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Characterizing natural fractures has a decisive effect on production forecasts in fractured oil and gas reservoirs. Discrete Fracture Networks (DFN) constitutes the main modeling framework for fractured geosystems. However, myriads of uncertainties are enclosed prior modeling representative stochastic or deterministic DFN ensembles. This paper presents a novel methodology for DFN calibration and an efficacious field application, which incorporates Well-testing interpretation, Embedded Discrete Fracture Model (EDFM) framework, and numerical reservoir simulation. The proposed workflow starts with the DFN generation from seismic data, imaging logging data and core data. After multiple DFNs are modeled, well-test analysis is employed to calibrate the intrinsic properties of fractures at different locations. Then, these fracture networks are characterized dynamically by EDFM, which promotes capturing the optimal fracture model quickly screened. Finally, pressure and production history match are reached for the DFN realization that honors the optimal fracture model.

The current commercial technologies used to produce heavy oils and bitumen are carbon-, energy-, and wastewater-intensive. These make them to be out of line with the global efforts of decarbonisation. Alternative processes such as the toe-to-heel air injection (THAI) that works as an in situ combustion process that uses horizontal producer well to recover partially upgraded oil from heavy oils and bitumen reservoirs are needed. However, THAI is yet to be technically and economically well proven despite pilot and semi-commercial operations. Some studies concluded using field data that THAI is a low-oil-production-rate process. However, no study has thoroughly investigated the simultaneous effects of start-up methods and wells configuration on both the short and long terms stability, sustainability, and profitability of the process. Using THAI validated model, three models having a horizontal producer well arranged in staggered line drive with the injector wells are simulated using CMG STARS. Model A has two vertical injectors via which steam was used for pre-ignition heating, and models B and C each has a horizontal injector via which electrical heater and steam were respectively used for pre-ignition heating. It is found that during start-up, ultimately, steam injection instead of electrical heating should be used for the pre-ignition heating. Clearly, it is shown that model A has higher oil production rates after the increase in air flux and also has a higher cumulative oil recovery of 2350 cm3 which is greater than those of models B and C by 9.6% and 4.3% respectively. Thus, it can be concluded that for long-term projects, model A settings and wells configuration should be used. Although it is now discovered that the peak temperature cannot in all settings tell how healthy a combustion front is, it has revealed that model A does indeed have far more stable, safer, and efficient combustion front burning quality and propagation due to the maintenance of very high peak temperatures of mostly greater than 600 °C and very low concentrations of produced oxygen of lower than 0.4 mol% compared to up to 2.75 mol% in model C and 1 mol% in model B. Conclusively, since drilling of, and achieving uniform air distribution in horizontal injector (HI) well in actual field reservoir are costly and impracticable at the moment, and that electrical heating will require unphysically long time before mobilised fluids reach the HP well as heat transfer is mainly by conduction, these findings have shown decisively that the easy-and-cheaper-to-drill two vertical injector wells configured in a staggered line drive pattern with the horizontal producer should be used, and steam is thus to be used for pre-ignition heating.

Coalbed methane (CBM) is produced before coal mining at the Qinshui Basin in China to utilize CBM and reduce CH4 volume fraction for coal mining. However, the volume fraction of CH4 often reaches the range between lower and upper explosion limits after CBM production, which is a great threat to coal mining safety. In previous work, we analyzed the feasibility of injecting CO2 into coalbeds to control CH4 volume fraction for mining safety and simultaneously enhancing CBM recovery. In this paper, we extended our work to propose a model to calculate the critical CO2 volume fraction for CO2 injection. We simplified the gas mixture during coal mining as the CO2/CH4/air mixture. The model of the critical CO2 volume fraction was then built based on the explosion limit formula for the CO2/CH4/N2 mixture. The formula for the critical CO2 volume was derived using the critical CO2 volume fraction. The model of the critical CO2 volume fraction was applied in a CBM reservoir at the South Shizhuang Block in the Qinshui Basin. The CO2 injection rate for this block was optimized to obtain the highest CBM recovery using the reservoir simulation method. Results show that the critical CO2 volume fraction is 7.97%, which makes the CH4 volume fraction out of the explosion limits. The optimum CO2 injection rate for this block is 8000m3/d which improves the CBM recovery up to 86.24%.

This study extends an integrated field characterization in Eagle Ford by optimizing the numerical reservoir simulation of highly representative complex fractured systems through embedded discrete fracture modeling (EDFM). The bottom-hole flowing pressure was history-matched and the field production was forecasted after screening complex fracture scenarios with more than 100 000 fracture planes based on their propped-type. This work provided a greater understanding of the impact of complex-fractures proppant efficiency on the production. After compaction tables were included for each propped-type fracture group, the estimated pressure depletion showed that the effective drainage area can be smaller than the complex fracture network if modeled and screened by the EDFM method rather than unstructured gridding technique. The essential novel value of this work is the capability to couple EDFM with third-party fracture propagation simulation automatically, considering proppant intensity variation along the complex fractured systems. Thus, this work is pioneer to model complex fracture propagation and well interference accurately from fracture diagnostics and pseudo 3D fracture propagation outcomes for multiple full wellbores to capture well completion effectiveness after myriads of sharper field simulation cases with EDFM.

