A Technically Rigorous and Fully Automated System for Performance Monitoring and Production Test Validation

Abstract

Abstract This paper describes the integration between a dynamic surveillance tool and a system analysis tool to provide the surveillance engineer with a new, fully automated and technically rigorous system, capable of true performance monitoring and reliable production test validation. The combination of the software tools and workflows resulted in an innovative Production Management and Optimization system (PROMO), with new and extended capabilities beyond those of either of the stand-alone packages. Algorithms were defined in order to automatically compare actual and modeled production (taking into account FTHP variations) on a daily basis. Additionally, as new production test data becomes available, the system can automatically display it on a calibrated IPR plot for fast and rigorous validation. The system has also been designed such that when a new well test is approved and validated, the IPR curve will be automatically re-calibrated to honor the new performance measurements. In principle no gas or oil field is outside the scope of such an application. Once an appropriate interface is set up to allow for data exchange between the surveillance and system analysis tools, it is a matter of building the appropriate processes that will yield the most beneficial results in terms of production optimization and data validation. The addition of data linkages to corporate data warehouses results in a system that requires little maintenance of input parameters and is always up-to-date with respect to the available data. The PROMO system, currently deployed in one gas plant (comprising of seven offshore gas fields, 14 platforms and 180 production strings) and one oil plant (comprising of two onshore oil fields and 10 production strings), is allowing the production engineers to easily identify under-performing strings (completions) and promptly intervene. In addition to providing a more reliable and time effective production test validation process, the engineer can fully analyze current well performance with daily, historical and forecasted data. Additional benefits include calculation of historic SBHP's from production tests, dependable production allocation (with great benefit for overall field management and reservoir modeling) and considerable time savings as pertinent data is automatically (as opposed to manually) handled and used in the system analysis algorithms. Introduction Production surveillance and reliable allocation play a major role in the efforts to optimize and maximize production from a field. Many software solutions exist to monitor actual performance variables of well and field systems. Just as important is performance modeling through system analysis methods and again the relevant commercial packages are several and well established. However, the added value from combining the two systems (production monitoring and system analysis) has not been entirely captured to date - at least not to its full potential. The operator involved in this project was no exception. Production data was stored in two corporate databases (daily and monthly production) and monitored using desktop spreadsheets. The inherent drawbacks to this surveillance process were redundant, static and localized subsets of corporate databases, no standardized or transferable workflows or formats, lack of strict data quality control and integrity, and poor fit-for-purpose of the spreadsheet software. Additionally the overall system was lacking the integrated system analysis capabilities to effectively monitor string/well performance. The necessary system analysis workflows were being achieved using an industry standard software tool, but at the expense of manual data entry. An obvious problem with such a disjointed system was the lack of communication between the two tool sets, resulting in lengthy production data handling and formatting before data could be returned to the system analysis software for the computations. Also there was no mechanism in place to return the system analysis results for use in the surveillance process.