Recent Submissions

  • Enhancing Fracture Network Characterization: A Data-Driven, Outcrop-Based Analysis

    Zhu, Weiwei; He, Xupeng; Santoso‬, ‪Ryan Kurniawan; Lei, Gang; Patzek, Tadeusz; Wang, Moran (Wiley, 2021-10-11) [Preprint]
    The stochastic discrete fracture network (SDFN) model is a practical approach to model complex fracture systems in the subsurface. However, it is impossible to validate the correctness and quality of an SDFN model because the comprehensive subsurface structure is never known. We utilize a pixel-based fracture detection algorithm to digitize 80 published outcrop maps of different scales at different locations. The key fracture properties, including fracture lengths, orientations, intensities, topological structures, clusters and flow are then analyzed. Our findings provide significant justifications for statistical distributions used in SDFN modellings. In addition, the shortcomings of current SDFN models are discussed. We find that fracture lengths follow multiple (instead of single) power-law distributions with varying exponents. Large fractures tend to have large exponents, possibly because of a small coalescence probability. Most small-scale natural fracture networks have scattered orientations, corresponding to a small κ value (κ<3) in a von Mises--Fisher distribution. Large fracture systems collected in this research usually have more concentrated orientations with large κ values. Fracture intensities are spatially clustered at all scales. A fractal spatial density distribution, which introduces clustered fracture positions, can better capture the spatial clustering than a uniform distribution. Natural fracture networks usually have a significant proportion of T-type nodes, which is unavailable in conventional SDFN models. Thus a rule-based algorithm to mimic the fracture growth and form T-type nodes is necessary. Most outcrop maps show good topological connectivity. However, sealing patterns and stress impact must be considered to evaluate the hydraulic connectivity of fracture networks.
  • Influence of pressure, temperature and organic surface concentration on hydrogen wettability of caprock; implications for hydrogen geo-storage

    Ali, Muhammad; Yekeen, Nurudeen; Pal, Nilanjan; Keshavarz, Alireza; Iglauer, Stefan; Hoteit, Hussein (Energy Reports, Elsevier BV, 2021-09-21) [Article]
    Hydrogen (H2) as a cleaner fuel has been suggested as a viable method of achieving the decarbonization objectives and meeting increasing global energy demand. However, successful implementation of a full-scale hydrogen economy requires large-scale hydrogen storage (as hydrogen is highly compressible). A potential solution to this challenge is injecting hydrogen into geologic formations from where it can be withdrawn again at later stages for utilization purposes. The geostorage capacity of a porous formation is a function of its wetting characteristics, which strongly influence residual saturations, fluid flow, rate of injection, rate of withdrawal, and containment security. However, literature severely lacks information on hydrogen wettability in realistic geological and caprock formations, which contain organic matter (due to the prevailing reducing atmosphere). We, therefore, measured advancing (θa) and receding (θr) contact angles of mica substrates at various representative thermo-physical conditions (pressures 0.1-25 MPa, temperatures 308–343 K, and stearic acid concentrations of 10−9- 10−2 mol/L). The mica exhibited an increasing tendency to become weakly water-wet at higher temperatures, lower pressures, and very low stearic acid concentration. However, it turned intermediate-wet at higher pressures, lower temperatures, and increasing stearic acid concentrations. The study suggests that the structural H2 trapping capacities in geological formations and sealing potentials of caprock highly depend on the specific thermo-physical condition. Thus, this novel data provides a significant advancement in literature and will aid in the implementation of hydrogen geo-storage at an industrial scale
  • Fracture Permeability Estimation Under Complex Physics: A Data-Driven Model Using Machine Learning

