bluuebunny/crossref_metadata_2025_split huggingface dataset:
Special Connections for Representing Multiscale Heterogeneities in Reservoir Simulation
Authors: Correia Manuel , Schiozer Denis 
Published: June 2020

Abstract
The significant quantities of oil contained in fractured karst reservoirs in Brazilian pre-salt fields adds new challenges to the development of upscaling procedures to reduce time on numerical simulations. This work aims to represent multiscale heterogeneities in reservoir simulators based on special connections between matrix, karst, and fracture mediums, both modeled in different grid domains within a single porosity flow model. The objective of this representation is a good balance between accuracy and simulation time. The principle combines the Embedded Discrete Karst Model (EDKM) and the Special Connection Fracture Model (SCFM), both developed by Correia et al, 2019. Therefore, this work extends the approach of special connections to integrate both karst and fracture mediums modeled in different grid domains and block scales. For a proper validation and numerical verification, we applied the methodology to a complex case study. The reference model is a refined grid model with: (1) an arrangement of large conduits (karsts), which are poorly connected, (2) a well-connected and orthogonal system of fractures and (3) a background medium (matrix). For the simulation model, the matrix grid domain has a grid block size of roughly 25 × 25 × 5 meters. The fracture domain has a grid block size of roughly 50 × 50 × 5 meters and the karst grid domain has the same block size as the reference model. Well-connected fractures are upscaled to the fracture domain by applying the Oda (1985) method. The results show a significant performance improvement regarding a dynamic matching response with the reference model, within a suitable simulation time and maintaining the dynamic resolution according to the representative elementary volume of heterogeneities, without using an unconstructed grid. Therefore, this work introduces a new method that can be applied to commercial flow simulators concerning the use of special connections to represent multiscale heterogeneities in flow simulators, without disregarding the accuracy over upscaling and an adequate simulation time.
Applications of Artificial Neural Network for Seismic Facies Classification: A Case Study from the Mid-Cretaceous Reservoir in Supergiant Oil Field
Authors: Al-Ali Ali , Stephen Karl , Shams Asghar 
Published: June 2020

Abstract
Facies classification is significant for characterization and evaluation of a reservoir because the distribution of facies has an important impact on reservoir modelling which is important for decision making and maximizing return. Facies classification using data from sources such as wells and outcrop cannot capture all reservoir characterization in the inter-well region and therefore as an alternative approach, seismic facies classification schemes have to be applied to reduce the uncertainties in the reservoir model. In this research, a machine learning neural network was introduced to predict the lithology required for building a full field earth model for carbonate reservoirs in Sothern Iraq.
In the present research, multilayer feed forward network (MLFN) and probabilistic neural network (PNN) were undertaken to classify facies and its distribution. The well log that was used for litho-facies classification is based on a porosity log. The spatial distribution of litho-facies was validated carefully using core data. Once successfully trained, final results show that PNN technique classified the carbonate reservoir into four facies, while the MLFN presented two facies. The final results on a blind well, show that PNN technique has the best performance on facies classification. These observations implied this reservoir consists of a wide range of lithology and porotype fluctuations due to the impact of depositional environment.
The work and the methodology provide a significant improvement of the facies classification and revealed the capability of probabilistic neural network technique when tested against the neural network. Therefore, it proved to be very successful as developed for facies classification in carbonate rock types in the Middle East and similar heterogeneous carbonate reservoirs.
Exploration of Correlated Prospects and Possible Joint Development Solutions
Authors: Jafarizadeh Babak 
Published: June 2020

Abstract
Drilling exploration wells depend on the uncertainty we perceive. With some simplification, this uncertainty is about the value of producible hydrocarbons. To drill a prospect, the expected benefits from producing and selling hydrocarbons should outweigh the costs. This principle also applies to clusters of interrelated exploration targets. Here, the benefits of drilling each prospect is information about the neighbouring prospects, proving producible hydrocarbons, or both; these benefits should outweigh the aggregate costs. In practice, estimating the expected benefit could be challenging especially when multiple smaller discoveries are developed under a joint development scheme. With these interrelationships, what is the optimal drilling strategy? In addition, what is the economic value of a group of prospects? This paper discusses the effect of joint development economics on perceived uncertainty and drilling decisions. We suggest a framework for valuation of correlated prospects.
Scaling Analysis to Characterise CO2 Storage in Saline Aquifers
Authors: Ghanbari Saeed , Mackay Eric J. , Pickup Gillian E. 
Published: June 2020

Abstract
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.
Development of a Multi-Solution Framework for Simultaneous Well Placement, Completion, and Control Optimization
Authors: Salehian Mohammad , Haghighat Sefat Morteza , Muradov Khafiz 
Published: June 2020

