Probabilistic Forecasting of Horizontal Well Performance in Unconventional Reservoirs Using Publicly-Available Completion Data

Voneiff, G.W.; Sadeghi, Seyed Hamidreza; Bastian, P.A.; Wolters, B.C.; Jochen, J.E.; Chow, B.; Chow, King Lau; Gatens, M.

doi:10.2118/168978-ms

Cited by 12 publications

(2 citation statements)

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“…Reservoir management enables us to obtain the most favorable production scenario given the current information of the reservoir. However, proper reservoir management becomes challenging to be performed due to the intrinsic uncertainties and complexities associated with the reservoir properties (Voneiff et al, 2014). To this end, accurate results for reservoirs are obtained if fine grid discretization is induced into the model.…”

Section: Introductionmentioning

confidence: 99%

Fast Multiscale Reservoir Simulations With POD-DEIM Model Reduction

et al. 2016

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Summary We present a global/local model reduction for fast multiscale reservoir simulations in highly heterogeneous porous media. Our approach identifies a low-dimensional structure in the solution space. We introduce an auxiliary variable (the velocity field) in our model reduction that achieves a high compression of the model. This compression is achieved because the velocity field is conservative for any low-order reduced model in our framework, whereas a typical global model reduction that is based on proper-orthogonal-decomposition (POD) Galerkin projection cannot guarantee local mass conservation. The lack of mass conservation can be observed in numerical simulations that use finite-volume-based approaches. The discrete empirical interpolation method (DEIM) approximates fine-grid nonlinear functions in Newton iterations. This approach delivers an online computational cost that is independent of the fine-grid dimension. POD snapshots are inexpensively computed with local model-reduction techniques that are based on the generalized multiscale finite-element method (GMsFEM) that provides (1) a hierarchical approximation of the snapshot vectors, (2) adaptive computations with coarse grids, and (3) inexpensive global POD operations in small dimensional spaces on a coarse grid. By balancing the errors of the global and local reduced-order models, our new methodology provides an error bound in simulations. Our numerical results, by use of a two-phase immiscible flow, show a substantial speedup, and we compare our results with the standard POD-DEIM in a finite-volume setup.

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Section: Introductionmentioning

confidence: 99%

Fast Multiscale Reservoir Simulations With POD-DEIM Model Reduction

et al. 2016

View full text Add to dashboard Cite

show abstract

“…However, proper reservoir management becomes challenging to be performed due to the intrinsic uncertainties and complexities associated with the reservoir properties (Voneiff et al, 2014). To this end, accurate results for reservoirs are obtained if fine grid discretization is induced into the model.…”

Section: Introductionmentioning

confidence: 99%

Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction

Ghasemi¹,

Yang²,

Gildin³

et al. 2015

SPE Reservoir Simulation Symposium

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In this paper, we present a global-local model reduction for fast multiscale reservoir simulations in highly heterogeneous porous media with applications to optimization and history matching. Our proposed approach identifies a low dimensional structure of the solution space. We introduce an auxiliary variable (the velocity field) in our model reduction that allows achieving a high degree of model reduction. The latter is due to the fact that the velocity field is conservative for any low-order reduced model in our framework. Because a typical global model reduction based on POD is a Galerkin finite element method, and thus it can not guarantee local mass conservation. This can be observed in numerical simulations that use finite volume based approaches. Discrete Empirical Interpolation Method (DEIM) is used to approximate the nonlinear functions of fine-grid functions in Newton iterations. This approach allows achieving the computational cost that is independent of the fine grid dimension. POD snapshots are inexpensively computed using local model reduction techniques based on Generalized Multiscale Finite Element Method (GMsFEM) which provides (1) a hierarchical approximation of snapshot vectors (2) adaptive computations by using coarse grids (3) inexpensive global POD operations in a small dimensional spaces on a coarse grid. By balancing the errors of the global and local reduced-order models, our new methodology can provide an error bound in simulations. Our numerical results, utilizing a two-phase immiscible flow, show a substantial speed-up and we compare our results to the standard POD-DEIM in finite volume setup.

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A review of plug-and-perforate, ball-and-seat, and single-entry pinpoint fracturing performance in the unconventional montney reservoir

Jamaloei¹

2021

J Petrol Explor Prod Technol

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The Montney tight siltstone reservoir is a multi-stacked play, which covers a total area of 130,000 km2 along the Alberta–British Columbia border in Western Canada. Since the late 1990s, different fracturing methods and fluids have been tested in 4000-plus Montney wells to find the optimal fracturing method and fluid. The previous studies reviewing the performance of fracturing methods in Montney do not represent a holistic evaluation of these methods, owing to some limitations, including: (1) using a small sample size, (2) having a limited scope by focusing on a specific aspect of fracturing (method/fluid), (3) relying on data analytics approaches that offer limited subsurface insight, and (4) generating misleading results (e.g., on optimum fracturing method/fluid) through using disparate data that are unstructured and untrustworthy as a result of significant regional variations in true vertical depth (TVD), geological properties, fluid windows, completed lateral length, fracturing method/fluid/date, and drawdown rate management and choke size strategy. The present study eliminates these limitations by rigorously clustering 4000-plus Montney wells based on the TVD, fluid window, completed lateral length, fracturing method/fluid/date, and drawdown rate strategy to isolate the effect of each fracturing method by comparing each well’s production to that of its offsets, which use different fracturing methods but possess similar geology, fluid window, and TVD. With similar TVD, fracturing fluid, and completion date, wells completed with pinpoint fracturing method outperform their offsets completed with ball-and-seat and plug-and-perforate (PnP) fracturing methods. However, wells completed with ball-and-seat and PnP methods that outperform their offset pinpoint wells have either: (1) been fractured one to four years earlier than the pinpoint wells and/or (2) used energized oil-based fluid, hybrid fluid, and energized slickwater versus slickwater used in the pinpoint offsets. This suggests that the water-phase trapping is more severe in these pinpoint wells attributable to the use of slickwater. Previous studies often favored one specific fracturing method or fluid without highlighting these complex interplays between the type of fracturing method, fracturing fluid, completion date (regional depletion or well vintage), and the reservoir properties and hydrodynamics.

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Probabilistic Forecasting of Horizontal Well Performance in Unconventional Reservoirs Using Publicly-Available Completion Data

Cited by 12 publications

References 1 publication

Fast Multiscale Reservoir Simulations With POD-DEIM Model Reduction

Fast Multiscale Reservoir Simulations With POD-DEIM Model Reduction

Fast Multiscale Reservoir Simulations using POD-DEIM Model Reduction

A review of plug-and-perforate, ball-and-seat, and single-entry pinpoint fracturing performance in the unconventional montney reservoir

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