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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.

Depletion-induced stress change causes the redistribution of stress field in reservoirs, which can lead to the reorientation of principal stresses. Stress reorientation has a direct impact on fracture propagation of infill wells. To understand the effect of stress reorientation on the propagation of infill well's fractures, an integrated simulation workflow that combines the reservoir flow calculation and the infill well hydraulic fracturing modeling is adopted. The reservoir simulation is computed to examine the relationship between the extent of stress reversal region and reservoir properties. Then, the hydraulic fracturing model considering the altered stress field for production is built to characterize the stress evolution of secondary fracturing. Numerical simulations show that stress reorientation may occur due to the decreasing of the horizontal stresses in an elliptical region around the parent well. Also, the initial stress difference is the driving factor for stress reorientation. However, the bottom hole pressure, permeability and other properties connected with fluid flow control timing of the stress reorientation. The decrease of the horizontal stresses around the parent well lead to asymmetrical propagation of a hydraulic fracture of the infill well. The study provides insights on understanding the influence of stress reorientation to the infill well fracturing treatment and interference between parent and infill wells.

Horizontal wells are often drilled and hydraulically fractured in tight reservoirs to produce hydrocarbons or heat. Different fracturing fluids such as slick water, gas, foam, gel, or a combination can be used with slick water being the most common fracturing fluid. In this paper, we study the impacts of different fracturing fluids on fractured well productivity using an in-house integrated hydraulic fracturing and reservoir simulator with an equation-of-state compositional model. We analyzed the fracture geometry, stress interference, proppant placement, and the subsequent well productivity using different fracturing fluids. The results clearly show that different fracturing fluids result in very different fracture shape, sand distribution, and water and hydrocarbon production. By conducting fracturing and production simulations in one simulator, we ensure that no physics and data loss occurs due to data migration between two different software packages for hydraulic fracturing and reservoir simulation. To the best of the authors’ knowledge, this is the first time that a single integrated equation-of-state compositional hydraulic fracturing and reservoir simulator has been presented and applied for well lifecycle simulation.

Summary Numerical smearing is oftentimes a challenge in reservoir simulation, particularly for complex tertiary recovery strategies. We present a new high-resolution method that uses dynamic coarsening of a fine underlying grid in combination with local timestepping to provide resolution in time and space. The method can be applied to stratigraphic and general unstructured grids, is efficient, introduces minimal computational overhead, and is applicable to flow models seen in practical reservoir engineering. Technically, the method is based on three concepts: Sequential splitting of the flow equations into a pressure equation and a system of transport equations Dynamic coarsening in which we temporarily coarsen the grid locally by aggregating cells into coarse blocks according to cell-wise indicators on the basis of residuals (gradients and other measures of spatial and temporal changes can also be used) Asynchronous local timestepping that traverses cells/coarse blocks in the direction of flow We assess the applicability of the method through a set of representative cases, ranging from conceptual to realistic, with complex fluid physics and reservoir geology, and demonstrate that the method can be used to reduce computational time and still retain high resolution in spatial/temporal zones and quantities of interest. NOTE: This paper is published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.

Geostatistical inversion can combine the advantages of two aspects: high horizontal resolution from deterministic seismic inversion and high vertical resolution from geostatistical simulation. Therefore, it becomes a new high resolution seismic inversion method. The method uses Bayesian inference to determine a posteriori probability density function of reservoir parameters based on seismic data, well logs and geostatistical information. Then, reservoir parameters are sampled and estimated using MCMC. The results have high resolution, including lithology, porosity, saturation and volume of shale et al., which can be used for reservoir evaluation, geological modeling and reservoir simulation. In this paper, the principle and workflow of geostatistical inversion based on Bayes-MCMC algorithm are firstly introduced. Then the integrated research of seismic inversion, geological modeling and reservoir simulation based on geostatistical inversion are applied to the development of Marine reservoirs in the South China Sea. This method improved the accuracy of geological modeling and efficiency of reservoir simulation.

A microscale heterogeneity quantification methodology is presented, which uses petrographic image analysis with multiscale simulation. Petrographic images of micro-porous carbonate rocks are conver...

