Widespread application of 3D geological modeling in oil and gas field development practices resulted in substantiation of the transition from the traditional concept of "absolute pore space?? to the concept of "effective pore space??. This could be achieved with the geophysical and well logging data interpretation algorithms and procedures focused on the determination of reservoirs dynamic characteristics with high vertical resolution and based on principles of adaptability and petrophysical invariance. The adaptive log data interpretation technology provides analytical relations between log interpretative parameters and reservoir rocks properties in the generalized form. Proposed interpretative algorithms are implemented in the geological modeling software package and combined with standard geological modeling procedures to develop the three-dimensional distribution of reservoir properties. Adaptive petrophysical models make possible the quantitative estimation of effective porosity and effective/phase/relative permeability. Formation parameters, which characterize the content of bound water in the framework and cement, maximum total porosity and effective porosity. Dependencies between effective porosity and effective permeability are estimated according to outcomes of petrophysical modeling. Effective porosity is calculated with the interpretation of standard log data. The distribution of reservoir properties in three-dimensional space is carried out with geostatistical simulation techniques. Application of effective porosity for prediction of relative permeability and capillary pressures with log data was realized as an important task for field development design. The test of the proposed technology is conducted on a large number of wells worldwide (Western and Eastern Siberia, Caspian region, Middle East, Alaska, etc.). Formations consist of clastic fine-grained sandstones with cement and framework complex mineral composition. Application of proposed technology in geological modeling software packages represents an innovative direction of geological information technologies. It does not require any special capital expenditure with a significant economy of forces and operational time.
The characterization of the fluid-flow properties in biogenically altered formations is a key for successful exploration campaigns. This study assessed reservoir quality and evaluated permeability of the biogenically-modified Cretaceous carbonate section in Saudi Arabia. When dealing with these bioturbated carbonates, characterization of sedimentary heterogeneities is often overprinted by the complex spatial geometries of burrows. The high-resolution 3D X-ray microscopy imaging and analysis of these bioturbated sections lead to a better understanding of the interconnectivity between permeable burrows and tight matrix. The analysis deploys multiscale imaging from whole core to sub-micron scale. The coarse imaging at 20-50 microns resolution helped to identify bioturbated sections to select samples for higher resolution tomography. The 3D sample tomograms were segmented to define burrows and matrix distributions, where samples were extracted for thin-sections, scanning electronic microscopy (SEM) and mercury injection capillary pressure (MICP) analyses to refine the pore sizes and rock types. The analysis showed an intricate, highly connected, mixed horizontal and inclined burrow system dominated by Thalassinoides. Intergranular porosity, associated with the fill of Thalassinoides, constitutes a mechanism for permeability enhancement in a tight matrix. Increased permeability is associated with higher dolomite content that might be used as a sweet spot identifier from wireline logs.
The adaptive technology of log data interpretation provides heterogeneous reservoirs evaluation in case of framework and clayey cement polymineral composition, notably clastic reservoir rocks. Values of apparent and total porosity are informativeless for such reservoirs. Petrophysical invariant (normalized effective or dynamic porosity) is applied as an interpretative parameter. It characterizes static reservoir properties as well as filtration properties. Proposed petrophysical models use minimum number of physically measureable variables (from core data or from prior petrophysical information about simulated object in core data shortage conditions), which tune interpretation algorithms with high accuracy description of reservoir rocks properties diversity. Effective porosity is estimated using adaptive interpretation of logging data. This procedure is conducted according to characteristic responses derived from each standard log (spontaneous potential, sonic, natural radioactivity, density and neutron logs). Then heterogeneous reservoir properties transfer to geological model. Adaptive technology advantages include following: the technology could be applied for rapid interpretation of log data large volumes; effective porosity could be calculated for complex polymineral reservoirs in absolute units without "reference beds"; the technology provides adaptive tuning on lithological and petrochemical conditions of the particular reservoir in situ, including the wellbore construction influence; it could be used for the old data re-interpretation. Thus, the adaptive log data interpretation practical importance is due to the radical reduction of the error sources number inherent to the conventional technology. The effective porosity prediction from standard log data is an important link in the chain of modern exploration and production activities. Its implementation determines how accurate and detailed a geological model will be and it definitely affects both reserves estimation and the design of a field development plan.
This paper is devoted to the development of capillary pressure and relative/phase permeabilities petrophysical models for different lithotypes of granular reservoirs. Proposed models describe core analysis data better than widely used models (Brooks-Corey model, J-function, Tiksie model, Burdine model). Models are verified on the representative core samples collections (over 200 samples) -sandstones with complex mineral composition from different fields worldwide (Western & Eastern Siberia, Caspian region, Middle East, Alaska). For described formations effective porosity is single value reservoir indicator. Control parameters of developed models have strong correlations with reservoir properties. Effective and dynamic porosities, hydrocarbon saturation in effective pore space (effective hydrocarbon saturation) determined with well logging data provide evaluation of relative/phase permeability values and hydrocarbon distribution in transition zones. The adaptive well logging data interpretation technology is applied for effective porosity and saturation determination. This technology is based on the effective porosity petrophysical model of granular reservoirs. It provides prediction of effective porosity values in reservoir conditions with standard well log data interpretation (spontaneous potential log, formation density log, gammaray log, neutron log and sonic log). The adaptive technique of resistivity log data interpretation is established for determination of effective hydrocarbon saturation. Proposed models of capillary pressure and relative/phase permeabilities are used in dynamic reservoir properties prediction algorithms with well logging data. Dynamic properties are transferred in digital geological and hydrodynamic models for reservoir development process simulation. Fluid filtration and mass transfer processes are the basis of the oilfields development for reservoirs with complex structure. Obtained results are applied for fluid filtration processes modeling and reservoir development technology design.
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.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.