Optimization of Displacement Efficiency in a CO&lt;sub&gt;2&lt;/sub&gt; Flooding Reservoir Under Uncertainty

Chen, S.; Li, H.; Yang, Daoyong

doi:10.2118/2008-127-ea

Cited by 3 publications

(1 citation statement)

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“…Although many techniques have been made available for production optimization in the upstream oil and gas industry, it is still a challenging task to optimize reservoir performance in the presence of physical and/or financial uncertainties [35]. Economic success of an EOR project principally depends on the efficiency of the selected method in the reservoir of interest and the way it is deployed.…”

Section: Discussionmentioning

confidence: 99%

Smart Proxy Modeling of SACROC CO2-EOR

Gholami

Mohaghegh

Maysami

2019

Fluids

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Large CO 2 -enhanced oil recovery (EOR) projects usually contain an abundance of geological and good performance data. While this volume of data leads to robust models, it often results in difficult to manage, slow-running numerical flow models. To dramatically reduce the numerical run-times associated with the traditional simulation techniques, this work investigated the feasibility of using artificial intelligence and machine learning technologies to develop a smart proxy model of the Scurry Area Canyon Reef Operators Committee (SACROC) oilfield, located in the Permian Basin, TX, USA. Smart proxy models can be used to facilitate injection-production optimization for CO 2 -EOR projects. The use of a coupled grid-based, and well-based surrogate reservoir model (SRM) (also known as smart proxy modeling) was investigated as the base of the optimization. A fit-for-purpose coupled SRM, which executes in seconds, was built based on high-resolution numerical reservoir simulation models of the northern platform of the SACROC oilfield. This study is unique as it is the first application of coupled SRM at a large oilfield. The developed SRM was able to identify the dynamic reservoir properties (pressure, saturations, and component mole-fraction) at every grid-block, along with the production characteristics (pressure and rate) at each well. Recent attempts to use machine learning and pattern recognition to build proxy models have been simplistic, with limited predictive capabilities. The geological model used in this study is comprised of more than nine million grid blocks. The high correlation between the actual component and SRM, which can be visualized by mapping the properties, along with the fast footprint of the developed model demonstrate the successful application of this methodology.

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Section: Discussionmentioning

confidence: 99%

Smart Proxy Modeling of SACROC CO2-EOR

Gholami

Mohaghegh

Maysami

2019

Fluids

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Performance of CO2-EOR and Storage Processes Under Uncertainty

Ampomah¹,

Balch²,

Cathar³

et al. 2016

SPE Europec Featured at 78th EAGE Conference and Exhibition

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This paper presents an optimization approach using a reservoir field scale compositional flow model to co-optimize oil production and CO2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. A geocellular model constructed from geophysical geological and engineering data acquired from the unit was used for the study. An initial history match of primary and secondary recovery constructed was used as basis for CO2 flood study. A scenario based prediction model constructed for FWU (Ampomah et al. 2016a) was used as the baseline case for comparison to study the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO2 storage. A multi objective function that considers both oil recovery and CO2 storage was defined. Initial sensitivity analysis using a Latin-hypercube sampling technique was used to study the effects of operational uncertain variables on a defined objective function. A number of these operational variables were selected as control variables to be included in the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without uncertainty. Vertical permeability anisotropy ratio (Kv/Kh) was selected as the uncertain parameter in optimization, with uncertainty based on experience from the history match. A risk aversion factor was used to represent results at various confidence levels. The simulation results were compared to a baseline case that predicted a CO2 storage of 75% purchased CO2 and oil recovery of 72% original oil in place. The results showed an improved approach for optimizing oil recovery and CO2 storage within FWU. At the end of 21 years of prediction out of the optimal case, more than 94% of purchased CO2 has been stored and nearly 80% of the oil recovered. The sensitivity analysis reduced the number of control variables to lessen computational time. The defined objective function proved to be a robust approach to co-optimize oil recovery and CO2 storage. The Farnsworth CO2 project will serve as a benchmark for future CO2–EOR or CCUS projects in the Anadarko basin or geologically similar basins throughout the world.

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How Leaders Can Shape the Oil & Gas Industry – Accelerating Innovations Through Business & Environmental Intelligent Systems

Louis

Khan

Ali

2021

SPE Middle East Oil &Amp; Gas Show and Conference

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One of the harms to climate brought about by anthropogenically instigated environmental change is the overabundance creation of CO2 because of industrialization. Research and development endeavors so far have been focused on the improvement of CCS (Carbon Capture and Sequestration), with the fundamental spotlight on the best way to eliminate CO2 from vent gases and how to cover it perpetually in deep aquifers or depleted oil and gas reservoirs to save the environment from the detrimental effects of CO2. At one side, the alarming situation due to excess emission of CO2 from industries has been bulled out and simultaneously, there is higher potential for CO2 in the depleted oil fields which can aid to the Enhanced Oil Recovery (EOR) through the prolonged CO2 injection in depleted oil fields. It is currently turning out to be certain that CCS technology could advance the utilization of fossil fuels than in any case recently thought. This paper discusses the integration of Carbon Capture and Sequestration (CCS) technology with the progressive strategy of Enhanced Oil Recovery (EOR). CCS includes various advances that can be utilized to catch CO2 from point sources. Countries that are badly affected by the harmful effects of global warming with depleting oil reserves in the very near future can be the most viable target of the CCS Project. The scope and potential of different techniques of CCS along with the opportunities and challenges and the real case scenarios happening in the world are discussed in detail. The economics, process cycle and case studies of this futuristic technology intend to give valuable insight to the implementation of this integrated technique to the prevalent depleting oil fields around the globe.

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Optimization of Displacement Efficiency in a CO<sub>2</sub> Flooding Reservoir Under Uncertainty

Cited by 3 publications

References 0 publications

Smart Proxy Modeling of SACROC CO2-EOR

Smart Proxy Modeling of SACROC CO2-EOR

Performance of CO2-EOR and Storage Processes Under Uncertainty

How Leaders Can Shape the Oil & Gas Industry – Accelerating Innovations Through Business & Environmental Intelligent Systems

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