Techniques for Effective Simulation, Optimization, and Uncertainty Quantification of the In-situ Upgrading Process

Abstract

Strongly temperature-dependent compositional flow and transport, chemical reactions, delivery of energy into the subsurface through downhole heaters, and complex natural fracture architecture render the dynamic modeling of In-situ Upgrading Process (IUP) a computationally challenging endeavor for carbonate extra-heavy oil resources. Economic performance indicators for such recovery methods can be considerably enhanced via simulation or simulation-based proxy models within an optimization framework (e.g., maximizing Net Present Value through achieving an optimal compromise between hydrocarbon recovery and the number of heater wells). The IUP is endowed with uncertain subsurface parameters as in the case of other recovery mechanisms. The number of subsurface uncertainties is especially large and the impacts of these uncertainties are intricate when IUP is applied to a complex naturally-fractured carbonate reservoir. Simulation results must reflect the impacts of these uncertainties; hence they should always deliver "expected-value production functions" and their attached uncertainty ranges, in short, the "error bars". Both the optimization and the uncertainty quantification workflows require (typically multiple) multi-scenario simulations, and are therefore very compute intensive.We describe our recent developments in simulation techniques, optimization algorithms, tool capabilities, and highperformance computing protocols that in unison form a massively parallel simulation/optimization/uncertainty-quantification workflow, in which it is almost equally easy to produce recovery time-functions with an attached uncertainty range, as it is to run a single simulation. Uncertainties are integral part of the simulation models in our dynamic modeling workflow. Our inhouse simulation platform supports various optimization and uncertainty quantification methods, such as conventional as well as robust optimization using a novel Simultaneous Perturbation and Multivariate Interpolation technique, Experimental Design, and Monte Carlo simulation, that can be linked together through a unified script-based interface, to carry out optimization in the presence of subsurface uncertainties and to quantify the impact of these uncertainties on simulation results. Application of our massively parallel dynamic modeling workflow is illustrated on a proprietary IUP recovery method for a complex naturally fractured extra-heavy oil (bitumen) reservoir as example. After briefly explaining these recovery processes and the modeling approach, we show the techniques (including their accompanying application results) that (1) notably accelerate the (single-model) simulation process, (2) effectively identify the predominant subsurface uncertainties, (3) rapidly optimize heater-producer patterns under the influence of predominant subsurface uncertainties, and (4) efficiently compute expected-value production functions with error bars.

Parallel black-box optimization of expensive high-dimensional multimodal functions via magnitude

“…14 One technique that we have not mentioned is the distributed quasi-Newton algorithm of (Gao et al, 2020) (see also (Gao et al, 2021)), which is designed for extremely expensive situations on the order of ≥ 1 day/evaluation. This and related algorithms such as SPMI do not appear to be publically available and/or comprehensively benchmarked in the literature: indeed, SPMI is described in (Alpak et al, 2013) as "an in-house massively parallel mixed integer and real variable optimization tool" (emphasis added).…”

Simulação Numérica de Escoamento não Isotérmico em Reservatório de Óleo com Poços Aquecedores

“…Considera-se, portanto, a utilização de elementos de aquecimento postos dentro do reservatório, de forma a realizar o chamado In-Situ Upgrading Process (IUP) [11,15], no qual através do aquecimento da jazida altera-se as propriedades dos uidos. Não é empregado nenhum tipo de injeção de uido aquecido, mas sim a introdução de poços aquecedores (heater wells) no reservatório [11].…”

“…com as incógnitas sendo avaliadas em i, j e no tempo n + 1, com (V b ) i,j = (∆x∆y) i,j L z para as Eqs. (13), (14) e (15), e introduziu-se as novas variáveis Introduz-se, em seguida, a transmissibilidade na direção x como sendo dada por…”

The application of outcrop analogues in geological modelling: a review, present status and future outlook

“…For this purpose, an accurate characterization of the connectivity of adjacent sandbodies is required that incorporates the effects of baffles or barriers between the major sandstone elements formed by fine-grained facies. Modelling studies (Larue & Hovadik 2006;Alpak et al 2013) suggest that such fine-grained barriers, if sufficiently common and laterally extensive, can significantly influence fluid flow. Such results have encouraged close examination and quantification of connectivity relationships within deep-water reservoir analogues.…”