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Reservoir Characterization serves multiple disciplines. The prediction of Pore Pressure, Fracture Gradients, Reservoir Stresses, Wellbore Stability and Lithology Columns provides the drilling engineers with information needed to deliver a problem free wellbore. On the other hand, the evaluation of reservoir properties of porosity, pore structure, permeability and fluids' saturation provides the reservoir engineers with the information needed to build the dynamic model of a reservoir. The evaluation of the reservoir parameters behind casing such as fluids saturation provides both the production engineers and the petrophysicists with the tools required to optimize reservoir deliverability. This course will combine all these information in a simplified way to integrate all attendees from the different disciplines for optimum reservoir management.
The expanding solvent-steam-assisted gravity drainage (ES-SAGD) is a newly proposed thermal recovery technique showing promising efficiency in terms of a smaller steam-to-oil ratio and greater production rate to recover heavy oils and bitumen from oil-bearing formations, where a solvent is coinjected with the steam in the SAGD process. Numerical simulation of the ES-SAGD process requires reliable relative permeability data. The number of reported measurements of relative permeability involving bitumen systems is limited in the literature, mostly because of the experimental difficulties involved in such measurements. The relative permeability data sets for Canadian bitumen, in the presence of solvents, are simply not available in the open literature. The fluid-flow behavior of bitumen/water systems in the presence of solvent is an important matter that must be assessed before the implementation of any ES-SAGD process; therefore, the objective of the current study is to evaluate the impact of a light hydrocarbon solvent (n-hexane) on bitumen/water relative permeability under SAGD conditions. For this purpose, two-phase bitumen/water relative-permeability measurements were conducted in sandpacks over a wide range of temperatures from 70°C to 220°C using Athabasca bitumen, deionized water, and a light hydrocarbon solvent. A well-instrumented experimental setup was developed to perform the relative permeability measurements with the capability of applying confining pressure on the sand and measuring the pore-pressure profile with several intermediate pressure taps. Isothermal oil-displacement tests were carried out with solvent premixed with bitumen. The history-matching approach and Johnson-Bossler-Naumann (JBN) method were used to translate the oil displacement data into the relative-permeability curves. The results obtained with a solvent from this study and without any solvent reported in our previous study are compared to assess the solvent’s impact on relative permeability. In addition, the steady-state relative permeability was measured to assess the reliability of unsteady-state relative permeability. The interfacial tension (IFT) and contact-angle measurements using the same fluids were carried out to determine the fluid/fluid interaction and wettability state of the system under high-pressure/high-temperature (HP/HT) conditions.
The results of the present study confirmed that the two-phase diluted bitumen/water relative permeability is sensitive to temperature, especially in terms of the endpoint relative permeability to bitumen and water. Furthermore, adding normal hexane (below the asphaltene precipitation threshold) not only improves the displacement efficiency of water flooding because of the significant decrease in oil viscosity but also modifies the wettability and IFT of this system. At the same temperature, the two-phase oil/water relative permeability for bitumen/water systems is significantly different when the oil is diluted with the solvent. Also, the impact of solvent is more pronounced at lower temperatures. Furthermore, the consistency between the steady-state and unsteady-state relative permeability data proved that the effect of viscous fingering was small enough.
Methane hydrate in the porous medium is formed within the pores of the sediments. The presence of a porous medium enhanced the heat transfer, whereas the presence of a hydrate promoter could enhance the mass transfer between the liquid-gas interface. In this study, we have studied the effect of sediment particle size and type of promoter on the kinetics of the methane hydrate formation and dissociation in the combined system. Environment-friendly amino acids (L-valine, L-methionine & L-histidine) and surfactant Sodium dodecyl sulfate are used as a promoter with four different particle sizes (46.4-245 μm, 160-630μm, 480-1800μm, 1400-5000μm) silica sand. Isothermal experiments are carried out using 3000 ppm promoter concentration at 100 bar, 274.15°C using the rocking cell to investigate the induction time, gas uptake, hydrate saturation. Temperature is further lowered to 266.15K to investigate the dissociation behavior of methane hydrate to study the self-preservation effect in the combined system.