In shale gas reservoir development, determination of hydraulic fracture geometry for horizontal wells is a demanding yet challenging task. One type of approach for hydraulic fracture optimization is based on reservoir simulation. To improve optimization efficiency and accuracy, an automatic and robust procedure integrating the gradient descent method with gas reservoir simulation has been developed. Fractured reservoir models were constructed using the “Multiple INteracting Continua” method, whereby an in-house shale gas reservoir simulator was implemented to model multiple gas transport mechanisms including non-Darcy flow, gas desorption, Klinkenberg effect, and geomechanical effect. The optimization procedure was first validated against two ideal cases and then applied to two realistic cases to optimize fracture spacing, half-length, and dimensionless fracture conductivity. It showed that the optimization results depend on optimization objective, reservoir property, natural fractures, economics and termination criteria. This gradient descent assisted fracture optimization procedure can achieve significant computational reduction and high prediction accuracy for various shale gas reservoir cases. Cited as : Chen, J., Wang, L., Wang, C., Yao, B., Tian, Y., Wu, Y.-S. Automatic fracture optimization for shale gas reservoirs based on gradient descent method and reservoir simulation. Advances in Geo-Energy Research, 2021, 5(2): 191-201, doi: 10.46690/ager.2021.02.08

The oil and gas fields are commonly developed with a group of production wells. Therefore, it can be essential for the industries to predict the performance of the production wells in order to optimize the development strategies. In practice, it frequently happens that we only hope to study the performance of a single production well. In such cases, it can be time consuming to run the reservoir simulation with the entire reservoir model to study the well performance. Hence, it can be preferred to determine the control volume (or drainage volume) of the target well from the entire reservoir and run the simulation with the small control volume to reduce the simulation cost. However, an irregular layout of the production wells and the heterogeneity of reservoir properties, which can be commonly observed in real field cases, can induce a stringent barrier for one to determine the control volumes. At present, we are still lacking a method to determine the control volumes of the production wells considering well distribution and reservoir heterogeneities. In order to overcome such a barrier, the authors proposed a new approach to divide the entire reservoir into small control volumes on the basis of the fast marching method (FMM). This approach is validated by comparing the simulation outputs of the target well calculated only with the determined control volume to those calculated with the entire reservoir model. The calculated results show that using the control volume that is determined with the proposed method to calculate the well performance can yield results that agree well with the results that are calculated with the entire reservoir model. This indicates that this proposed method is reliable to determine the control volume of the production wells. In addition, the calculated results in this work show that changing fracture length exerts a slight influence on the control volumes if the length of all fractures is increased, whereas, if only one of the fracture lengths is increased, the control volume of the corresponding well will be significantly increased. The number of the production wells and the distribution of the production well can noticeably influence the control volumes of the production wells. The findings of this study can help for optimizing the well spacing, estimating the ultimate recovery, and reducing the computational cost.

Since the discovery of methane hydrate in marine sands in 1999, our understanding of methane-hydrate-bearing sediments has progressed rapidly. Comprehensive studies of methane hydrate deposits in the Nankai Trough have made a great contribution to this research. Reservoir evaluation combining geophysical logging with pressure core analysis has become the standard protocol for exploring methane-hydrate-bearing sands, revealing that the effective permeability of methane-hydrate-bearing sands lies in the range of 1-100 md, even if the hydrate saturation reaches high value of 50-80 % in pores. Numerical and experimental studies of gas production have demonstrated that fluid flow and heat transfer are key rate-determining factors for field-scale depressurization-induced gas production. In that sense, the high permeability of methane-hydrate-bearing sands indicates the applicability of depressurization as a primary gas production method; however, a lack of heat limits hydrate dissociation and thus the recovery factor cannot exceed approximately 40 %. Thus, enhanced recovery methods are necessary to increase viability of commercialization. Experimental and numerical studies have shown that hydraulic fracturing enhances production rate, and that cyclic depressurization assisted by geothermal and deep depressurization using the latent heat of ice formation are possible means by which the enhancement of the recovery factor can be achieved while maintaining energy efficient production.

The effect of poroelastic properties of the shale matrix on gas storage and transport mechanisms has gained significant attention, especially during history-matching and hydrocarbon production forecasting in unconventional reservoirs. The common oil and gas industry practice in unconventional reservoir simulation is the extension of conventional reservoir simulation that ignores the dynamic behavior of matrix porosity and permeability as a function of reservoir effective net stress. This approach ignores the significant impact of the poroelastic characteristics of the shale matrix on hydrocarbon production. The poroelastic characteristics of the shale matrix highly relate to the shale matrix geomechanical properties, such as the Young’s Modulus, Poisson’s ratio, bulk modulus, sorption behavior, total organic content (TOC), mineralogy and presence of natural fractures in the multi-scale shale structure. In this study, in order to quantify the effect of the poroelasticity of the shale matrix on gas production, a multi-continuum approach was employed in which the shale matrix was divided into organic materials, inorganic materials and natural fractures. The governing equations for gas transport and storage in shale were developed from the basic fundamentals of mass and momentum conservation equations. In this case, gas transport in organics was assumed to be diffusive, while gas transport in inorganics was governed by convection. Finally, a fracture system was added to the multi-scale shale gas matrix, and the poroelastic effect of the shale matrix on transport and storage was investigated. A modified Palmer and Mansoori model (1998) was used to include the pore compression, matrix swelling/shrinkage and desorption-induced deformation of shale organic matter on the overall pore compressibility of the shale matrix. For the inorganic part of the matrix, relations between rock mechanical properties and the pore compressibility were obtained. A dual Langmuir–Henry isotherm was also used to describe the sorption behavior of shale organic materials. The coupled governing equations of gas storage and transport in the shale matrix were then solved using the implicit finite difference approach using MATLAB. For this purpose, rock and fluid properties were obtained using actual well logging and core analysis of the Marcellus gas well. The results showed the importance of the poroelastic effect on the pressure response and rate of gas recovery from the shale matrix. The effect was found to be mainly due to desorption-induced matrix deformation at an early stage. Coupling the shale matrix gas production including the poroelastic effect in history-matching the gas production from unconventional reservoirs will significantly improve engineering completion design optimization of the unconventional reservoirs by providing more accurate and robust production forecasts for each hydraulic fracture stage.