Abstract
Optimal field development and control aim to maximize the economic profit of oil and gas production. This, however, results in a complex optimization problem with a large number of correlated control variables at different levels (e.g. well locations, completions and controls) and a computationally expensive objective function (i.e. a simulated reservoir model). The typical limitations of the existing optimization frameworks are: (1) single-level optimization at a time (i.e. ignoring correlations among control variables at different levels); and (2) providing a single solution only whereas operational problems often add unexpected constraints likely to reduce the ‘optimal’, inflexible solution to a sub-optimal scenario.
The developed framework in this paper is based on sequential iterative optimization of control variables at different levels. An ensemble of close-to-optimum solutions is selected from each level (e.g. for well location) and transferred to the next level of optimization (e.g. to control settings), and this loop continues until no significant improvement is observed in the objective value. Fit-for-purpose clustering techniques are developed to systematically select an ensemble of solutions, with maximum differences in control variables but close-to-optimum objective values, at each level of optimization. The framework also considers pre-defined constraints such as the minimum well spacing, irregular reservoir boundaries, and production/injection rate limits.
The proposed framework has been tested on a benchmark case study, known as the Brugge field, to find the optimal well placement and control in two development scenarios: with conventional (surface control only) and intelligent wells (with additional zonal control using Interval Control Valves). Multiple solutions are obtained in both development scenarios, with different well locations and control settings but close-to-optimum objective values. We also show that suboptimal solutions from an early optimization level can approach and even outdo the optimal one at the higher-level optimization, highlighting the value of the here-developed multi-solution framework in exploring the search space as compared to the traditional single-solution approaches. The development scenario with intelligent completion installed at the optimal well location and optimally controlled during the production period achieved the maximum added value. Our results demonstrate the advantage of the developed multi-solution optimization framework in providing the much-needed operational flexibility to field operators.
Formation Damage Mechanisms Due to Hydraulic Fracturing of Shale Gas Wells
Authors: Elputranto Riza , Cirdi Ayse Pamir , Akkutlu I. Yucel 
Published: June 2020

Abstract
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 (&lt;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.
CO2 Foam Stabilized with Switchable Surfactants and Modified Nanoparticles Effected by PH and Salinity
Authors: Zhang Xuan , Zhang Guicai , Ge Jijiang , Wang Yanqing 
Published: June 2020

Abstract
Foam could increase the apparent viscosity of carbon dioxide (CO2) significantly and control the mobility. This work focused on the enhancement of CO2 foam stability with adding modified silica nanoparticles, which effected by the concentration ratio, pH and salinity.
The results demonstrated that the interaction between the nanoparticles and surfactants was effected by both salinity and pH, and the mixing solution of 0.5 wt% NPs and 0.2 wt% C1202 was colloidal stable in high salinity brine at pH4.5 and 80 °C, while at high pH 6.5, the NPs will aggregate. Higher nanoparticles concentration with constant surfactant concentration would increase the solution colloidal stability due to lower density of surfactant adsorbing at nanoparticles surface. The interfacial tension between CO2 and water dropped to around 6mN/m significantly with surfactant C1202 and adding nanoparticles has slight effect on interfacial tension. However, the compression modulus increased maximum 3 times obviously calculated by the decrease of interfacial tension in shrinking process, which proved that due to strong and irreversible nanoparticles adsorption. Moreover, the core flooding results confirmed that adding NPs results in more viscous foam generation to reduce the CO2 mobility and the total oil recovery enhanced 17% comparing with water flooding. This mixing solution makes it possible to enhance CO2 foam stability at low pH and given high salinity, which is important to reduce gas mobility in reservoir conditions and, eventually, enhance oil recovery.
The Effect of Horizontal-Permeability Anisotropy on the Design of Geothermal Doublets
Authors: Talebian Mojtaba , Salimi Hamidreza 
Published: June 2020

Abstract
The detection and quantification of horizontal-permeability anisotropy play a vital role in optimally placing geothermal wells in geothermal reservoirs and thereby maximizing the geothermal-energy recovery from a given geothermal-reservoir area. However, the study of permeability anisotropy within the horizontal plane has received less attention and often permeability anisotropy is neglected in view of simplification.
Our study show that the horizontal permeability anisotropy has been observed in nearly all geothermal doublets that have been tested so far in the Netherlands. The main objective of this work is to study the impacts of horizontal permeability anisotropy inferred from pressure-interference tests on geothermal-doublets performance.
A theoretical relation between the measured directional permeability and the elements of the permeability tensor are presented. In a case study, horizontal anisotropy has been detected and quantified using a pressure-transient analysis, interference test, and the knowledge of the reservoir geometry gained from the geological study. In addition, this work uses a detailed three-dimensional thermal reservoir simulator of a reservoir in the West Netherlands Basin to demonstrate the importance of considering permeability anisotropy in predicting the lifecycle, which is determined by the cold-temperature breakthrough of an existing doublet and in optimally designing the second doublet in the same licensed area.
It has been established that the areal permeability anisotropy plays an important role in the energy sweep efficiency and doublets placement. A correct arrangement between the permeability anisotropy direction and the placement of the wells leads to longer breakthrough time and increasing the heat sweep efficiency.
This work shows that the knowledge gained from the interference test and/or other experiments about the presence, direction, and scale of anisotropy can be used to adjust the reservoir model that can be further used to design and optimize geothermal doublets.
Digital Rock Physics in Low-Permeable Sandstone, Downsampling for Unresolved Sub-Micron Porosity Estimation
Authors: Ebadi Mohammad , Makhotin Ivan , Orlov Denis , Koroteev Dmitri 
Published: June 2020