The experimental results show that induction time in the combined system decreases as a sediment particle size decreases. Gas uptake remained unchanged in the combined system by changing the sediment particle size. We also report similar formation kinetics of hydrophobic amino acids (L-valine, L- methionine) and SDS at four particle sizes. At similar hydrate saturation, SDS has displayed weaker self- preservation effects compare to a hydrophilic amino acid in the porous medium.
Results in this study, support the conclusion available through other studies at lower concentration (500 ppm) of SDS and provide additional information about formation behavior at higher concentration (3000 ppm) of SDS. Results collected in this research could be beneficial in the selection of environmentally friendly chemicals for rapid methane hydrate formation in sediments to be used either in laboratory studies or for natural gas storage and transportation.
Alyafei, Nayef (Texas A&M University at Qatar) | Bautista, Jerahmeel (Texas A&M University at Qatar) | Mari, Sahar (Texas A&M University at Qatar) | Khan, Talha (Texas A&M University at Qatar) | Seers, Thomas (Texas A&M University at Qatar)
We present a project-based learning prototype for visual analysis of petrophysical properties using 2D cross-sections and micro-models of porous media. Micro-computed Tomography (CT) scans are used to create the quasi-2D micro-models that are printed using Stereolithography (SLA) 3D printers to study petrophysical properties in porous media. The methodology involves obtaining 8 different cross-sections of rocks either from micro-CT scans or online libraries. 2D cross-sections are segmented into black and white binary images and then skeletonized to create quasi-2D models. The flow of oil and water in initially water saturated pores in the printed 2D models mimics the drainage and imbibition processes, respectively. High definition photography is used to capture still and dynamic photographs of flow processes. The binary images are used to analyze porosity and grain size distribution while the still and dynamic photographs are used to analyze fluid saturation and displacement efficiency. The images are analyzed using open source software where a systematic tutorial is provided. The primary outcome of this project is to improve the understanding of petrophysical concepts and 3D printing by the utilization of imagery to create porous media. This project has been tested in teaching and showed major improvements in students’ understanding of petrophysical concepts when compared to pre-project. The data and tutorials used in this project are made available for the community to use through a link in the paper.
The initial water saturation in a reservoir is important for both hydrocarbon volume estimation and distribution of multi-phase flow properties such as relative permeability. Often, a practical reservoir engineering approach is to relate relative permeability to flow property regions by binning of the initial water saturation. The rationale behind this approach is that initial water saturation is related to both the pore-throat radius distribution and the wettability of the rock, both of which impact relative permeability. However, pore-throat radius and wettability are usually not explicitly included in geomodel property modelling. Therefore, the saturation height model (SHM) should not only capture an average hydrocarbon pore volume (HCPV), but also reflect the underlying mechanisms from hydrocarbon migration history and its impact on initial water saturation distribution.
This work defines a new terminology, "excess water", for more precise classification of SHM-scenarios in reservoirs where multiple mechanisms have interacted and caused a complex water saturation distribution. The physical basis for drainage and imbibition transition zones connected to both regional and perched aquifers is given. The distribution of initial water saturation in reservoirs containing excess water is demonstrated through numerical modelling of oil migration over millions of years.
High permeable reservoirs are more likely to have locally trapped water due to lower capillary forces. A static situation occurs in areas where the capillary forces cannot maintain a high enough water saturation for further water drainage. On the other hand, both high and low permeability reservoirs may have significant excess water due to still ongoing dynamical effects. In both cases, long distances for water to drain laterally to a regional aquifer enhances the possibility for a dynamic excess water situation.
The impact of excess water on well test results are demonstrated with focus on calculation of the product of permeability and sand thickness.
This work presents a new open access carbonate reservoir case study that uniquely considers the major uncertainties inherent to carbonate reservoirs using one of the most prolific aggradational parasequence carbonate formation sets in the U.A.E., the Upper Kharaib Member (Early Cretaceous), as an analogue. The ensemble considers a range of interpretational scenarios and geomodelling techniques to capture the main components of its reservoir architecture, stratal geometries, facies, pore systems, diagenetic overprints and wettability variations across its shelf-to-basin profile.
