Oilfield operators are paying more attention to monitors, sometimes in real time. Checks and balances are critical to make sure that primary production monitors facilitate a wealth of useful information and knowledge that justifies capital and operational expenditures. This additional surveillance is certainly tied to deploying more sensors and gathering more data. Credit is due to the rapid pace of applying data analytics to deal with large amounts of continuous data. Today, the dependence on primary monitors is higher than ever, so much so that orchestrated efforts are underway to make these nearly foolproof. Often, direct measurements are supplemented with model predictions. Also notably visible are the efforts to integrate multiple perspectives of sustained production.
In the pursuit of consistency and reliability for multiphase flow meters (MPFMs), paper SPE 222068 demonstrates an example of how to monitor remote metering. This essentially advocates monitoring of production monitors. As more subsea MPFMs are deployed to monitor extended assets, these need to be monitored systematically. Such a burden does not have to be overwhelmed by the influx of huge amounts of data. As such, dynamic verification of the output of sensors is ensured by using various intelligent techniques so that the gathered additional data leads to meaningful outcomes when the MPFMs operate within their operating envelopes.
Continuous, accurate knowledge of production rate and pressure is important not only for field surveillance but also for effective production optimization. A hybrid approach of integrating physics-based and machine-learning models for bottomhole pressure and rate prediction is presented in paper SPE 218762. The benefits of this approach have been reported with the capability of reproducing missing or filler data during infrequent measurements of production rate and pressure.
Recognizing the questionable reliability in some cases of flow profiles in horizontal wells captured by production-logging tools, paper URTeC 4054832 presents advanced thermal-hydrodynamic modeling. This rigorous simulation, designed specifically for horizontal wells, helps determine the contributions of fractures and the matrix to a well subject to complex fluid circulation inside and outside the liner.
The papers presented for additional reading also show a similar trend in production monitoring.
This Month’s Technical Papers
Multiphase Flowmeter System Automates Remote Monitoring
Hybrid Approach Predicts Accurate Flow Rates and Bottomhole Pressure
Thermal-Hydrodynamic Modeling Includes Fracture-Flow Analysis To Assess Well Flow
Recommended Additional Reading
SPE 222999 Advanced Fault Diagnosis and Prognostic Maintenance Strategies for Continuous Operation of Permanent Downhole Gauge Systems by Ali Dheyaa Mohammed, Petronas, et al.
URTeC 4053742 Interference Testing in Shale: A Generalized Degree of Production Interference and Developing New Insights Into the Chow Pressure Group by Chris Ponners, ResFrac, et al.
IPTC 23972 Unlocking Commingled Production Using Geochemical Production Allocation by S. Mejia, SLB, et al.
N.M. Anisur Rahman, SPE, is a senior petroleum engineering consultant with the Well Testing Division of the Reservoir Description and Simulation Department at Saudi Aramco. He holds BS and MS degrees in mechanical engineering from the Bangladesh University of Engineering and Technology and a PhD degree in petroleum engineering from the University of Alberta. Rahman is registered as a professional engineer in the Province of Alberta, Canada. He is a recipient of the 2016 SPE Middle East Regional Reservoir Description and Dynamics Award and is a member of the JPT Editorial Review Board.