Abstract
Meandering river reservoirs are essential targets for hydrocarbon exploration, although their characterization can be complex due to their multiscale heterogeneity. Multipoint geostatistics (MPS) has advantages in establishing reservoir architectural models. Training image (TI) stationarity is the main factor limiting the uptake of MPS modeling algorithms in subsurface modeling. A modeling workflow was designed to reproduce the distribution of heterogeneities at different scales in the Miocene Minghuazhen Formation of the Yangerzhuang Oilfield in the Bohai Bay Basin. Two TIs are established for different scales of architecture. An initial unconditional model generated with a process-based simulation method is used as the megascale TI. The mesoscale TI of the lateral accretion layers is characterized by an uneven spatial distribution of mudstone in length, thickness, frequency, and spacing. Models of different scales are combined by the probability cube obtained by lateral accretion azimuthal data as an auxiliary variable. Moreover, the permeability function sets are more suitable than the porosity model for collaboratively simulating the permeability model. Model verification suggests this workflow can accurately realize the multiscale stochastic simulation of channels, point bars, and lateral accretion layers of meandering fluvial reservoirs. The produced model conforms geologically realistically and enables the prediction of interwell permeability variation to enhance oil recovery.
Highlights
Meandering river deposits create significant hydrocarbon reservoirs
Its heterogeneity in fluid flow occurs within point bars, and it is related to the development degree of lateral accretion layers and affects the variation of porosity and permeability [9, 10]
Previous studies have focused on the sedimentary structure and lithologic heterogeneity in fluvial depositional systems, but little attention has been focused on the heterogeneity at the Geofluids architectural element scale, especially the heterogeneity variation in model parameters [11,12,13,14]
Summary
Meandering river deposits create significant hydrocarbon reservoirs. it is challenging to describe the geometric shapes of architectural elements since these reservoirs are characterized by fast planar phase change, complex sand body stacking, and substantial heterogeneity [1, 2]. The traditional modeling method of sequential indicator simulated (SIS) matches point data (wells) based on only an algorithm without regard to the information on sedimentary process [15,16,17,18] This method commonly produces unrealistic heterogeneous architectural model elements and overestimates the connectivity of these elements [19]. Modeling based on MPS captures objects by considering more than two points (cells) simultaneously and reproduces complex morphologies, such as those of the deposits of meandering rivers (e.g., point bars and channel fills) and nonlinear spatial correlations [26]. A multiscale reservoir architectural modeling workflow is studied, including meandering fluvial channels and point bars with lateral accretion elements. The variation function of rock permeability was further used to improve the modeling accuracy
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
