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Reservoir Performance

Since the last Reservoir Performance feature in September 2018, complex supply-and-demand challenges have continued to shape our technology and business-innovation models. Under significant pressure from several angles, operators around the world are focusing on lowering their production costs for both conventional and unconventional assets, while oilfield service companies are responding to customers’ cost-saving requests with incremental improvements in technology, supply chains, automation, and collaboration. While the current trends in machine learning and artificial intelligence certainly can help lower the production costs, future reservoir-performance improvements still will have to rely on reservoir characterization, surveillance, and optimization. The current quest for production-cost savings cannot continue without improvements in both operational efficiency and recovery factors.

In the past 12 months, 133 technical papers were presented at various conferences and meetings with a reservoir-performance focus and were reviewed for this feature, showcasing further advances in reservoir-performance monitoring, analysis, and optimization. For comparison, 157 and 160 technical papers were reviewed for the 2018 and 2017 features, respectively. Interestingly, this year, 39 papers had first authors from academia, 63 had first authors from operating companies, and 31 had first authors from oilfield service companies and consulting firms. For comparison, the review for the 2018 feature included 62 papers with first authors from academia, 70 with first authors from operating companies, and 25 with first authors from oilfield service companies and consulting firms.

The three primary papers selected and three alternative papers recommended as additional reading constitute a representative sample of the 133 papers reviewed for this feature. They are a geographically diverse mix of fundamental research, industrial research and development, and field-application studies, reporting the latest reservoir-performance advances.

This Month's Technical Papers

Improving Temperature-Logging Accuracy in Steamfloods

Integrating Fractional Flow Into Reservoir Surveillance Improves GOM Production

Chemical Tracer Flowback Data Help Understanding of Fluid Distribution

Recommended Additional Reading

SPE 192881 Reservoir Health Indicators Driving Performance Through Data Analytics by Mohamed Al Marzouqi, ADNOC, et al.

SPE 193701 Satellite INSAR Technology for Caprock-Integrity Monitoring of Cyclic Steam Stimulation and Steamflooding Heavy-Oil Production in Kuwait by Zu Biao Ren, Kuwait Oil Company, et al.

SPE 195366 Permeability and Porosity Evolution of Organic-Rich Shales as a Result of Heating by Tae Wook Kim, Stanford University, et al.

Silviu Livescu, SPE, is the chief scientist in the global Coiled Tubing Research and Engineering Centre of Baker Hughes, a GE company, in Calgary, with fundamental and applied research, industrial research and development, innovation, commercialization, and intellectual-property experience related to production engineering, completions, and reservoir engineering. He holds BS and MS degrees from Politehnica University of Bucharest in Romania and a PhD degree from the University of Delaware, all in mechanical engineering. Livescu is an SPE Distinguished Lecturer for 2018–2019 and is an executive editor for the Journal of Petroleum Science and Engineering and an associate editor for SPE Journal. He serves on the SPE Production and Facilities Advisory Committee, the SPE Management and Information Advisory Committee, and the JPT Editorial Committee. Livescu can be reached at https://ca.linkedin.com/in/silviu-livescu-14a96735.

Reservoir Performance

Silviu Livescu, SPE, Chief Scientist, Baker Hughes, a GE Company

01 September 2019

Volume: 71 | Issue: 9

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