    He, Xupeng; Zhu, Weiwei; Santoso, Ryan; Alsinan, Marwa; Kwak, Hyung; Hoteit, Hussein (SPE, 2021-09-15) [Conference Paper]
    Abstract The permeability of fractures, including natural and hydraulic, are essential parameters for the modeling of fluid flow in conventional and unconventional fractured reservoirs. However, traditional analytical cubic law (CL-based) models used to estimate fracture permeability show unsatisfactory performance when dealing with different dynamic complexities of fractures. This work presents a data-driven, physics-included model based on machine learning as an alternative to traditional methods. The workflow for the development of the data-driven model includes four steps. Step 1: Identify uncertain parameters and perform Latin Hypercube Sampling (LHS). We first identify the uncertain parameters which affect the fracture permeability. We then generate training samples using LHS. Step 2: Perform training simulations and collect inputs and outputs. In this step, high-resolution simulations with parallel computing for the Navier-Stokes equations (NSEs) are run for each of the training samples. We then collect the inputs and outputs from the simulations. Step 3: Construct an optimized data-driven surrogate model. A data-driven model based on machine learning is then built to model the nonlinear mapping between the inputs and outputs collected from Step 2. Herein, Artificial Neural Network (ANN) coupling with Bayesian optimization algorithm is implemented to obtain the optimized surrogate model. Step 4: Validate the proposed data-driven model. In this step, we conduct blind validation on the proposed model with high-fidelity simulations. We further test the developed surrogate model with newly generated fracture cases with a broad range of roughness and tortuosity under different Reynolds numbers. We then compare its performance to the reference NSEs solutions. Results show that the developed data-driven model delivers good accuracy exceeding 90% for all training, validation, and test samples. This work introduces an integrated workflow for developing a data-driven, physics-included model using machine learning to estimate fracture permeability under complex physics (e.g., inertial effect). To our knowledge, this technique is introduced for the first time for the upscaling of rock fractures. The proposed model offers an efficient and accurate alternative to the traditional upscaling methods that can be readily implemented in reservoir characterization and modeling workflows.
  • CO2 Leakage Rate Forecasting Using Optimized Deep Learning

    He, Xupeng; ZHU, Weiwei; Santoso, Ryan; Alsinan, Marwa; Kwak, Hyung; Hoteit, Hussein (SPE, 2021-09-15) [Conference Paper]
    Abstract Geologic CO2 Sequestration (GCS) is a promising engineering technology to reduce global greenhouse emissions. Real-time forecasting of CO2 leakage rates is an essential aspect of large-scale GCS deployment. This work introduces a data-driven, physics-featuring surrogate model based on deep-learning technique for CO2 leakage rate forecasting. The workflow for the development of data-driven, physics-featuring surrogate model includes three steps: 1) Datasets Generation: We first identify uncertainty parameters that affect the objective of interests (i.e., CO2 leakage rates). For the identified uncertainty parameters, various realizations are then generated based on Latin Hypercube Sampling (LHS). High-fidelity simulations based on a two-phase black-oil solver within MRST are performed to generate the objective functions. Datasets including inputs (i.e., the uncertainty parameters) and outputs (CO2 leakage rates) are collected. 2) Surrogate Development: In this step, a time-series surrogate model using long short-term memory (LSTM) is constructed to map the nonlinear relationship between these uncertainty parameters as inputs and CO2 leakage rates as outputs. We perform Bayesian optimization to automate the tuning of hyperparameters and network architecture instead of the traditional trial-error tuning process. 3) Uncertainty Analysis: This step aims to perform Monte Carlo (MC) simulations using the successfully trained surrogate model to explore uncertainty propagation. The sampled realizations are collected in the form of distributions from which the probabilistic forecast of percentiles, P10, P50, and P50, are evaluated. We propose a data-driven, physics-featuring surrogate model based on LSTM for CO2 leakage rate forecasting. We demonstrate its performance in terms of accuracy and efficiency by comparing it with ground-truth solutions. The proposed deep-learning workflow shows promising potential and could be readily implemented in commercial-scale GCS for real-time monitoring applications.
  • Stratigraphy of The Central Red Sea Margin: New Insights on the Tectono-stratigraphy of the Pre- and Syn- rift sedimentary sections and Arabian Plateau Uplift

