An Improvement on Modeling of Forced Gravity Drainage in Dual Porosity Simulations Using a New Matrix-Fracture Transfer Function

Samimi, Soodeh; Masihi, Mohsen; Gerami, Shahab; Ganjeh-Ghazvini, Mostafa

doi:10.1007/s11242-012-9999-7

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…Several different methods have been proposed to model a fracture in fractured media, and the most common method is using shape factor and transfer functions in heterogeneous and fractured reservoir simulation. [41][42][43][44] Other methods include recovery curves [45] and multiple interacting continuum (MINC). [23] The MINC method has been used to provide an accurate representation of matrix-fracture flow.…”

Section: Fracture Modellingmentioning

confidence: 99%

Free fall and controlled gravity drainage processes in fractured porous media: Laboratory and modelling investigation

2015

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Gravity drainage is known to be one of the most effective methods for oil recovery in fractured reservoirs. In this study, both free fall and controlled gravity drainage processes were studied using a transparent fractured experimental model, followed by modelling using commercial CFD software. The governing equations were employed based on the Darcy and mass conservation laws and partial pressure formulation. Comprehensive examination was done on variables such as fluid saturation, velocity, and pressure distribution in the matrix and fracture, as well as fluid front level and production rate. Additionally, effects of the model parameters on the gravity drainage performance were investigated. The experimental results confirmed a higher oil recovery factor at breakthrough for lower production rates in the controlled gravity drainage. Satisfactory agreement was observed between the experimental data and modelling results.

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Section: Fracture Modellingmentioning

confidence: 99%

Free fall and controlled gravity drainage processes in fractured porous media: Laboratory and modelling investigation

2015

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“…The second group of approaches, denoted as dual porosity and/or dual permeability model, rests on a conceptual picture according to which the system can be viewed as formed by a collection of continua characterized by differing properties and coexisting in space. In this context, fractures are considered as a continuum system overlapped to a less permeable porous medium (e.g., Samimi et al 2012;Geiger et al 2013;Maier and Geiger 2013;Tecklenburg et al 2016;Hui et al 2018). These mathematical models rely on transfer functions to evaluate exchange rates between the two continua, i.e., the porous matrix and the fractures (e.g., Al-Kobaisi et al 2009;Ramirez et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Sensitivity-based Parameter Calibration of Single- and Dual-continuum Coreflooding Simulation Models

et al. 2022

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Our study is keyed to the development of a viable framework for the stochastic characterization of coreflooding simulation models under two- and three-phase flow conditions taking place within a core sample in the presence of preferential flow of the kind that can be associated with the presence of a system of fractures. We do so considering various modeling strategies based on (spatially homogeneous or heterogeneous) single- and dual-continuum formulations of black-oil computational models and relying on a global sensitivity-driven stochastic parameter calibration. The latter is constrained through a set of data collected under a water alternating gas scenario implemented in laboratory-scale coreflooding experiments. We set up a collection of Monte Carlo (MC) numerical simulations while considering uncertainty encompassing (a) rock attributes (i.e., porosity and absolute permeability), as well as (b) fluid–fluid/ fluid–solid interactions, as reflected through characteristic parameters of relative permeability and capillary pressure formulations. Modern moment-based global sensitivity indices are evaluated on the basis of the MC model responses, with the aim of (i) quantifying sensitivity of the coreflooding simulation results to variations of the input uncertain model parameters and (ii) assessing the possibility of reducing the dimensionality of model parameter spaces. We then rest on a stochastic inverse modeling approach grounded on the acceptance–rejection sampling (ARS) algorithm to obtain probability distributions of the key model parameters (as identified through our global sensitivity analyses) conditional to the available experimental observations. The relative skill of the various candidate models to represent the system behavior is quantified upon relying on the deviance information criterion. Our findings reveal that amongst all tested models, a dual-continuum formulation provides the best performance considering the experimental observations available. Only a few of the parameters embedded in the dual-continuum formulation are identified as major elements significantly affecting the prediction (and associated uncertainty) of model outputs, petrophysical attributes and relative permeability model parameters having a stronger effect than parameters related to capillary pressure.

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“…Many different techniques have been developed for this purpose such as steam flooding [2][3][4][5][6], polymer flooding [2,[7][8][9][10][11][12][13], and gas injection [2,14,15], among others. In this paper, EOR is defined as the injection of gas, steam, surfactants, or other chemicals into the reservoir to improve reservoir productivity.…”

Section: Introductionmentioning

confidence: 99%

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

et al. 2017

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This paper presents a review of history matching and oil field development optimization techniques with a focus on optimization algorithms. History matching algorithms are reviewed as a precursor to production optimization algorithms. Techniques for history matching and production optimization are reviewed including global and local methods. Well placement, well control, and combined well placement-control optimization using both secondary and tertiary oil production techniques are considered. Secondary and tertiary recovery techniques are commonly referred to as waterflooding and enhanced oil recovery (EOR), respectively. Benchmark models for comparison of methods are summarized while other applications of methods are discussed throughout. No single optimization method is found to be universally superior. Key areas of future work are combining optimization methods and integrating multiple optimization processes. Current challenges and future research opportunities for improved model validation and large scale optimization algorithms are also discussed.

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An Improvement on Modeling of Forced Gravity Drainage in Dual Porosity Simulations Using a New Matrix-Fracture Transfer Function

Cited by 6 publications

References 16 publications

Free fall and controlled gravity drainage processes in fractured porous media: Laboratory and modelling investigation

Free fall and controlled gravity drainage processes in fractured porous media: Laboratory and modelling investigation

Sensitivity-based Parameter Calibration of Single- and Dual-continuum Coreflooding Simulation Models

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

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