History Match and Polymer Injection Optimization in a Mature Field Using the Ensemble Kalman Filter

Raniolo, S.; Dovera, Laura; Cominelli, Alberto; Callegaro, Chiara; Masserano, Franco

doi:10.3997/2214-4609.20142642

Cited by 28 publications

(27 citation statements)

References 12 publications

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“…A comparison of the performance of these variations is described in the numerical results below. Raniolo et al (2013) did not achieve optimized results of any significant value when using the original formulation which they reasoned to be the result of a poor gradient estimate. To counter this they proposed the use of a set of five selected models which would approximately capture the geological uncertainty.…”

Section: Different Gradient Formulationsmentioning

confidence: 99%

“…This subset of five models was chosen to roughly represent two P10 models, two P90 models and one P50 model. Raniolo et al (2013) used the EM algorithm to rank the geological realizations while Yang et al (2011) used direct numerical simulation of a SAGD process for the ranking. With this set of models, they then coupled each model with multiple control samples to estimate different individual gradients (akin to deterministic optimization), the summation of which results in a single robust gradient.…”

Section: Different Gradient Formulationsmentioning

confidence: 99%

“…Additionally, Raniolo et al (2013) and Li et al (2012), have investigated the applicability of approximate gradient techniques for life-cycle robust water flooding optimization while Yang et al (2011) applied the robust optimization principle to a Steam-Assisted Gravity Drainage (SAGD) application. Yasari et al 2013, Pajonk et al 2011 and Awotunde and Sibaweihi (2011) have investigated the applicability of robust multi-objective optimization using evolutionary algorithms for well control and well placement optimization with objectives varying from economic criteria to voidage replacement ratio and cumulative production volumes.…”

Section: Introductionmentioning

confidence: 99%

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Robust Ensemble-based Multi-objective Optimization

et al. 2014

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SUMMARYWe consider robust ensemble-based multi-objective optimization using a hierarchical switching algorithm for combined long-term and short term water flooding optimization. We apply a modified formulation of the ensemble gradient which results in improved performance compared to earlier formulations. We also apply multi-dimensional scaling to visualize projections of the high-dimensional search space, to aid in understanding the complex nature of the objective function surface and the performance of the optimization algorithm. This provides insights into the quality of the gradient, and confirms the presence of ridges in the objective function surface which can be exploited for multi-objective optimization. We used a 18553-gridblock reservoir model of a channelized reservoir with 4 producers and 8 injectors. The controls were the flow rates in the injectors, and the long-term and short-term objective functions were undiscounted net present value (NPV) and highly discounted (25%) NPV respectively. We achieved an increase of 15.2% in the secondary objective for a decrease of 0.5% in the primary objective, averaged over 100 geological realizations. The total number of reservoir simulations was around 20000, which indicates the potential to use the ensemble optimization method for robust multi-objective optimization of medium-sized reservoir models.

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Section: Different Gradient Formulationsmentioning

confidence: 99%

Section: Different Gradient Formulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust Ensemble-based Multi-objective Optimization

et al. 2014

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“…It has been demonstrated that significant scope exists for improved reservoir management through the use of numerical optimization methods in conjunction with reservoir simulation models (Peters 2011). While the focus so far has primarily been on water flooding optimization, polymer injection optimization (Raniolo et al 2013) and optimization under gas coning conditions (Hasan et al 2013) have also been explored.…”

Section: Introductionmentioning

confidence: 99%

A Theoretical look at Ensemble-Based Optimization in Reservoir Management

2015

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Ensemble-based optimization has recently received great attention as a potentially powerful technique for life-cycle production optimization, which is a crucial element of reservoir management. Recent publications have increased both the number of applications and the theoretical understanding of the algorithm. However, there is still ample room for further development since most of the theory is based on strong assumptions. Here, the mathematics (or statistics) of Ensemble Optimization is studied, and it is shown that the algorithm is a special case of an already well-defined natural evolution strategy known as Gaussian Mutation. A natural description of uncertainty in reservoir management arises from the use of an ensemble of history-matched geological realizations. A logical step is therefore to incorporate this uncertainty description in robust life-cycle production optimization through the expected objective function value. The expected value is approximated with the mean over all geological realizations. It is shown that the frequently advocated strategy of applying a different control sample to each reservoir realization delivers an unbiased estimate of the gradient of the expected objective function. However, this procedure is more variance prone than the deterministic strategy of applying the entire ensemble of perturbed control samples to each reservoir model realization. In order to reduce the variance of the gradient estimate, an importance sampling algorithm is proposed and tested on a toy problem with increasing dimensionality.