    AlTammar, Ali J. (2021-09) [Thesis]
    Advisor: Alafifi, Abdulkader Musa
    Committee members: Buchem, Frans van; Vahrenkamp, Volker
    Broad uplift of the Red Sea margins has extensively eroded the pre-rift sedimentary section and exhumed the Proterozoic basement in the Arabian and Nubian Shields. However, some pre-rift sedimentary rocks are preserved within rift grabens along the coast, and on top of the Arabian plateau beneath syn-rift basalts of Harrat Hadan. Previous studies on outcrops of pre- and syn-rift sedimentary rocks near Jeddah assigned them various ages and Formations leading to confusion. Moreover, no attempts were made to correlate them to the section sitting on top of the Arabian plateau. This study redefines the stratigraphy of pre-rift sedimentary rocks in the Jeddah area (Usfan and Shumaysi Formations) and correlates them with similar rocks located 200 km east over the Arabian Shield (Khurma and Umm Himar Formations). Field work, petrographic investigation and satellite image mapping data from the central Red Sea are used to reveal new stratigraphic correlations for the pre-rift section and new insights about the uplift of the Arabian plate. The pre-rift sedimentary rocks rest uncomfortably on the Precambrian basement, consisting of sandstones, oolitic ironstone, shale, and bioclastic limestones. Their distinguishing characteristic is the textural and compositional maturity and total absence of basement-derived lithic pebbles. The pre-rift sedimentary rocks are disconformably overlain by a syn-rift section, reaching several kilometers thick, consisting of immature continental redbeds composed of basement-derived conglomerates, sandstones, and mudstones. They are distinguished by their brick-red color, poor sorting, and compositional immaturity. The presence of pre-rift marine sediments in Harrat Hadan over the Arabian shield and in the coastal plain of the Red Sea indicates that it was at or below sea level during the early Cenozoic. Subsequently, the rift was filled with immature continental syn-rift sediments eroded from the margins. Some key markers, particularly oolitic ironstones, define correlative units throughout the study area. Furthermore, the presence of 28 My old basaltic lava flows at the base of the syn-rift section in both the Jeddah and Harrat Hadan areas provides, for the first time, a reliable date for the start of rifting in the central Red Sea, and clear separation of pre-rift from syn-rift sedimentary rocks
  • Fracture Network Analysis for Carbon Mineralization in the Oligocene Jizan Volcanics, Saudi Arabia

    Al Malallah, Murtadha (2021-09) [Thesis]
    Advisor: Alafifi, Abdulkader Musa
    Committee members: Hoteit, Hussein; Van der Zwan, Froukje M.
    This study aims to characterize the fracture network in altered Oligocene-Early Miocene basalts of the Jizan Group, which accumulated in half grabens during the continental rift stage of Red Sea evolution. Unlike fresh basalts, the Jizan Group was affected by low temperature hydrothermal metamorphism, which plugged the original matrix porosity in vesicles, breccias, and interflow layers with alteration minerals. However, the basalts are pervasively shattered by closely spaced fractures in several directions, which provide fracture permeability. Characterization of these fractures is essential to reducing the fracture permeability uncertainty for mineral carbonation by the dissolved CO2 process such as Carbfix. Conventional fracture orientation and densities were initially taken at outcrops of the Jizan Group to characterize the fracture network. Terrestrial Digital Photogrammetry (TDP) and Unmanned Aerial Vehicle Digital Photogrammetry (UAVDP) surveys were conducted to acquire images covering larger areas to create 2D orthoimages and 3D models of the outcrops using Agisoft Metashape, which were analyzed for fracture geometries using QGIS and Cloud Compare, respectively. The automated analysis of fracture orientations and densities compared well with conventional manual measurements. Similar fracture geometries were observed at seven different sites along the outcrop belt of the Jizan Group, which suggests a common origin. This study found four dominating fracture sets in the Jizan Group volcanics, with a dominant trend of fractures in the NNW direction, similar to the general trend of the Red Sea. The Northern sites presented higher fracture intensity compared to the southern sites, indicating more suitable environments for carbon mineralization. Moreover, mineralogical composition of spatially distributed samples collected from the Jizan Group volcanics were collected to investigate spatial distributions of secondary alteration minerals in the Jizan Group basalts. Epidote was observed in samples collected from southern outcrops indicating hydrothermal alteration temperatures higher than 230 C, whereas the northern sites lacked epidote and contained calcite indicating lower hydrothermal alteration temperatures. The presence of sufficient amounts of Ca according to previous studies conducted by Torres (2020), along with potential 3D fracture networks in the subsurface indicate feasibility for the injection of CO2 charged fluids in the subsurface of the volcanics.
  • Fault Traces: Generation of Fault Segments and Estimation of Their Fractal Dimension

    Zhu, Weiwei; Yalcin, Bora; Khirevich, Siarhei; Patzek, Tadeusz (Lithosphere, GeoScienceWorld, 2021-08-27) [Article]
    Fault damage zones have a higher upscaled permeability than the host rock because of a higher fracture intensity therein. Fracture distribution in the damage zone depends highly on the geometry of fault segments. However, precise images of architectural elements of large-scale faults at depth are difficult to obtain by seismic acquisition and imaging techniques. We present a numerical method that generates fault segments at multiple scales from an imprecise fault trace based on the fractal properties of these segments. The generated fault segments demonstrate hierarchical self-similar architecture, and their lengths follow approximately a lognormal distribution. These characteristics are similar to real fault segments observed in outcrops and seismic surveys. An algorithm that covers fault segments accurately with the minimum number of circles is proposed to calculate the fractal dimensions for both natural and computer-generated faults. The fractal dimensions of natural and generated fault segments are similar and range between 1.2 and 1.4.
  • Fault Traces: Generation of Fault Segments and Estimation of Their Fractal Dimension