For stress-sensitive reservoirs, understanding the characteristics of the inflow performance relationship is vital for evaluating the performance of a well and designing an optimal stimulation. In this study, a reservoir simulator was used to establish the inflow performance relationship of a well for a wide variety of reservoirs and wellbore conditions. First, a base case was simulated using typical reservoir, wellbore, and fluid parameters. Subsequently, variations from the base case were investigated. The results of the simulation indicate that the dimensionless inflow performance relationship in the stress-sensitive reservoir is similar to the Vogel-type inflow performance relationship, which is used for evaluating the productivity of a vertical well in a solution-gas-drive reservoir. Unlike the two-phase flow in a solution-gas-drive reservoir, the nonlinear characteristic of the inflow performance relationship in stress-sensitive reservoirs is caused by stress-dependent permeability. Furthermore, the stress sensitivity level is the only parameter that affects the nonlinearity coefficient of the dimensionless inflow performance relationship equation. The nonlinearity coefficient was plotted against the stress sensitivity index, and the nonlinearity coefficient was found to be linearly proportional to the stress sensitivity index. This study provides a realistic and less expensive methodology to evaluate the reservoir productivity of stress-sensitive reservoirs when the reservoir stress sensitivity level is known and to predict the reservoir stress sensitivity level when the inflow performance relationship of the stress-sensitive reservoirs is known. Cited as : Wang, F., Gong, R., Huang, Z., Meng, Q., Zhang, Q., Zhan, S. Single-phase inflow performance relationship in stress-sensitive reservoirs. Advances in Geo-Energy Research, 2021, 5(2): 202-211, doi: 10.46690/ager.2021.02.09

An appropriate well spacing plan is critical for the economic development of shale gas reservoirs. The biggest challenge for well spacing optimization is interpreting the subsurface uncertainties associated with hydraulic and natural fractures. Another challenge is the existence of complex natural fractures. This work applied an integrated well spacing optimization workflow in shale gas reservoirs of the Sichuan Basin in China with both hydraulic and natural fractures. The workflow consists of five components: data preparation, reservoir simulation, estimated ultimate recovery (EUR) analysis, economic calculation, and well spacing optimization. Firstly, the multiple realizations of thirteen uncertain parameters of matrix and fractures, including matrix permeability and porosity, three relative permeability parameters, hydraulic fracture height, half-length, width, conductivity, water saturation, and natural fracture number, length, and conductivity, were captured by the assisted history matching (AHM). The fractures were modeled by the embedded discrete fracture model (EDFM) accurately and efficiently. Then, 84 AHM solutions combining with five well spacing scenarios from 517 ft to 1550 ft would generate 420 simulation cases. After reservoir simulation of these 420 cases, we forecasted the long-term gas production for each well spacing scenario. Gas EUR degradation and well interference would imply the critical well spacing. The net present value (NPV) for all scenarios would be calculated and trained by K -nearest neighbors (KNN) proxy to better understand the relationship between well spacing and NPV. In this study, the optimum well spacing was determined as 793 ft, corresponding with a maximum NPV of 18 million USD, with the contribution of hydraulic fractures and natural fractures.

This paper presents an approach to optimize the recovery factor and sweep efficiency in a waterflooding process by automating the optimum injection rate calculations for water injectors using streamline simulation. A streamline simulator is an appropriate tool for modern waterflood management and can be used to determine the dynamic interaction between injector and producer pairs, which will vary over time based on sweep efficiency and operational changes. A streamline simulator can be used to identify injectors, which are not supporting production and contributing mainly to water producing wells. Streamlines illustrate natural fluid-flow paths in the reservoir, which are based on fluid properties, rock properties, well distribution and well rates across the reservoir. A bundle of connected streamlines can provide the oil in place between an injector/producer pair at any given time during a simulation run. Thus, the well pair recovery factors for each injector/producer pair, the produced water cut and the weighting factor for each injector are determined. Multiplying this weighting factor by the injection rates determines the new injection rate for each injector. For a well pair water cut that is lower than the average field water cut, the injection rate will be increased and vice versa. Given a finite volume of injection water, there will be a re-allocating of water from a well pair with a low recovery factor and high water cut and redistributing the water to injectors supporting low water cut producers, thus maximizing the recovery factor and reducing the field water production. The described approach is an automated procedure during the reservoir simulation run, making it appropriate for full field waterflood optimization with many injectors and producers in high-resolution heterogeneous brown reservoirs. This approach can reduce the water cut and increase the recovery factor and extend the life of the waterflooded oil fields. It was initially tested with a synthetic model and later with an actual reservoir model, which will be described in this paper.

Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off permeability and porosity values. These values directly affect the calculation of net pay thickness for each layer in the reservoir and consequently affect the target of estimating reservoir initial oil in place (IOIP). Also, the main challenge to the static modeling of such reservoirs is dealing with tight reservoir characteristics which cause major reservoir heterogeneity and complexities that are problematic to the process of modeling reservoir simulation. Twenty seven porosity and permeability measurements from Sadi/Tanuma reservoir were used to validate log interpretation data for model construction. The results of the history matching process of the constructed dynamic model is also presented in this paper, including data related to oil production, reservoir pressure, and well flowing pressure due to available production.

Summary In this paper, we aim to enhance our understanding of the multiphysical processes in carbon dioxide (CO2)-enhanced-oil-recovery (EOR) (CO2-EOR) operations using a modeling approach. We present the development of a comprehensive mathematical model for thermal/hydraulic/mechanical (THM) simulation of CO2-EOR processes. We adopt the integrated-finite-difference method to simulate coupled THM processes during CO2-EOR in conventional and unconventional reservoirs. In our method, the governing equations of the multiphysical THM processes are solved fully coupled on the same unstructured grid. To rigorously simulate the phase behavior of a three-phase, nonisothermal system, a three-phase flash-calculation module, dependent on the minimization of Gibbs energy, is implemented in the simulator. The simulator is thus applicable to both miscible and immiscible flooding simulations under isothermal and nonisothermal conditions. We have investigated the effect of cold-CO2 injection on injectivity as well as on phase behavior. We conclude that cold-CO2 injection is an effective way to increase injectivity in tight oil reservoirs and reduces overriding effect in high-water-bearing reservoirs. Using the developed general simulation framework, we have discovered and studied several intriguing multiphysical phenomena that cannot be captured by commonly used reservoir simulators, including the temperature-decreasing phenomenon near the production well and the permeability-enhancement effect induced by the thermal unloading process. These phenomena can be captured only by the fully coupled multiphysical model. The novelty of this paper lies in its integration of multiple physical simulation modules to form a general simulation framework to capture realistic flow and transport processes during CO2 flooding, and in revealing the behavior of cold-CO2 injection under THM effects.