Time-lapse (4D) seismic analysis plays a vital role in reservoir management and reservoir simulation model updates. However, 4D seismic data are subject to interference and tuning effects. Being able to resolve and monitor thin reservoirs of different quality can aid in optimizing infill drilling or in locating bypassed hydrocarbons. Using 4D seismic data from the Maui field in the offshore Taranaki Basin of New Zealand, we generate typical seismic attributes sensitive to reservoir thickness and rock properties. We find that spectral instantaneous attributes extracted from time-lapse seismic data illuminate more detailed reservoir features compared with those same attributes computed on broadband seismic data. We have developed an unsupervised machine-learning workflow that enables us to combine eight spectral instantaneous seismic attributes into single classification volumes for the baseline and monitor surveys using self-organizing maps (SOMs). Changes in the SOM natural clusters between the baseline and monitor surveys suggest production-related changes that are caused primarily by water replacing gas as the reservoir is being swept under a strong water drive. The classification volumes also facilitate monitoring water saturation changes within thin reservoirs (ranging from very good to poor quality) as well as illuminating thin baffles. Thus, these SOM classification volumes indicate internal reservoir heterogeneity that can be incorporated into reservoir simulation models. Using meaningful SOM clusters, geobodies are generated for the baseline and monitor SOM classifications. The recoverable gas reserves for those geobodies are then computed and compared with production data. The SOM classifications of the Maui 4D seismic data seem to be sensitive to water saturation change and subtle pressure depletions due to gas production under a strong water drive.

Mount Iyang-Argopuro is one of the geothermal working areas in the East Java. Mount Iyang-Argopuro has the potential of 185 MWe of reserves and 110 MWe of resources. It is estimated to have a liquid dominated reservoir with temperature up to 250-275 oC. An early 3D natural state numerical model of Mount Iyang-Argopuro Field is created using TOUGH2 simulator in order to identify the undisturbed condition of reservoir and resource assessment. Since Mount Iyang-Argopuro geothermal area is still in the exploration stage, the model created based on based on geological, geophysical, and geochemical data. The model has an area 14 km x 8.2 km and 9180 m in thickness. The model consists of 7410 of rectangular cell blocks with the roughest cell size is 1000 m x 1000 m and the finest is 200 m x 500 m. The model is verified by matching the model temperature and pressure profiles to the calculated geothermometer temperature and pressure, which shows good match enough.

In order to make full use of the information provided in the physical reservoirs, including the production history and environmental conditions, the whole life cycle of reservoir discovery and recovery should be considered when mapping in the virtual space. A new concept of reservoir digital twin and the exploratory multi-scale framework is proposed in this paper, covering a wide range of engineering processes related with the reservoirs, including the drainage, sorption and phase change in the reservoirs, as well as extended processes like injection, transportation and on-field processing. The mathematical tool package for constructing the numerical description in the digital space for various engineering processes in the physical space is equipped with certain advanced models and algorithms developed by ourselves. For a macroscopic flow problem, we can model it either in the Navier-Stokes scheme, suitable for the injection, transportation and oil-water separation processes, or in the Darcy scheme, suitable for the drainage and sorption processes. Lattice Boltzmann method can also be developed as a special discretization of the Navier-Stokes scheme, which is easy to be coupled with multiple distributions, for example, temperature field, and a rigorous Chapman-Enskog expansion is performed to show the equivalence between the lattice Bhatnagar-Gross-Krook formulation and the corresponding Navier-Stokes equations and other macroscopic models. Based on the mathematical toolpackage, for various practical applications in petroleum engineering related with reservoirs, we can always find the suitable numerical tools to construct a digital twin to simulate the operations, design the facilities and optimize the processes. Cited as: Zhang, T., Sun, S. An exploratory multi-scale framework to reservoir digital twin. Advances in Geo-Energy Research, 2021, 5(3): 239-251, doi: 10.46690/ager.2021.03.02