    Zhu, Weiwei; Yalcin, Bora; Khirevich, Siarhei; Patzek, Tadeusz (Lithosphere, GeoScienceWorld, 2021-08-27) [Article]
    Fault damage zones have a higher upscaled permeability than the host rock because of a higher fracture intensity therein. Fracture distribution in the damage zone depends highly on the geometry of fault segments. However, precise images of architectural elements of large-scale faults at depth are difficult to obtain by seismic acquisition and imaging techniques. We present a numerical method that generates fault segments at multiple scales from an imprecise fault trace based on the fractal properties of these segments. The generated fault segments demonstrate hierarchical self-similar architecture, and their lengths follow approximately a lognormal distribution. These characteristics are similar to real fault segments observed in outcrops and seismic surveys. An algorithm that covers fault segments accurately with the minimum number of circles is proposed to calculate the fractal dimensions for both natural and computer-generated faults. The fractal dimensions of natural and generated fault segments are similar and range between 1.2 and 1.4.
  • Natural Rock Fractures: From Aperture to Fluid Flow

    Cardona, Alejandro; Finkbeiner, Thomas; Santamarina, Carlos (Rock Mechanics and Rock Engineering, Springer Science and Business Media LLC, 2021-08-07) [Article]
    AbstractFractures provide preferential flow paths and establish the internal “plumbing” of the rock mass. Fracture surface roughness and the matedness between surfaces combine to delineate the fracture geometric aperture. New and published measurements show the inherent relation between roughness wavelength and amplitude. In fact, data cluster along a power trend consistent with fractal topography. Synthetic fractal surfaces created using this power law, kinematic constraints and contact mechanics are used to explore the evolution of aperture size distribution during normal loading and shear displacement. Results show that increments in normal stress shift the Gaussian aperture size distribution toward smaller apertures. On the other hand, shear displacements do not affect the aperture size distribution of unmated fractures; however, the aperture mean and standard deviation increase with shear displacement in initially mated fractures. We demonstrate that the cubic law is locally valid when fracture roughness follows the observed power law and allows for efficient numerical analyses of transmissivity. Simulations show that flow trajectories redistribute and flow channeling becomes more pronounced with increasing normal stress. Shear displacement induces early aperture anisotropy in initially mated fractures as contact points detach transversely to the shear direction; however, anisotropy decreases as fractures become unmated after large shear displacements. Radial transmissivity measurements obtained using a torsional ring shear device and data gathered from the literature support the development of robust phenomenological models that satisfy asymptotic trends. A power function accurately captures the evolution of transmissivity with normal stress, while a logistic function represents changes with shear displacement. A complementary hydro-chemo-mechanical study shows that positive feedback during reactive fluid flow heightens channeling.
  • Comparison of various reactive transport simulators for geological carbon sequestration

    Addassi, Mouadh; Omar, Abdirizak; Ghorayeb, Kassem; Hoteit, Hussein (International Journal of Greenhouse Gas Control, Elsevier BV, 2021-08-05) [Article]
    The capabilities of reactive transport modeling codes for geological carbon sequestration have improved significantly in the past decade. Comparing different geochemical modeling codes is crucial to identify modeling discrepancies, especially when experimental validation is not feasible. However, it is challenging to consistently get comparable results, as shown in previous studies where batch reaction of CO2 storage using different simulators sometimes resulted in significant discrepancies in their outputs. In this study, we introduce and demonstrate an approach to consistently produce comparable batch-reaction modeling of kinetically controlled CO2-water-rock interactions in PHREEQC, TOUGHREACT, and GEM, which are amongst the most widely used simulators for CO2 sequestration studies. The primary step is to assemble a thermodynamic database in PHREEQC format, with representative fluid properties for CO2-water interaction, and carefully convert it to the format of the other simulators. We use two case studies from the literature to demonstrate our method where good matches between the outputs of all three simulators were achieved, which was not previously attained. Furthermore, limiting the discrepancies in batch-reaction models provides a consistent baseline to study the coupled mechanisms of transport and chemical reaction, which was also successfully demonstrated with a one-dimensional reactive transport model in PHREEQC, GEM and TOUGHREACT.
  • Three-dimensional natural convection, entropy generation and mixing in heterogeneous porous medium

