Abstract
Determination of optimal well locations plays an important role in the efficient recovery of hydrocarbon resources. However, it is a challenging and complex task. The objective of this paper is to determine the optimal well locations in a heavy oil reservoir under production using a novel recovery process in which steam is generated, in situ, using thermochemical reactions. Self-adaptive differential evolution (SaDE) and particle swarm optimization (PSO) methods are used as the global optimizer to find the optimal configuration of wells that will yield the highest net present value (NPV). This is the first known application, where SaDE and PSO methods are used to optimize well locations in a heavy oil reservoir that is recovered by injecting steam generated in situ using thermo-chemical reactions. Comparison analysis between the two proposed optimization techniques is introduced. On the other hand, laboratory experiments were performed to confirm the heavy oil production by thermochemical means. CMG STARS simulator is utilized to simulate reservoir models with different well configurations. The experimental results showed that thermochemicals, such as ammonium chloride along with sodium nitrate, can be used to generate in situ thermal energy, which efficiently reduces heavy-oil viscosity. Comparison of results is made between the NPV achieved by the well configuration proposed by the SaDE and PSO methods. The results showed that the optimization using SaDE resulted in 15% increase in the NPV compared to that of the PSO after 10 years of production under in situ steam injection process using thermochemical reactions.
| Original language | English |
|---|---|
| Article number | 032906 |
| Journal | Journal of Energy Resources Technology, Transactions of the ASME |
| Volume | 141 |
| Issue number | 3 |
| DOIs | |
| State | Published - 1 Mar 2019 |
Bibliographical note
Publisher Copyright:Copyright © 2019 by ASME.
Keywords
- Differential evolution
- Heavy oil recovery
- In situ steam generation
- Net present value
- Particle swarm optimization
- Well-placement optimization
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
- Fuel Technology
- Energy Engineering and Power Technology
- Mechanical Engineering
- Geochemistry and Petrology
Fingerprint
Dive into the research topics of 'Well-placement optimization in heavy oil reservoirs using a novel method of in situ steam generation'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver