The Application of Data Validation and Reconciliation to Upstream Production Measurement Integration and Surveillance – Field Study (SPE ATCE 2021)
This paper presents the application of an advanced Data Validation and Reconciliation (DVR) methodology to a real offshore oil and gas field. The objective is to consistently integrate all available measurements, including well, surface, and fluid data, in order to automatically detect and correct measurement errors and reduce overall uncertainty in production data.
The DVR approach combines measurement redundancy with physical conservation laws to estimate the most probable production rates and to quantify their uncertainty. The methodology delivers coherent, real-time production data that can be used for production surveillance, well test validation, virtual metering, and production allocation. Field results demonstrate how DVR improves data reliability and supports better operational decision making.
Authors
Abstract
With the advent of increased measurements and instrumentation in oil and gas upstream production infrastructure; in the wellbore, in subsea and on surface processing facilities, data integration from all sources can be used more effectively in producing consistent and robust production profiles. The proposed data integration methodology aims at identifying the sources of measurement and process errors and removing them from the system. This ensures quasi error-free data when driving critical applications such as well rate determination from virtual and multiphase meters, and production allocation schemes, to name few. Confidence in the data is further enhanced by quantifying the uncertainty of each measured and unmeasured variable.
Advanced Data Validation and Reconciliation (DVR) methodology uses data redundancy to correct measurements. As more data is ingested in a modeling system the statistical aspect attached to each measurement becomes an important source of information to further improve its precision. DVR is an equation-based calculation process. It combines data redundancy and conservation laws to correct measurements and convert them into accurate and reliable information. The methodology is used in upstream oil & gas, refineries and gas plants, petrochemical plants as well as power plants including nuclear. DVR detects faulty sensors and identifies degradation of equipment performance. As such, it provides more robust inputs to operations, simulation, and automation processes.
The DVR methodology is presented using field data from a producing offshore field. The discussion details the design and implementation of a DVR system to integrate all available field data from the wellbore and surface facilities. The integrated data in this end-to-end evaluation includes reservoir productivity parameters, downhole and wellhead measurements, tuned vertical lift models, artificial lift devices, fluid sample analysis and thermodynamic models, and top facility process measurements. The automated DVR iterative runs solve all conservation equations simultaneously when determining the production flowrates “true values” and their uncertainties. The DVR field application is successfully used in real-time to ensure data consistency across a number of production tasks including the continual surveillance of the critical components of the production facility, the evaluation and validation of well tests using multiphase flow metering, the virtual flow metering of each well, the modeling of fluid phase behavior in the well and in the multistage separation facility, and performing the back allocation from sales meters to individual wells.