    Yang, Xiangjuan; Shao, Qian; Hoteit, Hussein; Carrera, Jesus; Younes, Anis; Fahs, Marwan (Advances in Water Resources, Elsevier BV, 2021-07-02) [Article]
    Three-dimensional (3D) natural convection (NC) processes in heterogeneous porous media and associated energy losses and mixing processes are still poorly understood. Studies are limited to two-dimensional domains because of computational burden, worsened by heterogeneity, which may demand grid refinement at high permeability zones for accurate evaluation of buoyancy forces. We develop a meshless Fourier series (FS) solution of the natural convection problem in a porous enclosure driven by thermal or compositional variations. We derive the vector potential formulation of the governing equations for vertical and horizontal heterogeneity of hydraulic conductivity and implement an efficient method to solve the spectral system with an optimized number of Fourier modes. 3D effects are induced either by heterogeneity or variable boundary conditions. The developed FS solution is verified against a finite element solution obtained using COMSOL Multiphysics. We evaluate entropy generation (viscous dissipation and mixing) indicators using FS expansions and assess how they are affected by heterogeneity. We define a large-scale Rayleigh number to account for heterogeneity by adopting an arithmetic average effective permeability. The FS solution is used to investigate the effect of the large-scale Rayleigh number and level of heterogeneity on NC processes and energy losses. Results show that increasing the Rayleigh number intensifies fluid flow, thus enhancing convective transfer, which causes a dramatic increase in total entropy generation. Both viscous dissipation and mixing (and thus chemical reactions in the solute transport case) increase. The third dimension effect, which also enhances flow and entropy indicators, is more pronounced at high Rayleigh numbers. Surprisingly, entropy variation indicators remain virtually unchanged in response to changes in heterogeneity, for fixed Rayleigh number, which we attribute to the arithmetic average permeability being indeed appropriate for NC in 3D. This study not only explores the effect of Rayleigh number and heterogeneity on natural convection processes and the associated entropy generation and mixing processes, but also provides a highly accurate solution that can be used for codes benchmarking.
  • Rock mechanical characterization of the Upper Cretaceous carbonate mudrocks of Jordan

    Iakusheva, Regina (2021-07) [Thesis]
    Advisor: Vahrenkamp, Volker
    Committee members: Alafifi, Abdulkader Musa; Finkbeiner, Thomas
    Rock mechanical properties of subsurface strata, such as strength, hardness, brittleness, and elasticity, play an important role during reservoir development for wellbore stability, fracture prediction and generation, and the application of other engineering techniques. Specifically, for unconventional reservoir development characterization of the mechanical properties of organic-rich layered rocks is critical, including for the design of proper drilling, well completion, and production programs. This study evaluates rock mechanical properties of Jordanian Upper Cretaceous organic-rich carbonate mudrocks, which are comprised of carbonate mudstone, chalky marl and shale interlayers. They are characterized by high organic content, heterogeneous porosity (1.2%- 35%) and a nanodarcy permeability. The study mainly derives rock mechanical properties from core and laboratory investigations, with the aim to access the impact of compositional and sedimentary facies variation on rock mechanical properties. The rocks were examined for their lithology, mineralogy, and mechanical properties. Microscopic investigation allowed the definition of four different microfacies (organic-rich (OR) mudstone, OR wackestone, silica-rich packstone, OR packstone). X-Ray analysis shows that different microfacies types exhibit various mineralogical compositions, with carbonate, biogenic quartz, and apatite as the dominant components. All samples are rich in TOC content, ranging from 7.5 to 25.3% (average 16.6 wt.%). The data show that microfacies variation has a clear impact on the rock mechanical properties. Leeb Hardness (LH) is higher in silica-rich packstone and OR mudstone. Intrinsic specific energy (ISE) and wave velocities reach their maximum in OR mudstones. The average porosity values are much higher in OR wackestones (33.2%) and OR packstones (34.3%). The brittleness index (BI), which was calculated based on mineral composition, indicate that silica-rich packstones and OR mudstones are brittle, while the other two microfacies have properties of a ductile material. In addition, the good correlation between the ISE and BI suggests that ISE values are a useful proxy for brittleness. The present study improves the understanding of the relationships between stratigraphy, microfacies, TOC, and mechanical properties. These insights bear implications for improvement of exploitation of the JOS, understanding of rock mechanical properties of mature unconventional formations as well as provide the workflow for more efficient procedure to access the compressive strength
  • Analysis and Visualization of 3D pore networks in Pleistocene reef cores from Shurayrah Island (Al Wajh, N Red Sea)

