In the early 21st century, oil and gas production in the U.S. was conjectured to be in terminal-irreversible decline. But, thanks to the advancement of hydraulic fracturing technologies over the last decade, operators are now able to produce two-thirds of U.S. oil and gas output from almost impermeable shale formations. Despite the enormous success of the ‘shale revolution’, there are still debates about how long shale production will last and if there will be enough to subsidize a meaningful transition to ‘greener’ power sources. Most official pronouncements of shale oil and gas reserves are based on purely empirical curve-fitting approaches or geological volumetric calculations that tend to largely overestimate the actual reserves. As an alternative to these industry-standard forecasting methods, we propose a more reliable, ‘transparent’, physics-guided and data-driven approach to estimating future production rates of oil and gas in shales. Our physics-based scaling method captures all essential physics of hydrocarbon production and hydrofracture geometry, yet it is as simple as the industry-favored Decline Curve Analysis (DCA), so that most engineers can adopt it. We also demonstrate that our method is as accurate as other analytical methods and has the same predictive power as commercial reservoir simulators but with less data required and significantly faster computational time. To capture the uncertainties of play-wide production, we combine physical scaling with the Generalized Extreme Value (GEV) statistics. So far, we have implemented this method to nearly half a million wells from all major U.S. shale plays. Since the results of our analyses are not subject to bias, policy-makers ought not to assume that the shale production boom will last for centuries.
| Identifer | oai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/673816 |
| Date | 11 1900 |
| Creators | Saputra, Wardana |
| Contributors | Patzek, Tadeusz, Physical Science and Engineering (PSE) Division, Huser, Raphaël, Marder, Michael P., Hoteit, Hussein |
| Source Sets | King Abdullah University of Science and Technology |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Rights | 2022-11-29, At the time of archiving, the student author of this dissertation opted to temporarily restrict access to it. The full text of this dissertation will become available to the public after the expiration of the embargo on 2022-11-29. |
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