The oil density at the bubble point is an important thermodynamic property required in reservoir simulation and production engineering. A higher-accuracy estimate of this property would improve the accuracy of reservoir and production engineering calculations. The bubble point oil density is obtained either from separator tests of reservoir fluids or from differential gas liberation tests. A new procedure utilizing separator and differential tests is proposed whereby the experimental data yield a unique value with high accuracy for the bubble point oil density. A consistent correction of other PVT properties, which are influenced by the bubble point oil density, is required to reflect the unique density value. A quantitative quality control index is defined to measure the quality of PVT laboratory reports. This is achieved by utilizing the unique property of the bubble point oil density, which is usually ignored.

Актуальность исследования обусловлена необходимостью изучения сложных неоднородных трещиноватых карбонатных коллекторов, которые являются одним из источников добычи углеводородов в условиях истощающихся ресурсов терригенных коллекторов. Цель работы - пересмотр концептуальной модели месторождения, поскольку текущая модель не в полной мере описывает фактическое поведение пласта, затрудняет подбор технологических решений для оптимизации разработки месторождения, а также не позволяет дать оценку потенциальной эффективности принятых решений. Объекты: залежь пласта M1 газоконденсатно-нефтяная, массивного типа, с газовой шапкой, приуроченная к выступу карбонатного фундамента девонского возраста на Арчинском месторождении. Методы: интегрированный подход к анализу результатов проведенных исследований, аналитические и численные расчеты, систематизация, обобщение, структуризация исходной информации по месторождению, моделирование нескольких концепций, сопоставление с фактическими данными. Результаты. Авторы представили альтернативный сценарий геологического строения и основных механизмов добычи рассматриваемой залежи, так как текущая модель не описывала фактическое поведение пласта, а результаты специальных исследований свидетельствуют о сложном геологическом строении комплекса, что затрудняло детальный прогноз распространения фильтрационно-емкостных свойств коллектора. Кроме того, разрешающая частота сейсмических методов ограничивает применение полного спектра современных технологий для прогноза продуктивности, латерального распространения трещиноватости и петрофизических характеристик коллектора. Обновленная концептуальная модель предполагает, что коллектор продуктивного пласта Арчинского месторождения представлен породами двух типов: известняками и бокситоподобными породами, по данным описания керна и геофизических исследований. Трещиноватость известняков, обусловленная тектоническим фактором, характеризуется равномерным распределением по разрезу и площади месторождения, и является наиболее влияющим параметром на технологические показатели разработки. Технологический режим эксплуатации некоторых скважин и высокие депрессии приводят к конусообразованию посредствам системы трещин, обеспечивающих гидродинамическую связь продуктивных и водонасыщенных интервалов. The relevance of the research is caused by the need to study complex, heterogeneous fractured carbonate reservoirs, which are one of the sources of hydrocarbon production in an age of depleted clastic reservoirs resources. The main aim of the research is the revision of the conceptual model of the field, since the current model does not fully describe the actual behavior of the formation, complicates the selection of technological solutions for field development and optimizing, and does not allow an assessment of the potential effectiveness of the decisions made. Object of the research is the M1 reservoir is gas-condensate-oil, massive type, with a gas cap, confined to the ledge of the carbonate basement of the Devonian age at the Archinsky deposit. Methods: an integrated approach to the analysis of research results, analytical and numerical calculations, systematization, generalization, structuring of initial information on the field, simulation of several concepts, comparison with actual data. Results. The authors presented an alternative scenario of the geological structure and the main production mechanisms of the reservoir. Since the current model did not describe the actual behavior of the reservoir, the results of special studies indicate a complex geological structure of the complex, which made it difficult to predict the distribution of reservoir properties. Moreover, the resolving frequency of seismic data limits the use of a full range of modern technologies for predicting productivity, lateral propagation of fractures, and petrophysical characteristics of a reservoir. The updated conceptual model assumes that according to the core description and geophysical studies of the Archinsky field, rocks of two types represent it: limestone and bauxite-like rocks. Fracturing of limestones, caused by the tectonic factor, is characterized by a uniform distribution over the section and the area of the field, and is the most influential parameter on the technological indicators of development. The technological mode of some wells and high depressions lead to water conning through a system of fractures that provide a hydrodynamic relation between productive and water-saturated intervals.

Oil displacement by a miscible fluid in a porous medium, which is related to injection of hydrocarbonic gas into an oil reservoir, is investigated. A compositional model is used to describe flow of multicomponent mixtures through the porous medium. The thermophysical properties of the mixtures are given by the equation of state of the van der Waals type. The reservoir simulation software for compositional modeling of flow through a porous medium is developed within the framework of this model. The efficiencies of oil displacement from the porous medium by methane or water are compared using the above software. It is shown that in the initial stages of injection oil displacement by water is more efficient under a fixed volume flow rate of the injected fluid. However, in the last stages gas injection becomes more efficient for displacement of light hydrocarbon components.

Reservoir simulation models are used to design oil field developments, estimate efficiency of geological and engineering operations and perform prediction calculations of long-term development performances. A method has been developed to adjust the permeability cube values during reservoir model history-matching subject to the corederived dependence between rock petrophysical properties. The method was implemented using an example of the Bobrikovian formation (terrigenous reservoir) deposit of a field in the Solikamskian depression. A statistical analysis of the Bobrikovian formation porosity and permeability properties was conducted following the well logging results interpretation and reservoir modelling data. We analysed differences between the initial permeability obtained after upscaling the geological model and permeability obtained after the reservoir model history-matching. The analysis revealed divergences between the statistical characteristics of the permeability values based on the well logging data interpretation and the reservoir model, as well as substantial differences between the adjusted and initial permeability cubes. It was established that the initial permeability was significantly modified by manual adjustments in the process of history-matching. Extreme permeability values were defined and corrected based on the core-derived petrophysical dependence KPR = f(KP) , subject to ranges of porosity and permeability ratios. By using the modified permeability cube, calculations were performed to reproduce the formation production history. According to the calculation results, we achieved convergence with the actual data, while deviations were in line with the accuracy requirements to the model history-matching. Thus, this method of the permeability cube adjustment following the manual history-matching will save from the gross overestimation or underestimation of permeability in reservoir model cells.

Petrophysical rock typing plays a major role in carbonate reservoir characterization and geological modeling for reservoir simulation. In this study, based on 1120 samples of mercury-injection capi...

SummaryIn the development of fractured reservoirs, geomechanics is crucial because of the stress sensitivity of fractures. However, the complexities of both fracture geometry and fracture mechanics make it challenging to consider geomechanical effects thoroughly and efficiently in reservoir simulations. In this work, we present a coupled geomechanics and multiphase-multicomponent flow model for fractured reservoir simulations. It models the solid deformation using a poroelastic equation, and the solid deformation effects are incorporated into the flow model rigorously. The noticeable features of the proposed model are it uses a pseudocontinuum equivalence method to model the mechanical characteristics of fractures; the coupled geomechanics and flow equations are split and sequentially solved using the fixed-stress splitting strategy, which retains implicitness and exhibits good stability; and it simulates geomechanics and compositional flow, respectively, using a dual-grid system (i.e., the geomechanics grid and the reservoir-flow grid). Because of the separation of the geomechanics part and the flow part, the model is not difficult to implement based on an existing reservoir simulator. We validated the accuracy and stability of this model through several benchmark cases and highlighted the practicability with two large-scale cases. The case studies demonstrate that this model is capable of considering the key effects of geomechanics in fractured-reservoir simulation, including matrix compaction, fracture normal deformation, and shear dilation, as well as hydrocarbon phase behavior. The flexibility, efficiency, and comprehensiveness of this model enable a more realistic geocoupled reservoir simulation.

The main parameter that drives oil industry contract investment and set up economic feasibility study for approving field development plan is hydrocarbon reservoir potential. So a qualified experience should be deeply afforded to correctly evaluate hydrocarbons reserve by applying different techniques at each phase of field management, through collecting and using valid and representative data sources, starting from exploration phase and tune-up by development phase. Commonly, volumetric calculation is the main technique for estimate reservoir potential using available information at exploration stage which is quite few data; in most cases, this technique estimate big figure of reserve. In this study case, volumetric calculation estimate gas initial in place (GIIP) value almost two times bigger than other techniques estimation of actual reservoir potential; it is a result of Asphiltena “Bitumen” existing in reservoir interval which occupied part of matrix pore and fill some fractures. This investigation is raised up at early field production life: material balance calculation and run simulation analysis are applied to re-assessment and tune-up reservoir potential; both techniques are set up almost same GIIP value which principally tuned to actual reservoir dynamic energy behavior. Finally, material balance should be viewed as a complement to simulation, not as a competing approach, and using both to improve analysis of hydrocarbon reservoirs.

Industrial development of extra and super heavy oil as an important energy resource substitute has been achieved worldwide. Steam-assisted gravity drainage (SAGD) is one of the most important recovery methods for extra and super heavy oil reservoirs. In this review paper, the following points of SAGD have been discussed: (1) mechanism, influencing factors and application criteria; (2) field application and experimental study; (3) analytical and reservoir simulation models; and (4) current research progress and future application of multi-medium-assisted SAGD. This study gives an overview of the current status and challenges of and solutions for the SAGD technology and provides reference for the effective recovery of extra and super heavy oil reservoirs.

In recent days, waterflooding activities carried out as a part of secondary recovery. Before performing waterflooding, engineers have to perform reservoir simulation first to predict reservoir performance in order to waterflood. Generally, reservoir simulation is conducted by using numerical simulation method. Numerical simulation gives precise results although it depens on the availiability, quality, and quantity of reservoir characteristic and injection operation data. In addition, numerical simulation also time-consuming and quite complex to use. Proxy model is kind of machine learning. It’s able to predict performance of waterflooding quickly and easier to use. The result isn’t differ too much with numerical simulation method. Proxy model is an equation model that construct form quite many experiment data. This research is trying to predict performance of normal 5 spot waterflooding in reservoir with channeling deltaic sand sedimentation by using proxy model. The proxy model will be tested on a real field case. The results indicate that proxy model is able, faster, reliable and easy to use to predict waterflooding performance in such type of reservoir.

To analyze the stability of the hydrocarbon wells, it is necessary to determine the exact value of in situ vertical and minimum and maximum horizontal components of the stress. Determination of the in situ stress in well planning is vital in detecting and preventing the occurrence of the instability in the walls of the drilled wells and fluid loss. Evaluation of the magnitude of in situ stress is required for optimizing drilling, well completion and reservoir simulation. Hence, access to the complete information on the in situ stresses while drilling is essential, especially in naturally fractured zones for prospective infill drilling in the field development plans. In this paper, the value of the in situ stress is determined for two wells drilled in the South Pars field, Iran. With information on the in situ stress and the pore pressure, the mud window for different depths of this well is obtained. The appropriate mud density and overpressure zone for safe drilling in the borehole are also determined.

Summary Field-scale representation of highly heterogeneous reservoirs remains a challenge in numerical reservoir simulation. In such reservoirs, detailed geological models are important to properly represent key heterogeneities. However, high computational costs and long simulation run times make these detailed models unfeasible to use in dynamic evaluations. Therefore, the scaling up of geological models is a key step in reservoir-engineering studies to reduce computational time. Scaling up must be carefully performed to maintain integrity; both truncation errors and the smoothing of subgrid heterogeneities can cause significant errors. This work evaluates the latter—the effect of averaging small-scale heterogeneities in the upscaling process—and proposes a new upscaling technique to overcome the associated limitations. The technique is dependent on splitting the porous media into two levels guided by flow- and storage-capacity analysis and the Lorenz coefficient (LC), both calculated with static properties (permeability and porosity) from a fine-scale reference model. This technique allows the adaptation of a fine highly heterogeneous geological model to a coarse-scale simulation model in a dual-porosity/dual-permeability (DP/DP) approach and represents the main reservoir heterogeneities and possible preferential paths. The new upscaling technique is applied to different reservoir-simulation models with water injection and immiscible gas injection as recovery methods. In deterministic and probabilistic studies, we show that the resulting coarse-scale dual-permeability models are more accurate and can better reproduce the fine-scale results in different upscaling ratios (URs), without using any simulation results of the reference fine-scale simulation models, as some of the current alternative upscaling methods do.