    Oyinloye, Michael (2021-07) [Thesis]
    Advisor: Vahrenkamp, Volker
    Committee members: Alafifi, Abdulkader Musa; Sun, Shuyu
    The characterization of petrophysical properties such as porosity and permeability of carbonate reservoirs for understanding their heterogeneous nature is essential to enhance reservoir modelling and exploration. In the early development stages of carbonate rocks, early diagenesis features fundamental changes in the porosity and permeability systems which will likely yield enormous influence on the subsequent diagenesis, and hence the petrophysical properties of potential limestone reservoirs. From a Late Pleistocene (MIS5) reefal core limestone from Al Wajh, Shurayrah Island, Northern Red Sea, KSA, detailed petrographic image analysis of thin sections, laboratory measurements of porosity and permeability and x-ray computed tomography (CT) of core plugs and whole core sections, were used for the identification, analysis and visualization of the pore types, pore network and pore connectivity. Analyzed x-ray CT scan images reveal the pore types, pore network and pore connectivity in 2D and 3D. A separate in-depth facies and diagenesis study using thin section images coupled with x-ray CT image analysis, shows lithofacies and microfacies types control most of the early diagenesis hence porosity and permeability. This thesis hopes to open a pathway to understanding pore and pore throat structures as well as the porosity-permeability relationship in young carbonate rocks before deep burial to enhance reservoir modelling and characterization of analogues
  • Improving Formation Pressure Integrity Tests with Field-Wise Test Data Analysis and Hydraulic Impedance Testing

    Abilov, Elmir (2021-07) [Thesis]
    Advisor: Patzek, Tadeusz
    Committee members: Finkbeiner, Thomas; Ahmed, Shehab
    Drilling operations without issues and non-productive time are highly desired by operators. Circulation loss is one of the common issues faced during drilling when a formation is fractured by mud weight or by Equivalent Circulating Density (ECD) exceeding the formation fracture gradient. This makes it necessary to obtain information about in-situ stress and rock strength. Formation Pressure Integrity Tests (FPITs) determine directly the fracture pressure of the formation or test the formation for a safe drilling mud weight window and kick tolerance. Although FPIT is a routine test conducted before drilling each hole section, previous studies and field experience have demonstrated several problems and a lack of unique operational procedures for these tests. This study examines some of the main issues faced during operation and interpretation of FPITs and possible solutions to eliminate them. We generated a unique database of FPITs which includes all necessary technical and non-technical details about each test and analyzed the discrepancy between surface and downhole pressure data generated while conducting FPITs. We also analyzed pressure build-up behavior versus pumped fluid volume and its similarities with Casing Integrity Tests (CIT). Furthermore, we investigated pressure loss rates after shut-in, and the application of hydraulic impedance testing to improve test quality. Our analysis of the discrepancy trends indicated that Reservoir Drilling Fluid (RDF) causes more pressure transmission losses than Oil-Based Mud (OBM). We examined more than 50 tests based on pressure build-up behavior versus pumped fluid volume and obtained an empirical equation that only requires the measured depth to give an estimation for the pressure build-up rate. In addition, comparing CIT with FPIT based on pressure build-up rate shows similarities between the tests, and CIT build-up rate values can potentially be used as an initial assumption for FPIT build-up rate. Our findings reveal that pressure loss rate after pump-off is less than 6 psi/min in more than 65% of the Formation Integrity Tests (FITs). We also suggest to use Hydraulic Impedance Testing (HIT) method together with formation strength tests to give a qualitative indication of fracture initiation and a quantitative estimation of fracture dimensions.
  • Application of Physics-Informed Neural Networks to Solve 2-D Single-phase Flow in Heterogeneous Porous Media

