| Title | Bayesian probabilistic dual-flow-regime decline curve analysis for complex production profile evaluation |
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| Author | Kong, B ; Chen, S;
Chen, Z; Zhou, Q |
| Source | Journal of Petroleum Science & Engineering vol. 195, 107623, 2020 p. 1-13, https://doi.org/10.1016/j.petrol.2020.107623 |
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| Year | 2020 |
| Alt Series | Natural Resources Canada, Contribution Series 20200287 |
| Publisher | Elsevier B.V. |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf; html |
| Subjects | fossil fuels; Science and Technology; petroleum industry; hydrocarbons; gas; oil; production; reserve estimates; models; reservoirs; fluid flow; flow regimes; bedrock geology; lithology; sedimentary
rocks; shales; computer simulations; gas wells; Montney Formation; machine learning; Artificial intelligence; Methodology |
| Illustrations | plots; tables; histograms; time series; profiles; sketch maps; bar graphs |
| Program | Geoscience for New Energy Supply (GNES) Shale-hosted petroleum resource assessment |
| Released | 2020 07 11 |
| Abstract | Decline curve analysis (DCA) has been broadly applied in the oil and gas industry to predict future production and estimate reserves. The Arps decline model is one of the most popular DCA models used by
the oil and gas industry. This model was designed for boundary dominated flow in conventional reservoirs. In practice, it has also been widely applied to both transient flow and boundary dominated flow in conventional reservoirs. Applied to a complex
production profile involving dual flow regime from artificially enhanced tight/shale reservoir, each production segment needs to be analyzed separately. Although several analytical decline curve models have been developed in recent years to address
the problem, none of them is flexible enough to model both production profiles from a single flow regime and a dual flow regime. In this study, we introduce a new production decline analysis model that can fit both production profiles from single
flow regime and dual flow regime without the need to separate the production segments. We also introduce a probabilistic measure using Bayesian Markov Chain Monte Carlo simulation to determine the existence of dual flow regimes, the location of the
regime switch, and uncertainties in parameter estimations with the new model. The proposed Probabilistic Dual Regime Decline Curve Analysis (PDR-DCA) method is tested on 344 horizontal Northern Montney gas wells. This proposed Bayesian approach
provides a workflow to generate probabilistic decline curve for both single and dual segment production profile, probabilistic type well curve for a well group, and production prediction for well with very short production history. |
| GEOSCAN ID | 326884 |
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