Seepage-type gas hydrate accumulation in subsea shallow formations involves complicated thermo-hydro-solid coupling processes and matching problem between various accumulation elements. The formation physical properties control local natural gas migration pathway and thus the final reservoir characteristics of hydrates. In this paper, a novel mixed-flux model for gas hydrate accumulation is established and then used to simulate the process of methane gas migration into the shallow stratum to form a hydrate reservoir. The effects of reservoir heterogeneity and gas source conditions on the distribution of pore fluid and hydrate accumulation are examined. The simulation results show that reservoir heterogeneity is conducive to the retention and lateral migration of CH4 in a hydrate stability zone. CH4 can contact more pore water to form a large hydrate reserve, but the formed hydrate is often dispersed. Low-permeability layers enhance the trapping of CH4 and form a uniform and large hydrate saturation. Besides, gas source conditions have an important impact on the hydrate accumulation in reservoirs. Large gas flux, small pore water flux, continuous gas supply, high content of heavy components in natural gas, and numerous gas source points contribute to large amounts of hydrates generation in a certain time period. The presented work will deepen our understanding of the controls of natural gas hydrate systems in subea shallow formations.

Suites of wireline well logs and three-dimensional (3D) seismic data were integrated to characterise the reservoir and estimate the hydrocarbon in Otigwe field, coastal swamp depositional belt, Niger Delta. The 3D seismic data were used to generate seismic sections through which fourteen faults and two horizons of interest were mapped across four wells. Depth structural map generated from the mapped faults and horizons of interest shows that the trapping mechanism within the field is fault-supported anticlinal structural trap. The four available wells were correlated using lithostratigraphic correlation to establish two reservoir continuities (Reservoir A and B). The estimated reservoir fluid volume at surface condition using reservoir simulation and modelling software is 59 MMstb for reservoir A and 25.70 MMstb for reservoir B. On the other hand, the estimated reservoir fluid volume at surface condition using analytical method is 52.58 MMstb for reservoir A and 18.85 MMstb for reservoir B. Using reservoir simulation and modelling software, the average net-to-gross ratio and shale volume for reservoir A range from 0.86 to 0.89 and 0.11 to 0.14, respectively, while for reservoir B the range is between 0.69 to 0.82 and 0.18 to 0.31, respectively. On the flipside using the analytical method, the average net-to-gross ratio and shale volume for reservoir A is 0.78 and 0.22, respectively. The results from the volumetric estimation of reservoir fluids showed close values using both methods and reservoir A is more prolific compare to B.

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.

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.

Constructing a reservoir simulation model requires an accurate definition of saturation functions, including capillary pressure and relative permeability data. Usually, these saturation functions are available only for a limited number of samples. Assigning saturation functions to the simulation model requires finding a clear relationship between them and a 3D predictable property of grid cells. Different indices are usually evaluated to describe such a relationship. It was recently shown that each petrophysical dynamic rock type should form similar True Effective Mobility (TEM) curves. In this study, TEM-function was used to evaluate the reliability and performance of different rock typing indices in defining dynamic rock types. FZI, FZIM, MFZI, and FZI∗ (FZI-star) indices were considered and tested on a collection of laboratory-derived core-flooding data from an Iranian carbonate reservoir. Results showed that FZI-star had a better performance than FZI, MFZI, and FZIM.

Most petroleum reservoirs contain faults, and a key methodological challenge in full-field reservoir modeling is to include the effects of 3D sub-seismic fault zone structure within the 2D fault surfaces represented in commercially available simulators. To address this shortcoming, connectivity-based geometrical upscaling (GU) is introduced to include these fault zones implicitly in the upscaled reservoir model, and in this study, a comparison is made of the accuracy and flexibility of two different GU methods. The existing template-based geometrical upscaling (TBGU) method is compared to a newly developed flow-based geometrical upscaling (FBGU) method. In both methods, the faults and their associated single-phase fault rock properties are represented in the upscaled reservoir simulation model implicitly as neighbor and non-neighbor cell-to-cell connection transmissibilities, which are determined from 3D fault zone structures, but these transmissibilities are calculated in very different ways. Both approaches require a high-resolution reservoir model (i.e., truth model), containing 3D fault zone structure explicitly within the model geometry, which is then upscaled using the two methods to take into account the influences of the fault zone structure. The accuracy of both the upscaling methods is examined by comparing the flow behavior of the truth model with that of model versions upscaled using two different ways. The results of the two versions of upscaled models revealed significant differences and indicate that the FBGU technique is a much more accurate and flexible means of including structurally complex fault zone into low-resolution upscaled reservoir simulation models.