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“…Reviewing recent studies evaluating the economics of polymer flooding it can be concluded that OPEX described above is generally underestimated (Alkhatib, 2015;AlSofi and Blunt, 2011;Behr, Olie, Visser & Leonhardt, 2013;Botechia, Correia & Schiozer, 2016;Mogollón, Tillero, Gutiérrez & Luján, 2016;Raniolo, S., Dovera, L., Cominelli, A., Callegaro, C., and Masserano, F., 2013;Sieberer et al, 2016). Mogollón and Lokhandwala (2013) presented an example of polymer flood economics using a broad range of costs to potentially cover high OPEX based on a probabilistic approach.…”

Section: Summary Discussionmentioning

confidence: 99%

Historical and recent observations in polymer floods: An update review

Manrique¹,

Ahmadi²,

Samani³

2017

CT&F Cienc. Tecnol. Futuro

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Polymer flooding has been the most widely used chemical enhanced oil recovery (EOR) method. The experience gained over the past decades from laboratory studies to project design and field implementation has been well documented in the literature. The main objectives of this paper are to evaluate recent observations of polymer floods that report injection rates leading to pressure values above the formation fracture pressure (FFP), high polymer production, formation of tight emulsions and/or productivity losses.Based on this review, it can be concluded that no direct evidence exists to support that injecting polymer above the FFP will lead to more polymer production. However, uncertainties associated with the estimation of fracture propagation/dimensions using pressure Fall-Off Tests (FOT) still remain. High polymer production, other than severe channeling, is generally reported in large scale/commercial projects. The impact of oil geochemistry/ composition and water salinity on oil-water-polymer emulsions is commonly overlooked in polymer flood studies. The formation of in-situ emulsions can also explain the injectivity and/or productivity reduction and well test interpretation (i.e. FOT) reported in polymer floods. It was also identified that the OPEX (Operational Expenditures) associated with oil-water separation in the presence of polymer and productivity losses (i.e. workovers, stimulation costs) are generally underestimated. Finally, this review is expected to contribute with the planning, design and implementation of future polymer flood pilots and field expansions. OBSERVACIONES HISTÓRICAS Y RECIENTES EN INYECCIÓN DEPOLÍMEROS: REVISIÓN ACTUALIZADA. OBSERVAÇÕES HISTÓRICAS E RECENTES DE INJEÇÃO DE POLÍMEROS:REVISÃO ACTUALIZADA. EDUARDO MANRIQUE et. al. 18 L a inyección de polímeros es el método químico de recobro mejorado con mayor número de implementaciones a escala de campo. La experiencia adquirida en las últimas décadas desde estudios de laboratorio hasta el diseño e implementación de campo ha sido bien documentada en la literatura. El objetivo principal de este trabajo es evaluar observaciones recientes de proyectos de inyección de polímero reportando tasas de inyección por encima de la presión de fractura de la formación, alta producción de polímero, formación de emulsiones viscosas y/o pérdidas de productividad.Basados en esta revisión, se puede concluir de que no existen evidencias directas de que la inyección de polímero a tasas que impliquen superar la presión de fractura induzcan a una mayor producción de polímeros. Sin embargo, existen incertidumbres relacionadas con la estimación de las dimensiones y propagación de fracturas utilizando pruebas de caídas de presión (FOT). La alta producción de polímero, por razones diferentes a canalizaciones severas, generalmente se reportan en proyectos a escala comercial. Por otra parte, el impacto de la composición y geoquímica del crudo y de la salinidad del agua en la formación de emulsiones agua:petróleo:polímero ha sido subestimado en estudios de in...

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History Match and Polymer Injection Optimization in a Mature Field Using the Ensemble Kalman Filter

Cited by 28 publications

References 12 publications

Robust Ensemble-based Multi-objective Optimization

Robust Ensemble-based Multi-objective Optimization

A Theoretical look at Ensemble-Based Optimization in Reservoir Management

Historical and recent observations in polymer floods: An update review

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