Fully anonymized data from 43 wells across 22 fields in the Bab Basin in the U.A.E from different geo-depositional settings and height above the free water level (FWL) was used. The data comprises of a full suite of open-hole logs and core data which has been anonymized, rescaled, repositioned and structurally deformed; FWLs were normalized and the entire model was placed in a unique coordinate system. The resultant static and dynamic models(s) capture the geological setting and reservoir heterogeneities of selected fields but now at a manageable scale. Synthetic production data has been generated by adding wells to an undisclosed ‘truth case’ model to obtain field-wide and well-by-well production data (oil, gas, and water rates, bottom-hole pressures etc.) from simulation runs.
The original oil in place (OOIP) and reserves that have been computed from these models are synthetic and unique. Here we present an initial field development plan and corresponding reservoir simulations that showcase the heterogeneity inherent to the model and demonstrate the variability of the flow and storage capacity of the different reservoir architectures found in and around the Bab Basin. This is an example application of how we can use synthetic production data to improve our understanding of flow behaviours in carbonates.
The novelty of our work is the provision of a unique open access dataset which enables reproducible science in the field of reservoir characterisation and simulation, and helps training new generations of geoscientists and reservoir engineers in the art of characterising, simulating and predicting the reservoir performance of carbonate reservoirs under different recovery processes.
Much work has been done on hydraulic-fracturing as a well stimulation technique but our understanding of formation damage due to fracturing is limited. This is due to inherent complexity of shale-water interactions under subsurface conditions. Damage is triggered by cold and low-salinity water invasion into the formation. Here, we introduce the formation damage mechanisms as a multi-physics/chemistry problem developing in a region near the fracture-matrix interface. Using high-resolution flow simulation models, we investigate the mechanisms and their impact on natural gas production.
The simulation model includes geo-mechanically fully coupled non-isothermal multi-component two-phase flow equations that are developed for a multi-scale porous medium representative of the shale formations. We consider the occurrence of formation damage during two consecutive periods: well shut-in period which is considered to begin with the completion of fracturing and extending 1-2 days; followed by water flow-back and gas production period which takes months.
During the early shut-in period, cold water invasion leads to thermal contraction of the matrix and reduces the normal mean stress. These changes improve the formation permeability temporarily, they may create secondary fractures, and modify the capillary pressure and saturations in the water invaded zone. These thermal effects are reduced rapidly, however, due to heat supplied by the reservoir. Osmosis pressure and the associated clay swelling cause the formation matrix to absorb fracturing water, reduce the matrix permeability, and amplify the capillary pressure/saturations. In summary, the well goes to the flowback and production with modified near-fracture conditions. During the water flowback the water saturation near the fracture-matrix interface increases; hence, liquid blockage effect on the gas flow becomes larger than that predicted based on the water imbibition during the shut-in only. This is due to capillary-end-effect developing near the interface during the water flow-back, when the fracturing water is displaced by the gas, i.e., drainage. Clay swelling and stress change continue during the withdrawal of the fluids. Consequently, we observe significant impairment in gas production rates.
Only a fraction (<20%) of the injected water is ultimately produced back from the shale gas wells; the rest stays in the fractures and invades into the formation. Our simulation work shows that it is mainly the water in the fractures that are produced. The rest stays in the fractures due to relative permeability effects therein, and in the matrix as capillary-bound water due capillary end effect and to clay-swelling.