A forecasting method of oil well production based on multivariate time series (MTS) and vector autoregressive (VAR) machine learning model for waterflooding reservoir is proposed, and an example application is carried out. This method first uses MTS analysis to optimize injection and production data on the basis of well pattern analysis. The oil production of different production wells and water injection of injection wells in the well group are regarded as mutually related time series. Then a VAR model is established to mine the linear relationship from MTS data and forecast the oil well production by model fitting. The analysis of history production data of waterflooding reservoirs shows that, compared with history matching results of numerical reservoir simulation, the production forecasting results from the machine learning model are more accurate, and uncertainty analysis can improve the safety of forecasting results. Furthermore, impulse response analysis can evaluate the oil production contribution of the injection well, which can provide theoretical guidance for adjustment of waterflooding development plan.

This paper presents a novel petrophysical experiment for measuring the 3D permeability tensor at reservoir conditions in fractured vuggy carbonate rock. The permeability variation with confining pressure is demonstrated through the experimental investigation; the permeability ellipse plots show the decrease of permeability, as a function of the increase in effective stress. The experiment was developed at reservoir conditions (120 °C temperature and variable confining pressure) in a native whole rock sample, from the Gulf of Mexico naturally fractured and vuggy reservoir. The analysis of the laboratory data reveals the elliptical behavior of permeability. Two ellipses were generated, one corresponding to the fracture network (secondary porosity system) and another for matrix porosity and permeability (primary porosity system). An important result is the compaction of the representative fracture network ellipse until it fuses with the matrix porosity ellipse at a high confining pressure state. The test contributes to the understanding of the mechanical and flow aspects of permeability, for naturally fractured reservoirs. The experimental results provide a basis for improving reservoir simulation studies, to obtain realistic predictions of reservoir behavior.

Primary drainage capillary pressure data are usually correlatable with a 3D predictable property of grid cells. Accordingly, rock typing is normally performed based on an established correlation. Primary drainage as well as corresponding imbibition and/or secondary drainage capillary pressure curves are averaged to establish a saturation table for each rock type region in reservoir modeling. This study investigates the reliability of this industry-accepted methodology, and has two main contributions. First, we show that if different types of capillary pressures are plotted against water saturation, comparing them might be highly misleading. We demonstrate that although primary drainage capillary pressure data may be plotted against water saturation, the imbibition and secondary drainage capillary pressure data should be plotted against imbibed water saturation. This would enable reservoir engineers to check whether rocks with similar primary drainage capillary pressures do or do not have similar imbibition/secondary drainage counterparts. Using this technique, rock quality can be also deduced from imbibition and secondary drainage capillary pressure curves. We use capillary pressure data measured on limestone and sandstone samples from the Asmari Formation in three Iranian oilfields to evaluate our technique. The second contribution of this study is the proposal of a new methodology for preparing capillary pressure curves for reservoir models. In our methodology, a grid cell can represent more than one rock type region, each specific to a saturation function. As a part of this methodology, we present new physically meaningful equations for averaging primary drainage, imbibition, and secondary drainage capillary pressure curves.

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.

To increase the efficiency of appraisal and development of hydrocarbon fields, the most effective technology is the integration of geological and field information into modern software systems for reservoir simulation, starting from the input of seismic data to field development planning based on a reservoir models. Building a three-dimensional geocellular models is an integral part of hydrocarbon reservoir management. After all, the reservoir model built to solve the main tasks of reservoir management such as: achieve the highest recovery and maximum economic effect. The modern level of software and the advances in computer processing power and graphics allows you to operate with big data, provides an opportunity for its systematization, statistical processing and detecting the basic laws between them. The availability of reliable data plays important role in the creation of a database for reservoir models. The input data for reservoir modelling of the fields, which were discovered in the 1960s, are the results of complex studies, characterized by insufficient accuracy and low quality. Lack of reliable and high-quality data brings significant uncertainty in all stages of modelling from volumetric estimation to the history match and forecasting. The necessity of using available geological and field information has led to the development of new methodological principles and approaches to reservoir modelling in conditions of limited initial information. According to the results of numerous studies, a significant number of methods have been developed, which are successfully used in the design of simulation models of hydrocarbon reservoirs of JSC “Ukrgazvydobuvannya”. Thanks to the use of new approaches to the building of 3D-models, high accuracy and reliability of the simulation results under such conditions is achieved.

