2 research outputs found
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Feedback control of polymer flooding process considering geologic uncertainty
textPolymer flooding is economically successful in reservoirs where the water flood mobility ratio is high, and/or the reservoir heterogeneity is adverse, because of the improved sweep resulting from the mobility-controlled oil displacement. The performance of a polymer flood can be further improved if the process is dynamically controlled using updated reservoir models and a closed-loop production optimization scheme is implemented. However, the formulation of an optimal production strategy is based on uncertain production forecasts resulting from uncertainty in spatial representation of reservoir heterogeneity, geologic scenarios, inaccurate modeling, scaling, just to cite a few factors. Assessing the uncertainty in reservoir modeling and transferring it to uncertainty in production forecasts is crucial for efficiently controlling the process. This dissertation presents a feedback control framework that (1) assesses uncertainty in reservoir modeling and production forecasts, (2) updates the prior uncertainty in reservoir models by integrating continuously monitored production data, and (3) formulates optimal injection/production rates for the updated reservoir models. This approach focuses on assessing uncertainty in reservoir modeling and production forecasts originated mainly by uncertain geologic scenarios and spatial variations of reservoir properties (heterogeneity). This uncertainty is mapped in a metric space created by comparing multiple reservoir models and measuring differences in effective heterogeneity related to well connectivity and well responses characteristic of polymer flooding.
Continuously monitored production data is used to refine the uncertainty map using a Bayesian inversion algorithm. In contrast to classical approach of history matching by model perturbation, a model selection problem is implemented where highly probable reservoir models are selected to represent the posterior uncertainty in production forecasts. The model selection procedure yields the posterior uncertainty associated with the reservoir model. The production optimization problem is solved using the posterior models and a proxy model of polymer flooding to rapidly evaluate the objective function and response surfaces to represent the relationship between well controls and an economic objective function. The value of the feedback control framework is demonstrated with two examples of polymer flooding where the economic performance was maximized.Petroleum and Geosystems Engineerin
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Proposal of a rapid model updating and feedback control scheme for polymer flooding processes
textThe performance of Enhanced Oil Recovery (EOR) processes is adversely affected by the heterogeneous distribution of flow properties of the rock. The effects of heterogeneity are further highlighted when the mobility ratio between the displacing and the displaced fluids is unfavorable. Polymer flooding aims to mitigate this by controlling the mobility ratio resulting in an increase in the volumetric swept efficiency. However, the design of the polymer injection process has to take into account the uncertainty due to a limited knowledge of the heterogeneous properties of the reservoir. Numerical reservoir models equipped with the most updated, yet uncertain information about the reservoir should be employed to optimize the operational settings. Consequently, the optimal settings are uncertain and should be revised as the model is updated. In this report, a feedback-control scheme is proposed with a model updating step that conditions prior reservoir models to newly obtained dynamic data, and this followed by an optimization step that adjusts well control settings to maximize (or minimize) an objective function.
An illustration of the implementation of the proposed closed-loop scheme is presented through an example where the rate settings of a well affected by water coning are adjusted as the reservoir models are updated. The revised control settings yield an increase in the final value of the objective function. Finally, a fast analog of a polymer flooding displacement that traces the movement of random particles from injectors to producers following probability rules that reflect the physics of the actual displacement is presented. The algorithm was calibrated against the full-physics simulation results from UTCHEM, the compositional chemical flow simulator developed at The University of Texas at Austin. This algorithm can be used for a rapid estimation of basic responses such as breakthrough time or recovery factor and to provide a simplified characterization the reservoir heterogeneity.
This report is presented to fulfill the requirements to obtain the degree of Master of Science in Engineering under fast track option. It summarizes the research proposal presented for my doctorate studies that are currently ongoing.Petroleum and Geosystems Engineerin