    Alhubail, Ali (2021-07) [Thesis]
    Advisor: Hoteit, Hussein
    Committee members: Sun, Shuyu; Ahmed, Shehab
    Neural networks have recently seen tremendous advancements in applicability in many areas, one of which is their utilization in solving physical problems governed by partial differential equations and the constraints of these equations. Physics-informed neural networks is the name given to such neural networks. They are different from typical neural networks in that they include loss terms that represent the physics of the problem. These terms often include partial derivatives of the neural network outputs with respect to its inputs, and these derivatives are found through the use of automatic differentiation. The purpose of this thesis is to showcase the ability of physics-informed neural networks to solve basic fluid flow problems in homogeneous and heterogeneous porous media. This is done through the utilization of the pressure equation under a set of assumptions as well as the inclusion of Dirichlet and Neumann boundary conditions. The goal is to create a surrogate model that allows for finding the pressure and velocity profiles everywhere inside the domain of interest. In the homogeneous case, minimization of the loss function that included the boundary conditions term and the partial differential equation term allowed for producing results that show good agreement with the results from a numerical simulator. However, in the case of heterogeneous media where there are sharp discontinuities in hydraulic conductivity inside the domain, the model failed to produce accurate results. To resolve this issue, extended physics-informed neural networks were used. This method involves the decomposition of the domain into multiple homogeneous sub-domains. Each sub-domain has its own physics informed neural network structure, equation parameters, and equation constraints. To allow the sub-domains to communicate, interface conditions are placed on the interfaces that separate the different sub-domains. The results from this method matched well with the results of the simulator. In both the homogeneous and heterogeneous cases, neural networks with only one hidden layer with thirty nodes were used. Even with this simple structure for the neural networks, the computations are expensive and a large number of training iterations is required to converge.
  • Carbonate Acidizing: Modeling and Uncertainty Propagation Analysis

    Sahu, Qasim (2021-07) [Thesis]
    Advisor: Hoteit, Hussein
    Committee members: Alafifi, Abdulkader Musa; Vahrenkamp, Volker C.
    Reservoir stimulation is a common technique used to improve the productivity of carbonate reservoirs. One of the effective stimulation methods is carbonate acidizing. This process involves injecting a reactive fluid to dissolve the rock mineral, creating a conductive path for hydrocarbon flow. With the development of tight and unconventional reservoirs, stimulation has become more critical for optimal economic production. This study aims to simulate the dissolution of carbonate in matrix acidizing. A reactive transport model is implemented in a finite – element solver to simulate the initiation and propagation of the dissolution channel in the carbonate rock in a two – dimensional domain. We investigate the effect of varying the injection rate on the dissolution channel and the efficiency of the acidizing fluid. Next, we use polynomial chaos expansion to conduct uncertainty propagation analysis. These uncertainties may have a major impact on the predictability of the simulation model. We utilize the surrogate model and Sobol indices to identify the most significant parameter in the model. The analysis provides an assessment of how the uncertainty can propagate to the model’s response. Also, we utilize the surrogate model to calculate the univariate effect. The results showed that the dissolution channel and pore volume to breakthrough depends on the injection rate. Furthermore, the surrogate model reproduces the simulation model results for the 5 dissolution channel, the pore volume to breakthrough, and the effective permeability. The global sensitivity analysis shows that the acid capacity number is the most significant parameter for the pore volume to breakthrough with the highest Sobol index value. For effective permeability, the initial mean porosity is the primary source of uncertainty. The marginal effect calculated for the individual parameter correlates with the results from Sobol indices.
  • Semi-Analytical Solution to Assess CO2 Leakage in the Subsurface through Abandoned Wells

    Qiao, Tian (2021-07) [Thesis]
    Advisor: Hoteit, Hussein
    Committee members: Patzek, Tadeusz; Sun, Shuyu
    Geological storage is an effective approach capable of reducing greenhouse gases emissions at significant scales by storing the CO2 underground. Subsurface reservoirs with sealing caprocks can provide long-term containment for the injected CO2. However, the leakage is a major concern in most storage sites. The presence of abandoned wells penetrating the reservoir caprock may cause leakage flow paths for CO2 to the overburden. To access the leakage in the subsurface, an analytical model for the time-varying leaky well is needed. In this thesis, we propose a new semi-analytical approach based on pressure-transient analysis to model the behavior of leakage and corresponding pressure distribution in multiple wells multiple layers system. Current solutions either take approximations on essential operations or requires numerical inversion for the solution in the Laplace domain. In this work, we employ the superposition in time and space to solve the diffusivity equation in 2D radial flow to approximate the transient pressure in the reservoirs. We use numerical simulations to verify the proposed time-dependent semi-analytical solution. The results show good agreement in both pressure and leakage rates. Sensitivity analysis is conducted to assess different CO2 leakage scenarios to the overburden. The equivalent injection rate is also proposed to release the single-phase assumption so that the solution can recover identical results as two-phase numerical simulation in the far-field.
  • Structural aspects, mechanisms and emerging prospects of Gemini surfactant-based alternative Enhanced Oil Recovery technology: A review