As oil and gas extraction activities move into deeper rock formations, many experimental studies and field investigations indicate rock exhibits a plastic behavior rather than a pure linear elastic behavior, so poroelastoplasticity must be taken into account in the reservoir simulation. Because reservoir rock is a porous material consisting of a compressible solid matrix and number of compressible fluids occupying the pore space, fully coupled modeling is required for reservoir simulation considering solid-fluid interaction, complex stress conditions and nonlinear behaviors. But the computational process could be cumbersome when constant tangent stiffness method is used to address the poroelastoplastic behavior. In this paper, a fully coupled poroelastoplasticity reservoir model based on Drucker-Prager yield criterion is implemented the tangent stiffness method, and the computational efficiency is compared with the constant stiffness method. The accuracy of these two methods is demonstrated in one-dimensional consolidation. In a case study, these two methods are used to analyze the stresses and pore pressure of a reservoir and computing results and running efficiency are compared. Also, the linear elastic and nonlinear solutions are compared in one-dimensional consolidation and reservoir modeling. It shows that the difference between results by constant stiffness method and tangent stiffness method is very small, while the tangent stiffness method shows significantly fewer iteration numbers and shorter running time than the constant stiffness method.

SummaryIn coal-seam-gas (CSG) fields, where single wells tap multiple seams, it is likely that some of the individual seams hardly contribute to gas recovery. This study aims to examine the contribution of individual seams to the total gas and water production considering that each seam can have different properties and dimensions. A sensitivity analysis using reservoir simulation investigates the effects of individual seam properties on production profiles.A radial model simulates the production of a single CSG well consisting of a stack of two seams with a range of properties for permeability, thickness, seam extent, initial reservoir pressure, coal compressibility and porosity. The stress dependency of permeability obeys the Palmer and Mansoori (1998) model. A time coefficient (α) relates seam radius, viscosity, porosity, fracture compressibility, and permeability. It is used to aid interpretation of the sensitivity study. Finally, two hypothetical simulation scenarios with five seams of different thicknesses and depths obtained from producing wells are explored. The range in properties represents conditions found in the Walloon Coal Measures (WCM) of the Surat Basin, relevant to the Australian CSG industry.Each seam in the stack achieves its peak production rate at different times, and this can be estimated using α. Seams with lower α reach the peak gas rate earlier than those with higher α-coefficient. The distinct behavior of gas-production profiles depends on the combination of individual seam properties and multiseam interaction. At a αratio > 1 (i.e., αtop/αbottom > 1), the bottom seam peaks first but achieves lower gas recovery than the top seam. An increasing αratio is associated with the inhibition of less-permeable seams and reduced overall well productivity. For αratio

Natural gas from ultra-deep reservoirs has been a major contributor for reserves boost, deliverability construction, and profits growth in natural gas industry in China. As a significant strategic domain in the future development of upstream business, the high-quality development of ultra-deep gas resources has great significance for economic benefits enhancement and sustained regional supply assurance. In this paper, based on the appraisal of development characteristics and effectiveness in the developed large ultra-deep gas fields, challenges for high quality development were indicated, which include the difficulties in structure confirm, uncertainties in reserves define and production optimization, risks of aquifer water early breakthrough and high investment of deep wells. Through indoor physical simulation experiments, reservoir characterization, performance evaluation, reservoir simulation and knowledge acquisition from analogous fields at home and abroad, the connotation and requirements for high quality development were discussed, and furthermore, strategies and proposals were thus proposed as follows: to strengthen the pre-development reservoir evaluation to define movable gas reserves and quantify rational production rate so as to avoid facility waste; to optimize both well pattern and well flow rate to achieve uniform depletion and high EUR; to continuously enhance drilling & completion technologies to further reduce drilling and completion circle and cost and targeted reservoir stimulation technologies to enhance movable reserves and single-well productivity and increase the depletion of inferior reserves; and to innovate management modes to establish scientific programs and procedures for the construction, production and operation of ultra-deep gas fields and strictly control the upper limit index of production rate so as to emphasize quality benefits. In conclusion, high-quality development of ultra-deep gas fields, a hard and complex system though, will be possibly achieved only by continuous innovation of exploration and development technologies and management modes.

