Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
The initialization of a reservoir simulator calls for the populating of a three-dimensional dynamic grid-cell model using subsurface data and interrelational algorithms that have been synthesized to be fit for purpose. These prerequisites are rarely fully satisfied in practice. This paper sets out to strengthen initialization through four key thrusts, all of which seek to optimize the bridgehead between reservoir geoscience and reservoir engineering, and thereby maximize value from reservoir simulation. The first addresses representative data acquisition, which includes the key-well concept as a framework for the cost-effective incorporation of free-fluid porosity and permeability within an initialization database. The second concerns the preparation of these data and their products for populating the static and dynamic models. Important elements are dynamically conditioned net-reservoir cut-offs, recognition of primary flow units, and establishing interpretative algorithms at the simulator grid-cell scale for application over net-reservoir zones. The third thrust is directed at the internal consistency of capillary character, relative permeability properties and petrophysically-derived hydrocarbon saturations over net reservoir. This exercise is central to the simulation function and it is an integral component of hydraulic data partitioning. The fourth concerns the handling of formation heterogeneity and anisotropy, especially from the standpoint of directional parametric averaging and interpretative algorithms. These matters have been synthesized into a workflow for optimizing the initialization of reservoir simulators. In so doing, a further important consideration is the selection of the appropriate procedures that are available within and specific to different software packages. It is the authors’ experience that implementation of these thrusts has demonstrably enhanced the authentication of reservoir simulators through more readily attainable history matches with less required tuning. This outcome is attributed to a more systematic initialization process with a lower risk of artefacts. Of course, these benefits feed through to more assured estimates of ultimate recovery and, thence, hydrocarbon reserves.
The initialization of a reservoir simulator calls for the populating of a three-dimensional dynamic grid-cell model using subsurface data and interrelational algorithms that have been synthesized to be fit for purpose. These prerequisites are rarely fully satisfied in practice. This paper sets out to strengthen initialization through four key thrusts, all of which seek to optimize the bridgehead between reservoir geoscience and reservoir engineering, and thereby maximize value from reservoir simulation. The first addresses representative data acquisition, which includes the key-well concept as a framework for the cost-effective incorporation of free-fluid porosity and permeability within an initialization database. The second concerns the preparation of these data and their products for populating the static and dynamic models. Important elements are dynamically conditioned net-reservoir cut-offs, recognition of primary flow units, and establishing interpretative algorithms at the simulator grid-cell scale for application over net-reservoir zones. The third thrust is directed at the internal consistency of capillary character, relative permeability properties and petrophysically-derived hydrocarbon saturations over net reservoir. This exercise is central to the simulation function and it is an integral component of hydraulic data partitioning. The fourth concerns the handling of formation heterogeneity and anisotropy, especially from the standpoint of directional parametric averaging and interpretative algorithms. These matters have been synthesized into a workflow for optimizing the initialization of reservoir simulators. In so doing, a further important consideration is the selection of the appropriate procedures that are available within and specific to different software packages. It is the authors’ experience that implementation of these thrusts has demonstrably enhanced the authentication of reservoir simulators through more readily attainable history matches with less required tuning. This outcome is attributed to a more systematic initialization process with a lower risk of artefacts. Of course, these benefits feed through to more assured estimates of ultimate recovery and, thence, hydrocarbon reserves.
The initialization of a reservoir simulator calls for the populating of a three-dimensional dynamic grid-cell model using subsurface data and interrelational algorithms that have been synthesized to be fit for purpose. These prerequisites are rarely fully satisfied in practice. This paper sets out to strengthen initialization through four key thrusts. The first addresses representative data acquisition, which includes the key-well concept as a framework for the cost-effective incorporation of free-fluid porosity and permeability within an initialization database. The second concerns the preparation of these data and their products for populating the static and dynamic models. Important elements are dynamically-conditioned net-reservoir cut-offs, recognition of primary flow units, and establishing interpretative algorithms at the simulator grid-cell scale for application over net-reservoir zones. The third thrust is directed at the internal consistency of capillary character, relative permeability properties and petrophysically-derived hydrocarbon saturations over net reservoir. This exercise is central to the simulation function and it is an integral component of hydraulic data partitioning. The fourth concerns the handling of formation heterogeneity and anisotropy, especially from the standpoint of directional parametric averaging and interpretative algorithms. These matters have been synthesized into a workflow for optimizing the initialization of reservoir simulators. In so doing, a further important consideration is the selection of the appropriate procedures that are available within and specific to different software packages. The implementation of these thrusts has demonstrably enhanced the authentication of reservoir simulators through more readily attainable history matches with less required tuning. This outcome is attributed to a more systematic initialization process with a lower risk of artefacts. Of course, these benefits feed through to more assured estimates of ultimate recovery and thence hydrocarbon reserves.
Tight hydrocarbon reservoirs are a major unconventional reserve. To profitably develop such reserves, horizontal wells and multistage hydraulic fracturing techniques are applied to maximize the reservoir drainage areas and increase reservoir conductivity to the wellbores by creating flow channels in the tight reservoirs. Without in-depth studies that include reservoir characterization, field modeling, well test and production data analysis by a multidisciplinary team, reservoir properties cannot be reproduced and well performance cannot be represented to accurately forecast production. Overestimating or underestimating production rates creates tremendous loss for oil companies or operators. Integrated workflow combines multiple disciplines and professionals for specific projects. The target reservoir is in the central Jungger basin, northern China, which is a green field for tight oil reservoirs with an anticline structure, fault system and unconformity and stratigraphic traps. The paper presents the thorough reservoir characterization, systematic process and reference for a tight oil development plan. The high heterogeneity, low porosity, low permeability and production uncertainty in unconventional reservoirs sped up progress and investment in integrated workflow for reservoir development through risk quantification. This paper presents a systematic study of unconventional resource characteristics, and describes an integrated workflow for reservoir characterization and development of tight oil reservoirs in northwest China which combines geology, seismic, geostatistics, well logging and core data. The process and methodology comprises a geological study, a field geological model with reservoir characterization, petrophysical modeling, numerical well testing, hydraulic fracture modeling based on a geomechanical study and a field reservoir simulation study. Reservoir grid is refined to capture the effect of hydraulic fracture on well performance, calibrate model using well testing and history matching for examining model accuracy, and then finally production of post-fracturing is estimated. This paper also includes the details of sensitivity analysis proposed to address the critical uncertainties and strategy to enhance well deliverability such as well placement, half-fracture lengths, hydraulic fracturing stages and fracture conductivity. The workflow enables the feasibility of coupling multiple disciplines including geology, geophysics, geostatistics, petrophysics and reservoir engineering into an integrated platform for information sharing, project management and strategy using static and dynamic data while simultaneously checking and updating reservoir data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.