    Pal, Nilanjan; Hoteit, Hussein; Mandal, Ajay (Journal of Molecular Liquids, Elsevier BV, 2021-06-30) [Article]
    The design and development of chemical routes with fascinating physicochemical attributes comprise a major field of research in enhanced oil recovery (EOR). ‘Dimerization’ depicts a novel way to control structural assemblies and physicochemical properties, to achieve marked improvements in the chemical EOR process, and strategize oil recovery performance. There are immense possibilities for the diversification of gemini surfactant structure, which essentially consists of two identical or distinct amphiphilic units linked with a spacer group. Gemini surfactant molecules possess significantly lower critical micelle concentration (CMC) as compared to their monomeric counterparts, owing to their ability to self-aggregate at low dosages. Gemini surfactants exhibit a uniquely stable micellar structure, favorable interfacial behavior, rock-wetting character, viscoelasticity and cost-profitability. Gemini surfactant-assisted EOR solutions are expected to provide enhanced stability in comparison to conventional fluids, with the added advantage of minor operating investments and significant returns for petroleum producing companies. Gemini surfactants form an intermediary between conventional surfactants and polymeric materials, with desirable traits of both kinds of chemicals. Mechanisms associated with gemini surfactant-assisted EOR have been reported. In this review, the status, developmental trends and prospects of gemini (dimeric) surfactants, with respect to the needs of the petroleum industry have been elaborated. Though gemini surfactants have been used in numerous sectors, their application in EOR has been limited owing to unfamiliarity and commercial unavailability. Prospective gemini surfactant systems have been discussed herein to identify technical risks, calibrate reservoir simulation models, contribute to environmental responsibility and develop operating strategies to improve oil recovery/economics.
  • Data-driven analysis of climate change in Saudi Arabia: trends in temperature extremes and human comfort indicators

    Odnoletkova, Natalia; Patzek, Tadeusz (Journal of Applied Meteorology and Climatology, American Meteorological Society, 2021-06-30) [Article]
    AbstractWe have analyzed the long-term temperature trends and extreme temperature events in Saudi Arabia between 1979 and 2019. Our study relies on the high resolution, consistent and complete ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). We evaluated linear trends in several climate descriptors, including temperature, dewpoint temperature, thermal comfort and extreme event indices. Previous works on this topic used data from weather station observations over limited time intervals and did not include temperature data for recent years. The years 2010-2019 have been the warmest decade ever observed by instrumental temperature monitoring and comprise the eight warmest years on record. Therefore the earlier results may be incomplete and their results no longer relevant. Our findings indicate that over the past four decades, Saudi Arabia has warmed up at a rate that is 50% higher than the rest of land mass in the Northern Hemisphere. Moreover, moisture content of the air has significantly increased in the region. The increases of temperature and humidity have resulted in the soaring of dew point temperature and thermal discomfort across the country. These increases are more substantial during summers, which are already very hot compared to winters. Such changes may be dangerous to people over vast areas of the country. If the current trend persists into the future, human survival in the region will be impossible without continuous access to air conditioning.
  • Impact of fracture geometry and topology on the connectivity and flow properties of stochastic fracture networks

    Zhu, Weiwei; Khirevich, Siarhei; Patzek, Tadeusz (Water Resources Research, American Geophysical Union (AGU), 2021-06-27) [Article]
    In a low permeability formation, connectivity of natural and induced fractures determines overall hydraulic diffusivity in fluid flow through this formation and defines effective rock permeability. Efficient evaluation of fracture connectivity is a nontrivial task. Here we utilize a topological concept of global efficiency to evaluate this connectivity. We address the impact of key geometrical properties of stochastic fracture networks (fracture lengths, orientations, apertures and positions of fracture centers) on the macro-scale flow properties of a shale-like formation. Six thousand different realizations have been generated to characterize these properties for each fracture network. We find that a reduced graph of a fracture network, which consists of the shortest paths from the inlet nodes (fractures) to all outlet nodes, contributes most to fluid flow. 3D fracture networks usually have higher global efficiency than 2D ones, because they have better connectivity. All geometrical properties of fractures influence quality of their connectivity. Aperture distribution impacts strongly global efficiency of a fracture network, and its influence is more significant when the system is dominated by large fractures. Fracture clustering lowers global efficiency in both 2D and 3D fracture networks. Global efficiency of 2D and 3D fracture networks also decreases with the increasing exponent of the power-law distribution of fracture lengths, which means that the connectivity of the system decreases with an increasing number of small fractures. Realistic fracture networks, composed of several sets of fractures with constrained preferred orientations, share all the characteristics of the stochastic fracture networks we have investigated.

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