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.

We explore the petrophysical behavior of the two interbedded lithofacies (sandy silt and clayey silt) that constitute the Green Canyon Block 955 hydrate reservoir in the deep-water Gulf of Mexico by performing experiments on reconstituted samples of the reservoir material. Sandy silts reconstituted to the in situ porosity have a permeability of 11.8 md (1.18 × 10−14 m2), which is similar to the intrinsic permeabilities measured in intact cores from hydrate reservoirs of similar grain size offshore Japan (Nankai Trough) and offshore India. Reconstituted clayey silts have a much lower intrinsic permeability of 3.84 × 10−4 md (3.84 × 10−19 m2) at the in situ stress. The reconstituted sandy silt is less compressible than the clayey silt. Mercury injection capillary pressure measurements demonstrate that the largest pores with the clayey silt are still smaller than the pores remaining after 90% hydrate saturation in sandy silt. We interpret that the methane solubility in pores of clayey silt is always less than that necessary to form hydrate, which explains why no hydrate is present in the clayey silt. We upscale the reservoir properties to estimate the behavior of interbedded sandy silt and clayey silt. We find the upscaled intrinsic horizontal and vertical permeabilities for the entire reservoir interval are 8.6 md (8.6 × 10−15 m2) and 1.4 × 10−3 md (1.4 × 10−18 m2). We estimate that during reservoir production, a maximum vertical strain of approximately 12% will result. Ultimately, this study will inform reservoir simulation models with petrophysical properties at scales of both individual lithofacies and reservoir formation.

Accumulation of liquids in gas-condensate reservoirs may lead to a vertical flow of liquid caused by density difference in the presence of gravity. In this paper, the effect of this vertical flow on the prediction of production data has been investigated. To achieve this goal, a single-layer synthetic cylindrical reservoir is considered and, the flows are simulated with and without vertical direction grid blocks with two lean and rich fluids. The governing equations of the so-called Modified Black-Oil (MBO) model are solved in a cylinder sector using the open-source Matlab Reservoir Simulation Toolbox (MRST). When the vertical flow is taken into consideration, the results show that gravity may lead to migration of liquid condensates to lower regions and the production rates decrease as a consequence of wellbore partially blockage especially for the rich fluid. In addition, gravity may cause a non-linear effect on the flow behavior and increase in the condensates production rates. All results are also obtained for three values of critical liquid condensate saturation to show the effect of this parameter on the production. It has been shown that neglecting the vertical flow may cause significant errors in the result of production, i.e. up to 25% when the fluid is rich and the critical condensate saturation is 0.15. To generalize the effect of the reservoir thickness, dimensional analysis is carried out which yields a similarity parameter. The findings of this study can help for a better understanding of near well flow in gas-condensate reservoirs. Based on this study, in applications in which the reservoir gas is rich in condensate and the thickness of the reservoir layer or the vertical permeability is high enough, it is recommended that the gravity effect is taken into account by enough grid points in the vertical direction in each layer.

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...

The numerical modelling of flows in geologic porous media, accounting for plastic behaviour of rocks at high temperatures and hydrofracturing at high fluid pressures, is required for a better understanding of hydrothermal and volcanic systems. The investigation of these systems is limited given the lack of reliable and available reservoir simulation software that accounts for complicated rock behaviour at elevated temperatures. In this paper, we present such software as an extension of the MUFITS reservoir simulator. We describe the mathematical model utilised for modelling the permeability changes of elastic and plastic rocks and input data formats to the simulator. We present several application examples related to the modelling of brittle–ductile transition in hydrothermal systems, in particular perturbed with the emplaced degassing magma body, and provide the corresponding simulator input data to facilitate and ease its further usage.