Relative permeability and capillary pressure are the key parameters of the multiphase flow in a reservoir. To ensure an accurate determination of these functions in the areas of interest, the core flooding and centrifuge experiments on the relevant core samples need to be interpreted meticulously. In this work, relative permeability and capillary pressure functions are determined synchronously by history matching of multiple experiments simultaneously in order to increase the precision of results based on additional constraints coming from extra measurements. To take into account the underlying physics without making crude assumptions, the Special Core Analysis (SCAL) experiments are chosen to be simulated instead of using well know simplified analytical or semianalytical solutions. Corresponding numerical models are implemented with MRST (Lie, 2019) library. The history matching approach is based on the adjoint gradient method for the constrained optimization problem. Relative permeability and capillary pressure curves, which are the objectives of history matching, within current implementation can have a variety of representations as Corey, LET, B-Splines and NURBS. For the purpose of analyzing the influence of correlations on the history matching results in this study, the interpretation process with assumed analytical correlations is compared to history matching based on generic NURBS representation of relevant functions.
This study shows the application of scaling analysis in the context of CO2 storage. Scaling analysis has been used in many flooding processes to characterize the displacement in such systems. The study aims to derive the key dimensionless numbers pertinent to CO2 storage in saline aquifers. This set of dimensionless numbers may be used to characterize important storage characteristics such as injectivity, plume migration and mobility, the pressure response and the ultimate storage capacity in potential saline aquifers.
CO2 storage in a two-dimensional cross-sectional model representing part of a saline aquifer was considered. The model is assumed to be full of brine when CO2 is injected into it. The fundamental equations for the material conservation of each phase, and the transport equations were formulated and derived. All fluids and the formation were considered compressible. These fundamental equations were then converted into the dimensionless domain by applying inspectional analysis to allow the identification of the key dimensionless numbers characterizing the storage process.
The storage process in such a system can be described by twelve dimensionless numbers, each of which characterize a different aspect of the storage process. Some numbers are similar to those already observed in the context of petroleum processes while a few of them are solely relevant to the storage process. Importantly, the pressure response and the injectivity consideration of the storage process can be described by the injectivity number and the ratio of compressibilities.
A numerical model was constructed to test the sensitivity of the storage process with respect to these dimensionless numbers. Results show the same set of dimensionless numbers can describe storage performance in different systems as long as the processes in all of them are described by identical dimensionless numbers. The lateral migration of the plume and its onset arrival at the storage boundary can be described by the combination of the magnitudes of gravity numbers, effective aspect ratio number, mobility ratio between CO2 and brine and finally the ratio of CO2 and formation compressibilities relative to brine compressibility.
For a confined storage system, the storage efficiency was correlated with the magnitudes of the influencing dimensionless numbers. The derived dimensionless numbers may be used as a set of characterization parameters for describing the storage process in potential storage candidates. They can also be used effectively as a preliminary screening criteria for the purpose of site selection amongst potential storage candidates.
Various physico-chemical processes are affecting Alkali Polymer (AP) Flooding. Core floods can be performed to determine ranges for the parameters used in numerical models describing these processes. Because the parameters are uncertain, prior parameter ranges are introduced and the data is conditioned to observed data. It is challenging to determine posterior distributions of the various parameters as they need to be consistent with the different sets of data that are observed (e.g. pressures, oil and water production, chemical concentration at the outlet).
Here, we are applying Machine Learning in a Bayesian Framework to condition parameter ranges to a multitude of observed data.
To generate the response of the parameters, we used a numerical model and applied Latin Hypercube Sampling (2000 simulation runs) from the prior parameter ranges.
To ensure that sufficient parameter combinations of the model comply with various observed data, Machine Learning can be applied. After defining multiple Objective Functions (OF) covering the different observed data (here six different Objective Functions), we used the Random Forest algorithm to generate statistical models for each of the Objective Functions.
Next, parameter combinations which lead to results that are outside of the acceptance limit of the first Objective Function are rejected. Then, resampling is performed and the next Objective Function is applied until the last Objective Function is reached. To account for parameter interactions, the resulting parameter distributions are tested for the limits of all the Objective Functions.
The results show that posterior parameter distributions can be efficiently conditioned to the various sets of observed data. Insensitive parameter ranges are not modified as they are not influenced by the information from the observed data. This is crucial as insensitive parameters in history could become sensitive in the forecast if the production mechanism is changed.
The workflow introduced here can be applied for conditioning parameter ranges of field (re-)development projects to various observed data as well.