Relative permeability (kr) and the capillary pressure (Pc) are the central key elements defining the multiphase fluids flow behavior in the porous media. However, the dynamic capillarity should consider the dynamic relative permeability and the dynamic capillary pressure while performing waterflooding process in extremely low permeable formations. In order to improve the oil production, the advanced horizontal well drilling along with multiple hydraulic fracturing is generally instigated to penetrate the unconventional resources. The aim of this study is to consider the dynamic capillarity in a commercial reservoir simulation, while utilizing the data gained from the dynamic and steady experiments of the relative permeability and the capillary pressure impacts during waterflooding process in the core plugs of unconventional tight oil reservoirs. The commercial reservoir simulation conducted sensitivity analyses using Computer Modeling Group simulator. The outcomes show that the well production of the reservoir is overestimated while implementing steady data for forecasting due to which the oil saturation decreases more equally and further rapidly. Additionally, the forecast of the well production estimated to breakthrough sooner. However, neglecting the dynamic capillarity causes a huge breakthrough of water influx. Therefore, the core objective of this study is to probe the consequences of taking into consideration the dynamic capillarity in ultra-low permeable formations while giving an alternative perspective to forecast the production of the hydraulically fractured unconventional tight oil reservoirs.

Chemical Enhanced Oil Recovery (EOR) processes comprise a number of flooding techniques aimed at increasing the operational life of mature oilfields. Among these, polymer flooding is one of the most developed; its functionality is to increment the aqueous viscosity, avoiding the formation of viscous fingering. Reservoir simulators consider this influence as well as other physical properties (e.g., adsorption, permeability reduction). However, the polymer degradation is usually not considered even though it plays a critical role in the viscosity. In this paper this mechanism is analyzed and coupled with the previously mentioned physical phenomena in order to present a complete study of their influence in the EOR process. Moreover, since a fully second-order accuracy scheme is used along with a Total Variation Diminishing (TVD) flux-limiting function, the influence of the latter on the recovery factor is also discussed. Results showed that the negative effect of the polymer adsorption was the most relevant physical phenomenon in terms of the oil recovery. Furthermore, the analysis of the discretization of the differential equations showed that traditional, linear first-order schemes created numerical diffusion affecting negatively the macroscopic sweeping efficiency, which disappeared when TVD techniques were used. Reservoir simulators allow determining the desired designing properties for future polymers in relationship with the characteristics of the oilfield to be exploited.

Summary Fractured vuggy reservoir is a typical type of carbonate reservoir. The 3D complex fracture networks and Stokes flow inside vugs make fractured vuggy reservoir simulation remain a challenging problem. Most of the proposed models in previous studies are computation consuming, which cannot meet with the demand of field application. In this paper, a novel and efficient hybrid model, consisting of a modified embedded discrete fracture model (EDFM) and a vug model, is proposed to simulate multiphase flow in 3D complex fractured vuggy reservoirs. The modified EDFM improves the fracture-discretization process by using two sets of independent grids for matrix and fracture systems, which promotes the modeling of 3D complex fractures in real geological structures. Meanwhile, the vug model simplifies the coupled porous-free flow with the assumption of multiphase instantaneous gravity differentiation. The accuracy of the modified EDFM and the vug model is demonstrated by comparing the results with those of the conventional EDFM and volume of fluid (VOF) method. After that, a series of case studies, including three conceptual fracture-vug unit models and a real field model, have been conducted to test the proposed hybrid model. The results of the three fracture-vug unit models indicate the significant effect of a local fracture-vug structure on the flow characteristics and production performance. Finally, the application with a real field model with 3D complex fracture and vug geometries further verifies the practicability of our proposed model in real fractured vuggy reservoirs.

The increasing energy demand has to be met while we transitioned to a decarbonized energy future. Heavy oil and bitumen reserves are urgently needed to be developed to ensure that a smooth transition is provided. In this work, field-scale kinetics parameters are used to study the effect of reservoir pay thickness on the performance of toe-to-heel air injection (THAI) process. Air was injected at constant rate into three different models with the thicknesses of 24 m, 16 m, and 8 m, respectively. The oil produced is slightly affected by the reservoir thickness. It is found that the lower the reservoir thickness, the larger the cumulative air-to-oil ratio (cAOR), indicating that heat loss increases with the decrease in the reservoir thickness. This trend is similar to steam-based processes. At constant air injection flux, it is found that both the cumulative oil produced and the cAOR decrease with the decrease in the reservoir thicknesses. This decrease is attributed to the decrease in the rate of heat generation in the thinner reservoirs, which in turn results in lower combustion zone temperature and thus lower temperature gradients between the reservoir and the overburden and the reservoir and the underburden. Consequently, a more general conclusion is that decreasing the air injection rate by the same factor the reservoir thickness is decreased (i.e. keeping the air injection flux constant) results in a more economical THAI process operation compared to when the air injection rate is kept constant (i.e. allowing increase in air injection flux).

This study is intended to expand the scope of microbial enhanced oil recovery (MEOR) simulation studies from 1D to field scale focussing on fluid viscosity variation and heterogeneity that lacks in most MEOR studies. Hence, we developed a model that incorporates: (1) reservoir simulation of microbe-induced oil viscosity reduction and (2) field-scale simulation and robust geological uncertainty workflow considering the influence of well placement. Sequential Gaussian simulation, co-kriging and artificial neural network were used for the petrophysical modelling prior to field-scale modelling. As per this study, the water viscosity increased from 0.5 to 1.72 cP after the microbe growth and increased biomass/biofilm. Also, we investigated the effect of the various component compositions and reaction frequencies on the oil viscosity and possibly oil recovery. For instance, the fraction of the initial CO2in the oil phase (originally in the reservoir) was varied from 0.000148 to 0.005 to promote the reactions, and more light components were produced. It can be observed that the viscosity of oil reduced considerably after 90 days of MEOR operation from an initial 7.1–7.07 cP and 6.40 cP, respectively. Also, assessing the pre- and post-MEOR oil production rate, we witnessed two main typical MEOR field responses: sweeping effect and radial colonization occurring at the start and tail end of the MEOR process, respectively. MEOR oil recovery factors varied from 28.2 to 44.9% OOIP for the various 200 realizations. Since the well placement was the same for all realizations, the difference in the permeability distribution amongst the realizations affected the microbes’ transport and subsequent interaction with nutrient during injection and transport.