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.

Recent experience in applying recurrent neural networks (RNNs) to interpreting Permannt Downhole Gauge (PDG) records has highlighted the potential utility of machine learning algorithms to learn reservoir behavior from data. The power of the RNN resides in its ability to retain information in a form of memory of previous patterns and information contained in the previous behavior of phenomena being modeled. This memory plays a role of informing the decision at the present time by using what happened in the past. This property suggests RNNs as a suitable choice to model sequences of reservoir information, even when the reservoir modeler is faced with incomplete knowledge of the underlying physical system. Convolutional Neural Networks (CNNs) are another variant of machine learning algorithms that have shown promise in sequence modeling domains, such as audio synthesis and machine translation. In this study, RNN and CNN were applied to tasks that traditionally would be modeled by a reservoir simulator. This was achieved by formulating the relationship between physical quantities of interest from subsurface reservoirs as a sequence mapping problem. In addition, the performance of a CNN layer as compared to RNN was evaluated systematically to investigate their capabilities in a variety of tasks of interest to the reservoir engineer. Preliminary results suggest that CNNs, with specific design modifications, are as capable as RNNs in modeling sequences of information and as reliable when making inferences to cases that has not been seen by the algorithm during training. Design details and reasons pertaining to the way these two seemingly different architectures process information, and handle memory are also discussed.

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.

The process of “hysteresis” has widely attracted the attention of researchers and investigators due to its usage in many disciplines of science and engineering. Economics, physics, chemistry, electrical, mechanical, and petroleum engineering are some examples of disciplines that encounter hysteresis. However, the meaning of hysteresis varies from one field to another, and therefore, many definitions occur for this phenomenon depending on the area of interest. The “hysteresis” phenomenon in petroleum engineering has gained the attention of researchers and investigators lately, because of the role that plays in reservoir engineering and reservoir simulation. Hysteretic effects influence reservoir performance. Therefore, an accurate estimation of rock and fluid property curves has an essential role in evaluating hydrocarbon recovery processes. In this paper, a comprehensive review of research and growth on the hysteresis of wettability for its applications in petroleum engineering is reported. Also, theoretical and experimental investigations of hysteresis of wettability are compared and discussed in detail. The review highlights a range of concepts in existing models and experimental processes for wettability hysteresis. Furthermore, this paper tracks the current development of hysteresis and provides insight for future trends in the research. Finally, it reveals an outlook on the research challenges and weaknesses of hysteresis of wettability.

Summary The reduction of pore pressure caused by depletion can induce significant reservoir compaction and loss of permeability, especially in unconsolidated reservoirs. In this paper, we develop a numerical approach on the basis of computer-based simulations of unconsolidated rock samples subjected to mechanical tests that replicate the one-dimensional (1D) strain depletion path and allow for a prediction of permeability loss. The 1D strain stress path is a good approximation for long and thin conventional reservoirs with a compliant caprock. The numerical sample consists of crushable stiff and soft grains (proxies for sand and shale) simulated with the discrete element method (DEM) coupled with the bonded-particle model (BPM). Model parameters are calibrated through numerical single-grain-crushing tests which reproduce the experimentally measured sand strength. Grain crushing induced by the uniaxial strain stress path results in a pronounced reduction of porosity and permeability, which manifests more readily for samples with large grain size. The change of particle-size distribution indicates that high effective stresses cause grain crushing and production of a significant amount of fines that lower permeability. Simulation results indicate that the presence of soft grains and inclusions (e.g., shale fragments) facilitates grain crushing. Reservoir simulations—incorporating the change of porosity and permeability as a compaction table—show that the compaction can enhance cumulative production due to compaction drive but also reduces production rate by impairing the reservoir permeability. This multiscale numerical workflow bridges grain-scale compaction behavior and field-scale reservoir production.