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A multi-chamber, finite-difference dynamic model assumed pore-scale reservoir properties and replicated laboratory processes to determine oil-water transition zone characteristics: (1) imbibition residual oil saturation to water flood (distributed as a function of rock properties); (2) imbibition oil-water relative permeability (according to both steady-state and unsteady-state calculations); and, (3) microscopic oil recovery factor as a function of height above free water level. A priori, scaled capillary pressure hysteresis and segregated flow conditions governed pore-scale flow behaviour (initial mobile saturation scaled 0-1) assuming a pipeline network analogue. Although an oil-water system was modelled the process could be extended to other fluid phases. The dynamic model was divided into five chambers replicating two experiments. Flow between chambers was regulated by transmissibility multipliers (open/shut). Replicating a core displacement experiment, an oil source rock "drained" (flooded) the central core chamber to form the oil-water transition zone; water then imbibed into the core chamber displacing mobile oil into a shallower effluent chamber; capillary pressure hysteresis defined the imbibition residual oil saturation to water flood. In a second experiment, the central core chamber was subdivided into zones, each comprising five model layers, and the imbibition oil-water relative permeability was determined by flooding the quiesced core chamber situated between high/low-pressure chambers (source/sink). Both steady-state and unsteady-state relative permeability were determined across the oil-water transition zone. The Digital Core Laboratory (DCL) determined the distribution of imbibition residual oil saturation as a function of: wettability assumption; rock properties; and, proximity to the free water level. For a range of wettability assumptions, imbibition oil-water relative permeability was determined across the transition zone, on a zonal basis, from top core chamber (top reservoir) down to the free water level. Summary of Results: (1) The imbibition residual oil saturation (ISorw) decreased with depth toward the free water level, while the drainage irreducible water saturation (Swir) increased with depth; (2) ISorw was found to be strongly influenced by the wettability assumption, contrasting with the uniformity of Swir; (3) Microscopic oil recovery factor was determined across the transition zone as a function of both proximity to the free water level and the wettability assumption; except for the oil-wet case, microscopic oil recovery factor increased with depth toward the free water level. The novel approach was the multi-chambered design of the finite difference model forming a Digital Core Laboratory (DCL). Tuning the model to a Special Core Analysis (SCAL) data set, with the objective of filling SCAL data gaps, is expected to be one application.
A multi-chamber, finite-difference dynamic model assumed pore-scale reservoir properties and replicated laboratory processes to determine oil-water transition zone characteristics: (1) imbibition residual oil saturation to water flood (distributed as a function of rock properties); (2) imbibition oil-water relative permeability (according to both steady-state and unsteady-state calculations); and, (3) microscopic oil recovery factor as a function of height above free water level. A priori, scaled capillary pressure hysteresis and segregated flow conditions governed pore-scale flow behaviour (initial mobile saturation scaled 0-1) assuming a pipeline network analogue. Although an oil-water system was modelled the process could be extended to other fluid phases. The dynamic model was divided into five chambers replicating two experiments. Flow between chambers was regulated by transmissibility multipliers (open/shut). Replicating a core displacement experiment, an oil source rock "drained" (flooded) the central core chamber to form the oil-water transition zone; water then imbibed into the core chamber displacing mobile oil into a shallower effluent chamber; capillary pressure hysteresis defined the imbibition residual oil saturation to water flood. In a second experiment, the central core chamber was subdivided into zones, each comprising five model layers, and the imbibition oil-water relative permeability was determined by flooding the quiesced core chamber situated between high/low-pressure chambers (source/sink). Both steady-state and unsteady-state relative permeability were determined across the oil-water transition zone. The Digital Core Laboratory (DCL) determined the distribution of imbibition residual oil saturation as a function of: wettability assumption; rock properties; and, proximity to the free water level. For a range of wettability assumptions, imbibition oil-water relative permeability was determined across the transition zone, on a zonal basis, from top core chamber (top reservoir) down to the free water level. Summary of Results: (1) The imbibition residual oil saturation (ISorw) decreased with depth toward the free water level, while the drainage irreducible water saturation (Swir) increased with depth; (2) ISorw was found to be strongly influenced by the wettability assumption, contrasting with the uniformity of Swir; (3) Microscopic oil recovery factor was determined across the transition zone as a function of both proximity to the free water level and the wettability assumption; except for the oil-wet case, microscopic oil recovery factor increased with depth toward the free water level. The novel approach was the multi-chambered design of the finite difference model forming a Digital Core Laboratory (DCL). Tuning the model to a Special Core Analysis (SCAL) data set, with the objective of filling SCAL data gaps, is expected to be one application.
Measurement of Special Core Analysis (SCAL) parameters is a costly and time-intensive process. Some of the disadvantages of the current techniques are that they are not performed in-situ, and can destroy the core plugs, e.g., mercury injection capillary pressure (MICP). The objective of this paper is to introduce and investigate the emerging techniques in measuring SCAL parameters using Nuclear Magnetic Resonance (NMR) and Artificial Intelligence (Al). The conventional methods for measuring SCAL parameters are well understood and are an industry standard. Yet, NMR and Al - which are revolutionizing the way petroleum engineers and scientists describe rock/fluid properties - have yet to be utilized to their full potential in reservoir description. In addition, integration of the two tools will open a greater opportunity in the field of reservoir description, where measurement of in-situ SCAL parameters could be achieved. This paper shows the results of NMR lab experiments and Al analytics for measuring capillary pressures and permeability. The data set was divided into 70% for training and 30% for validation. Artificial Neural Network (ANN) was used and the developed model compared well with the permeability and capillary pressure data measured from the conventional methods. Specifically, the model predicted permeability 10% error. Similarly, for the capillary pressures, the model was able to achieve an excellent match. This active research area of prediction of capillary pressure, permeability and other rock properties is a promising emerging technique that capitalizes on NMR/AI analytics. There is significant potential is being able to evaluate wettability in-situ. Core-plugs undergoing Amott-Harvey experiment with NMR measurements in the process can be used as a building block for an NMR/AI wettability determination technique. This potential aspect of NMR/AI analytics can have significant implications on field development and EOR projects The developed NMR-Al model is an excellent start to measure permeability and capillary pressure in-situ. This novel approach coupled with ongoing research for better handling of in-situ wettability measurement will provide the industry with enormous insight into the in-situ SCAL measurements which are currently considered as an elusive measurement with no robust logging technique to evaluate them in-situ.
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