CO2 storage is a greenhouse gas mitigation instrument for many countries. In this paper, we investigate the possibility of CO2 storage in the region of the Precaspian basin using the compositional flow model that was verified by the data of the Frio pilot project, USA. We use local grid refinement in the commercial reservoir simulator. In the reservoir simulation for data of the Frio Pilot project, we have achieved a good history matching of well pressure. Different scenarios were tested, and post-injection migration was shown for both case studies. The long-term reservoir simulation shows the potential amount of trapped CO2 by residual and dissolved trapping mechanisms in the Precaspian basin. The performed uncertainty study covered the uncertainty of the model’s parameters resulting in P10, P50 and P90 cases in terms of the amount of trapped CO2.

Steadily decreasing oil production due to the maturation of oil fields and generally low energy commodity prices in Trinidad and Tobago (TT) have highlighted the need for more economical methods of enhanced oil recovery. These factors have also stimulated advances in research on the possible utilization of Enhanced Oil Recovery (EOR) technologies in TT. Estimates have shown that there is in excess of 1 billion barrels of oil in place (OIP) in reserves located in South West Trinidad where suitable EOR techniques can be employed to produce oil from these reserves. This study evaluated the outcomes after the application of various EOR techniques including CO2, waterflood (low and high salinity), Xanthan gum (XG) polymer slug, and polymer gel slug (low and high salinity) on the matured EOR 33 reservoir located in the lower Forest sands in Southern Trinidad. The simulated performance characteristics were obtained digitally utilizing the compositional reservoir simulation modelling (CMG-GEM) software where values of oil recovery %, reservoir pressure, and water cut % were obtained for each EOR technique. A comparison of the performance attributes was used to determine the best EOR option for the EOR 33 reservoir. A novel experimental and simulation approach was employed. The nature of the adsorption interaction between XG and gravel packed sand was studied in the laboratory and the Langmuir coefficients were generated for interactions at different salinities which were then incorporated into the simulation protocols to produce enhanced EOR projections. The results indicated that all the EOR strategies applied to EOR 33 resulted in an improvement in the oil recovery % (ranging between 28 and 54%). Compared to the CO2, water flood, and polymer flood strategies, the gel slug polymer flooding strategy resulted in the highest oil recovery factors with a maximum value of approximately 54% occurring at 1000 ppm NaCl. This strategy also yielded an associated water cut of 97% and a pressure of 617 psi demonstrating that this combination is the best EOR strategy for use in the EOR 33 reservoir and is an appropriate choice for process of optimizing oil recovery within these fields. This study also highlights the significant potential for the use EOR methods in heavy oil reserves located in South West Trinidad.

Viscosity is defined as the resistance of the fluid to flow. It plays a very significant role in most oil and gas engineering applications. The measured viscosity for any crude oil at surface condition is called by the dead oil viscosity, where the dead oil viscosity is a function in any correlation to calculate the viscosity of the crude oil. Thus, the dead oil viscosity is important in most applications related to the petroleum engineering. Accordingly, a new mathematical and artificial neural network (ANN) dead oil viscosity correlations were developed for Libyan crudes and compared with renowned dead oil viscosity correlations using 104 samples from different reservoirs. The evaluation in this study has been done by statistical and graphical error analysis. The results shown that the ANN model has proven to be a useful tool for predicting where the ANN model has given the best result with low error AAD was 14.40509 % and R^2 was 95.91%. The ANN model and mathematical model gave the lowest error when they compared with different empirical correlations.

The demand for crude oil is continuously increasing every year, and the discovery of new oil reservoirs is declining. Crude oil recovery from the mature and developed fields is somewhere between 20 and 40% of the original oil in place. Therefore, it is necessary to boost the production from the existing mature fields. Secondary recovery of hydrocarbon involves techniques that compensate the natural energy of the reservoir by injecting fluids, usually water or gas. Tertiary recovery methods are implemented to recover the crude oil trapped within the capillaries of the reservoir rocks. Tertiary recovery is the process in which different combinations of chemicals or thermal energy, or microbes are infused into the reservoir, which alters the reservoir rock and fluid properties, relative permeability, capillary pressure within the porous medium, interfacial tension, and wettability to recover crude oil and helps in additional crude oil recovery. The mechanism involved in the process and the selection of secondary and tertiary oil recovery methods are discussed in this chapter with a brief introduction of core flooding experiments and reservoir simulators.

The research of multiphysical thermal-hydraulic-mechanical (THM) simulation has achieved significant progress in the past decade. Currently, two general approaches for poromechanical simulation co-exist in the reservoir simulation community, namely the stress approach with stress as the primary variable for the mechanical governing equations and the displacement approach with displacement as the primary variable. In this work, we aim to provide a theoretical foundation and a practical semi-analytical solution for the stress approach based on the Navier-Beltrami-Michell Equations. Moreover, we will clarify the relationship (and equivalence) between the two approaches. We have firstly proven the existence and uniqueness of the stress solution of Navier-Beltrami-Michell equation with given pressure and temperature field. Moreover, we have demonstrated the equivalence of the stress formulation to the displacement formulation. Based on Fourier's expansion, we have developed a general semi-analytical solution for thermal-hydraulic-mechanical process. The semi-analytical solution takes the pressure solution from the hydraulic simulation module (or a commercial reservoir simulator) and directly predicts the stress tensor of the multiphysical system. As such, the solution can be programmed fully coupled with the hydraulic simulation module to predict the stress field with varying pressure and temperature of homogeneous poroelastic rocks under given stress boundary conditions. From the work above, we have laid a theoretical foundation for the stress approach. The derived semi-analytical solution of the stress field shows excellent accuracy. The solution has been used to predict the transient stress field of a dual-porosity system during primary depletion. This paper is arguably the first trial to clarify the relationship between the stress approach and the displacement approach. Moreover, the derived semi-analytical solution provides a convenient yet precise way to obtain the stress field without time-consuming numerical simulation.