Abstract
The approach to handle the unresolved pores at 3D X-ray Micro Computed Tomography (μCT) images of core samples is developed. It enables a sufficient widening of digital rock studies for tight rocks. The μCT images of a low-permeable sandstone with a resolution of 1.2 μm/voxel have been generated. Pore Size Distribution shows the presence of a significant amount of sub-resolution pores. Downsampling has been applied to estimate the actual porosity with extrapolation.
Visual noise, artifacts, and roundoff errors are the major factors affecting the quality of μCT images. We apply transform and spatial domain filtering to minimize all the artifacts. Regarding the overall concept of porosity and through running a geometrical histogram analysis, the Random Walker segmentation as a robust mathematical algorithm has been applied to turn the greyscale μCT images into binary ones resembling pores and grains. Next, the porosity of the binary images with a resolution of 1.2 μm/voxel has been calculated. The procedure continues with downsampling to artificially reduce the resolution and calculate the corresponding porosity.
It has been observed that the calculated porosity for the highest resolution of 1.2 micrometer is still lower than the experimental value which is due to the existence of pores which their sizes are less than 1.2 micrometer, and cannot be seen in the CT images. In order to take the effects of sub-resolution pores into account, an extrapolation relying on the downsampling technique has successfully been applied. The implemented technique is based on the fact that the porosity of the reservoir rock sample is not a function of resolution. However, plotting of the calculated porosities versus their relevant resolutions indicates that the value of porosity has an inverse relationship with the voxel size. In other words, it could be interpreted that the closest values of the calculated porosity to the laboratory reports will be the output of the image processing when the size of voxel moves towards zeros as much as possible, which is technically impossible. Instead, a trendline can be fitted into the scatter plot of porosity versus resolution and find its extrapolation value for the voxel size of zero, which provides the porosity as close as possible to the experimental value.
The main logic behind the digital core analysis is to calculate the properties only according to the digital images. Although there are some studies in which modifications have been done to consider the effects of sub-resolution pores, they are severely suffering from mathematical complexities, and they are mainly based on the global thresholding. The proposed technique can provide an accurate value of porosity when there are no additional data about the pore structure of the sub-micron scale.
Numerical Simulation Guideline of Oil Recovery by Cycle-Dependent Three-Phase Process Using Coreflood Experiments
Authors: Al Zayer Hassan , Sohrabi Mehran 
Published: June 2020

Abstract
Many oil reservoirs worldwide have cycle dependent oil recovery either by design (e.g. WAG injection) or unintended (e.g. repeated expansion/shrinkage of gas cap). However, to reliably predict oil recovery involving three-phase flow process, a transformational shift in the procedure to model such complex recovery method is needed. Therefore, this study focused on identifying the shortcomings of the current reservoir simulators to improve the simulation formulation of the cycle-dependent three-phase relative- permeability hysteresis.
To achieve this objective, several core-scale water-alternating-gas (WAG) injection experiments were analysed to identify the trends and behaviours of oil recovery by the different WAG cycles. Furthermore, these experiments were simulated to identify the limitations of the current commercial simulators available in the industry. Based on the simulation efforts to match the observed experimental results, a new methodology to improve the modelling process of WAG injection using the current simulation capabilities was suggested. Then the WAG injection core-flood experiments utilized in this study were simulated to validate the new approach.
The results of unsteady-state WAG injection experiments performed at different conditions were used in this simulation study. The simulation of the WAG injection experiments confirmed the positive impact of updating the three-phase relative-permeability hysteresis parameters in the later WAG injection cycles. This change significantly improved the match between simulation and WAG experimental results. Therefore, a systematic workflow for acquiring and analyzing the relevant data to generate the input parameters required for WAG injection simulation is presented. In addition, a logical procedure is suggested to update the simulation model after the third injection cycle as a workaround to overcome the limitation in the current commercial simulators.
This guideline can be incorporated in the numerical simulators to improve the accuracy of oil recovery prediction by any cycle-dependent three-phase process using the current simulation capabilities.