Production Performance by Use of Inversion-Based Methods in South Europe Field","authors":"Eleonora Pignotti, Salvatore Spagnolo, S. Pilone, Gianni Baldassarri, P. Cappuccio, Alberto Valente, P. Greco, Mariangela Gonzalez Zamora","doi":"10.2523/iptc-22241-ms","DOIUrl":null,"url":null,"abstract":"\n The objective of this paper is to demonstrate how a physics-based data driven model and inversion procedures can transform traditional ESP well monitoring into an indispensable tool for predicting multiphase flow rates in ESP production wells. Model and prediction techniques are evaluated by comparison with real field data, measured both live and retroactively from different ESP producing wells located in the South Europe producing field.\n Operational data commonly gathered by ESP gauge, such as Pressures data, Motor Current and Operative Frequency can be used to predict flow through ESP components, without need for rental of expensive Well Testing equipment. The exploitation of a similar advantage is made possible by the application of artificial intelligence algorithm joined with physics based modelling, taking in as input ESP dynamic data and giving as output a simulation–with acceptable accuracy- of the continuous downhole flow and reservoir properties, allowing the oil operator to obtain key information to optimize well production based on the calculation of ESP operational point.\n Such cost-effective metering technology is already suitable for online real-time systems implementation and has already been put in place in South Europe field, where it gives reliable results that will yield ongoing ESP run life improvement through its constant application. The improvement of several ESP KPIs, such as MTBF and MTTF, is strictly related to a more accurate follow up of the ESP operative point, hence of the ESP production. Higher ESP MTBF/MTTF might lead to a reduction of the number of necessary ESP replacement workover for year, thus causing the enhancement of hydrocarbon recovery and a reduction of the differed production.In addition to all of this, the possibility of virtual metering well production performance by means of a virtual model might provide a sensible reduction of the number of replacement systems provided from Service Companies, hence the overall optimization of production operation costs.\n The increasing need for operational efficiency, cost reduction and improved equipment means that service life has driven the recent technological developments related to electrical submersible pump (ESP) well operation management. This paper well described the application and the benefits of such technology to be used as reference successful case by other key players in the O&G market.","PeriodicalId":10974,"journal":{"name":"Day 2 Tue, February 22, 2022","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Tue, February 22, 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2523/iptc-22241-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
The objective of this paper is to demonstrate how a physics-based data driven model and inversion procedures can transform traditional ESP well monitoring into an indispensable tool for predicting multiphase flow rates in ESP production wells. Model and prediction techniques are evaluated by comparison with real field data, measured both live and retroactively from different ESP producing wells located in the South Europe producing field.
Operational data commonly gathered by ESP gauge, such as Pressures data, Motor Current and Operative Frequency can be used to predict flow through ESP components, without need for rental of expensive Well Testing equipment. The exploitation of a similar advantage is made possible by the application of artificial intelligence algorithm joined with physics based modelling, taking in as input ESP dynamic data and giving as output a simulation–with acceptable accuracy- of the continuous downhole flow and reservoir properties, allowing the oil operator to obtain key information to optimize well production based on the calculation of ESP operational point.
Such cost-effective metering technology is already suitable for online real-time systems implementation and has already been put in place in South Europe field, where it gives reliable results that will yield ongoing ESP run life improvement through its constant application. The improvement of several ESP KPIs, such as MTBF and MTTF, is strictly related to a more accurate follow up of the ESP operative point, hence of the ESP production. Higher ESP MTBF/MTTF might lead to a reduction of the number of necessary ESP replacement workover for year, thus causing the enhancement of hydrocarbon recovery and a reduction of the differed production.In addition to all of this, the possibility of virtual metering well production performance by means of a virtual model might provide a sensible reduction of the number of replacement systems provided from Service Companies, hence the overall optimization of production operation costs.
The increasing need for operational efficiency, cost reduction and improved equipment means that service life has driven the recent technological developments related to electrical submersible pump (ESP) well operation management. This paper well described the application and the benefits of such technology to be used as reference successful case by other key players in the O&G market.