Comprehensive characterization investigation of multiple time-varying rock-fluid properties in waterflooding development

Journal of Energy Resources Technology ◽

10.1115/1.4052166 ◽

2021 ◽

pp. 1-18

Author(s):

Jingqi Lin ◽

Ruizhong Jiang ◽

Zeyang Shen ◽

Qiong Wang ◽

Yongzheng Cui ◽

...

Keyword(s):

History Matching ◽

Absolute Permeability ◽

Multiple Time ◽

Time Varying ◽

Reservoir Model ◽

Oil Viscosity ◽

Fluid Properties ◽

Black Oil Model ◽

Comprehensive Characterization

Abstract In this paper, the characterization parameter ‘effective displacement flux’ is employed to describe the flushing intensity and a new numerical simulator in which the rock-fluid properties considered functions of the effective displacement flux is developed based on the black oil model. Additionally, a conceptual reservoir model is established to validate the effective characterization of the time-varying mechanisms: the time-varying oil viscosity can characterize the viscous fingering of the water phase the time-varying absolute permeability can present the aggravation of reservoir heterogeneity, the alteration of wettability is characterized with the time-varying relative permeability, and the ultimate recovery will increase with the combined effect of all three time-varying factors. Eventually, the new simulator is applied to the simulation of an actual waterflooding reservoir to illustrate the assistance in history matching. The simulation results of our simulator can readily match the history data, which proves that the consideration of comprehensive time-varying rock-fluid properties can significantly improve the accuracy during the numerical simulation of waterflooding reservoirs.

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Comprehensive Characterization of Airship Response to Wind and Time Varying Mass

AIAA Atmospheric Flight Mechanics Conference ◽

10.2514/6.2010-7626 ◽

2010 ◽

Cited By ~ 2

Author(s):

Jayme Waishek ◽

Atilla Dogan ◽

Yasmina Bestaoui

Keyword(s):

Time Varying ◽

Varying Mass ◽

Comprehensive Characterization

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Multiresolution Grid Connectivity-Based Transform for Efficient History Matching of Unconventional Reservoirs

SPE Journal ◽

10.2118/199368-pa ◽

2020 ◽

Vol 25 (04) ◽

pp. 1895-1915 ◽

Cited By ~ 1

Author(s):

Hyunmin Kim ◽

Akhil Datta-Gupta

Keyword(s):

History Matching ◽

Basis Functions ◽

Unconventional Reservoirs ◽

Hydraulic Fractures ◽

Reservoir Model ◽

Fracture Properties ◽

Data Resolution ◽

Matrix Properties ◽

The Matrix

Summary Proper characterization of heterogeneous rock properties and hydraulic fracture parameters is essential for optimization of well spacing and reliable estimation of estimated ultimate recovery (EUR) in unconventional reservoirs. High resolution characterization of matrix properties and complex fracture parameters require efficient history matching of well production and pressure response. We propose a novel reservoir model parameterization method to reduce the number of unknowns, regularize the ill-posed problem, and enhance the efficiency of history matching of unconventional reservoirs. The proposed method makes a low-rank approximation of the spatial distribution of reservoir properties taking into account the varying model resolution of the matrix and hydraulic fractures. Typically, hydraulic fractures are represented with much higher resolution through local grid refinements compared to the matrix properties. In our approach, the spatial property distribution of both matrix and fractures is represented using a few parameters via a linear transformation with multiresolution basis functions. The parameters in transform domain are then updated during model calibrations, substantially reducing the number of unknowns. The multiresolution basis functions are constructed by using Eigen-decomposition of an adaptively coarsened grid Laplacian corresponding to the data resolution. Higher property resolution at the area of interest through the adaptive resolution control while keeping the original grid structure improves quality of history matching, reduces simulation runtime, and improves the efficiency of history matching. We demonstrate the power and efficacy of our method using synthetic and field examples. First, we illustrate the effectiveness of the proposed multiresolution parameterization by comparing it with traditional methods. For the field application, an unconventional tight oil reservoir model with a multistage hydraulic fractured well is calibrated using bottomhole pressure and water cut history data. The hydraulic fractures as well as the stimulated reservoir volume (SRV) near the well are represented with higher grid resolution. In addition to matrix and fracture properties, the extent of the SRV and hydraulic fractures are also adjusted through history matching using a multiobjective genetic algorithm. The calibrated ensemble of models are used to obtain bounds of production forecast. Our proposed method is designed to calibrate reservoir and fracture properties with higher resolution in regions that have improved data resolution and higher sensitivity to the well performance data, for example the SRV region and the hydraulic fractures. This leads to a fast and efficient history matching workflow and enables us to make optimal development/completion plans in a reasonable time frame.

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