This work presents the approaches used for the optimal placement and determination of parameters of hydraulic fractures in horizontal and multilateral wells in a low-permeability reservoir using various methods, including 3D modeling. The results of the production rate of a multilateral dualwellbore well are analyzed after the actual hydraulic fracturing performed on the basis of calculations. The advantages and disadvantages of modeling methods are evaluated, recommendations are given to improve the reliability of calculations for models with hydraulic fracturing (HF)/ multistage hydraulic fracturing (MHF).

The potential of nanoparticles, which are classified as advanced fluid material, have been unlocked for improved oil recovery in recent years such as nanoparticles-assisted waterflood process. However, there is no existing commercial reservoir simulation software that could properly model phase behaviour and transport phenomena of nanoparticles. This paper focuses on the development of a novel robust advanced simulation algorithms for nanoparticles that incorporate all the main mechanisms that have been observed for interpreting and predicting performance. The general algorithms were developed by incorporating important physico-chemical interactions that exist across nanoparticles along with the porous media and fluid: phase behaviour and flow characteristic of nanoparticles that includes aggregation, splitting and solid phase deposition. A new reaction stoichiometry was introduced to capture the aggregation process. The new algorithm was also incorporated to describe disproportionate permeability alteration and adsorption of nanoparticles, aqueous phase viscosities effect, interfacial tension reduction, and rock wettability alteration. Then, the model was tested and duly validated using several previously published experimental datasets that involved various types of nanoparticles, different chemical additives, hardness of water, wide range of water salinity and rock permeability and oil viscosity from ambient to reservoir temperature. A novel advanced simulation tool has successfully been developed to model advanced fluid material, particularly nanoparticles for improved/enhanced oil recovery. The main scripting of physics and mechanisms of nanoparticle injection are accomplished in the model and have acceptable match with various type of nanoparticles, concentration, initial wettability, solvent, stabilizer, water hardness and temperature. Reasonable matching for all experimental published data were achieved for pressure and production data. Critical parameters have been observed and should be considered as important input for laboratory experimental design. Sensitivity studies have been conducted on critical parameters and reported in the paper as the most sensitive for obtaining the matches of both pressure and production data. Observed matching parameters could be used as benchmarks for training and data validation. Prior to using in a 3D field-scale prediction in Malaysian oilfields, upscaling workflows must be established with critical parameters. For instance, some reaction rates at field-scale can be assumed to be instantaneous since the time scale for field-scale models is much larger than these reaction rates in the laboratory.

In this paper, we describe an approach to designing monitoring schemes for carbon dioxide sequestration in saline aquifers. Changes in key parameters are investigated over timescales of up to a thousand years. The study addresses movement of the CO2 plume, possible locations for observation wells and the period for which a storage location should be monitored. For the initial sensitivity analysis, we use a simple homogeneous reservoir simulation model to understand how reservoir, operational and model parameters affect the amount of mobile CO2 remaining at different times over the storage period. The parameters with the greatest impact are taken forward to uncertainty studies, which are conducted on two reservoir models with more realistic geological characteristics: one with lateral extensive baffles and one with sand channels. For these cases, we investigate the movement of the CO2 plume and its arrival at possible locations for an observation well. Results from the sensitivity analysis indicate that the most influential parameters are horizontal permeability, dipping angle, critical gas saturation, salinity, the period of injection and the capillary pressure curve. The results from the uncertainty studies indicate that for the two heterogeneous models, a reasonable monitoring period is in the range of 60 to 150 years and that the movement of the plume probably stops after approximately 100 years. The arrival time of CO2 at the observation well can be predicted with greater confidence when the well is in close proximity to the injector and in the direction in which CO2 will preferably move. A correlation analysis on the uncertain parameters shows that the main contributor affecting the amount of mobile CO2 is critical gas saturation, followed by dipping angle and the period of injection. While previous studies focus on how different parameters affect immobilization of CO2, this study aims to develop a methodology to plan long-term monitoring of mobile CO2. Prediction of the expected plume movement can help to determine suitable observation well locations and reasonable timescales for the monitoring process.

We present the current status of time-lapse seismic integration at the Farnsworth (FWU) CO2 WAG (water-alternating-gas) EOR (Enhanced Oil Recovery) project at Ochiltree County, northwest Texas. As a potential carbon sequestration mechanism, CO2 WAG projects will be subject to some degree of monitoring and verification, either as a regulatory requirement or to qualify for economic incentives. In order to evaluate the viability of time-lapse seismic as a monitoring method the Southwest Partnership (SWP) has conducted time-lapse seismic monitoring at FWU using the 3D Vertical Seismic Profiling (VSP) method. The efficacy of seismic time-lapse depends on a number of key factors, which vary widely from one application to another. Most important among these are the thermophysical properties of the original fluid in place and the displacing fluid, followed by the petrophysical properties of the rock matrix, which together determine the effective elastic properties of the rock fluid system. We present systematic analysis of fluid thermodynamics and resulting thermophysical properties, petrophysics and rock frame elastic properties, and elastic property modeling through fluid substitution using data collected at FWU. These analyses will be framed in realistic scenarios presented by the FWU CO2 WAG development. The resulting fluid/rock physics models will be applied to output from the calibrated FWU compositional reservoir simulation model to forward model the time-lapse seismic response. Modeled results are compared with field time-lapse seismic measurements and strategies for numerical model feedback/update are discussed. While mechanical effects are neglected in the work presented here, complementary parallel studies are underway in which laboratory measurements are introduced to introduce stress dependence of matrix elastic moduli.