bluuebunny/crossref_metadata_2025 huggingface dataset:
Formation Damage Mechanisms Due to Hydraulic Fracturing of Shale Gas Wells
Authors: Elputranto Riza , Cirdi Ayse Pamir , Akkutlu I. Yucel
Published: June 2020

Much work has been done on hydraulic-fracturing as a well stimulation technique but our understanding of formation damage due to fracturing is limited. This is due to inherent complexity of shale-water interactions under subsurface conditions. Damage is triggered by cold and low-salinity water invasion into the formation. Here, we introduce the formation damage mechanisms as a multi-physics/chemistry problem developing in a region near the fracture-matrix interface. Using high-resolution flow simulation models, we investigate the mechanisms and their impact on natural gas production.

The simulation model includes geo-mechanically fully coupled non-isothermal multi-component two-phase flow equations that are developed for a multi-scale porous medium representative of the shale formations. We consider the occurrence of formation damage during two consecutive periods: well shut-in period which is considered to begin with the completion of fracturing and extending 1-2 days; followed by water flow-back and gas production period which takes months.

During the early shut-in period, cold water invasion leads to thermal contraction of the matrix and reduces the normal mean stress. These changes improve the formation permeability temporarily, they may create secondary fractures, and modify the capillary pressure and saturations in the water invaded zone. These thermal effects are reduced rapidly, however, due to heat supplied by the reservoir. Osmosis pressure and the associated clay swelling cause the formation matrix to absorb fracturing water, reduce the matrix permeability, and amplify the capillary pressure/saturations. In summary, the well goes to the flowback and production with modified near-fracture conditions. During the water flowback the water saturation near the fracture-matrix interface increases; hence, liquid blockage effect on the gas flow becomes larger than that predicted based on the water imbibition during the shut-in only. This is due to capillary-end-effect developing near the interface during the water flow-back, when the fracturing water is displaced by the gas, i.e., drainage. Clay swelling and stress change continue during the withdrawal of the fluids. Consequently, we observe significant impairment in gas production rates.

Only a fraction (<20%) of the injected water is ultimately produced back from the shale gas wells; the rest stays in the fractures and invades into the formation. Our simulation work shows that it is mainly the water in the fractures that are produced. The rest stays in the fractures due to relative permeability effects therein, and in the matrix as capillary-bound water due capillary end effect and to clay-swelling.
CO2 Foam Stabilized with Switchable Surfactants and Modified Nanoparticles Effected by PH and Salinity
Authors: Zhang Xuan , Zhang Guicai , Ge Jijiang , Wang Yanqing
Published: June 2020

Foam could increase the apparent viscosity of carbon dioxide (CO2) significantly and control the mobility. This work focused on the enhancement of CO2 foam stability with adding modified silica nanoparticles, which effected by the concentration ratio, pH and salinity.

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

The detection and quantification of horizontal-permeability anisotropy play a vital role in optimally placing geothermal wells in geothermal reservoirs and thereby maximizing the geothermal-energy recovery from a given geothermal-reservoir area. However, the study of permeability anisotropy within the horizontal plane has received less attention and often permeability anisotropy is neglected in view of simplification.

Our study show that the horizontal permeability anisotropy has been observed in nearly all geothermal doublets that have been tested so far in the Netherlands. The main objective of this work is to study the impacts of horizontal permeability anisotropy inferred from pressure-interference tests on geothermal-doublets performance.

A theoretical relation between the measured directional permeability and the elements of the permeability tensor are presented. In a case study, horizontal anisotropy has been detected and quantified using a pressure-transient analysis, interference test, and the knowledge of the reservoir geometry gained from the geological study. In addition, this work uses a detailed three-dimensional thermal reservoir simulator of a reservoir in the West Netherlands Basin to demonstrate the importance of considering permeability anisotropy in predicting the lifecycle, which is determined by the cold-temperature breakthrough of an existing doublet and in optimally designing the second doublet in the same licensed area.

It has been established that the areal permeability anisotropy plays an important role in the energy sweep efficiency and doublets placement. A correct arrangement between the permeability anisotropy direction and the placement of the wells leads to longer breakthrough time and increasing the heat sweep efficiency.

This work shows that the knowledge gained from the interference test and/or other experiments about the presence, direction, and scale of anisotropy can be used to adjust the reservoir model that can be further used to design and optimize geothermal doublets.
Digital Rock Physics in Low-Permeable Sandstone, Downsampling for Unresolved Sub-Micron Porosity Estimation
Authors: Ebadi Mohammad , Makhotin Ivan , Orlov Denis , Koroteev Dmitri
Published: June 2020

The approach to handle the unresolved pores at 3D X-ray Micro Computed Tomography (μCT) images of core samples is developed. It enables a sufficient widening of digital rock studies for tight rocks. The μCT images of a low-permeable sandstone with a resolution of 1.2 μm/voxel have been generated. Pore Size Distribution shows the presence of a significant amount of sub-resolution pores. Downsampling has been applied to estimate the actual porosity with extrapolation.

Visual noise, artifacts, and roundoff errors are the major factors affecting the quality of μCT images. We apply transform and spatial domain filtering to minimize all the artifacts. Regarding the overall concept of porosity and through running a geometrical histogram analysis, the Random Walker segmentation as a robust mathematical algorithm has been applied to turn the greyscale μCT images into binary ones resembling pores and grains. Next, the porosity of the binary images with a resolution of 1.2 μm/voxel has been calculated. The procedure continues with downsampling to artificially reduce the resolution and calculate the corresponding porosity.

It has been observed that the calculated porosity for the highest resolution of 1.2 micrometer is still lower than the experimental value which is due to the existence of pores which their sizes are less than 1.2 micrometer, and cannot be seen in the CT images. In order to take the effects of sub-resolution pores into account, an extrapolation relying on the downsampling technique has successfully been applied. The implemented technique is based on the fact that the porosity of the reservoir rock sample is not a function of resolution. However, plotting of the calculated porosities versus their relevant resolutions indicates that the value of porosity has an inverse relationship with the voxel size. In other words, it could be interpreted that the closest values of the calculated porosity to the laboratory reports will be the output of the image processing when the size of voxel moves towards zeros as much as possible, which is technically impossible. Instead, a trendline can be fitted into the scatter plot of porosity versus resolution and find its extrapolation value for the voxel size of zero, which provides the porosity as close as possible to the experimental value.

The main logic behind the digital core analysis is to calculate the properties only according to the digital images. Although there are some studies in which modifications have been done to consider the effects of sub-resolution pores, they are severely suffering from mathematical complexities, and they are mainly based on the global thresholding. The proposed technique can provide an accurate value of porosity when there are no additional data about the pore structure of the sub-micron scale.
Numerical Simulation Guideline of Oil Recovery by Cycle-Dependent Three-Phase Process Using Coreflood Experiments
Authors: Al Zayer Hassan , Sohrabi Mehran
Published: June 2020

Many oil reservoirs worldwide have cycle dependent oil recovery either by design (e.g. WAG injection) or unintended (e.g. repeated expansion/shrinkage of gas cap). However, to reliably predict oil recovery involving three-phase flow process, a transformational shift in the procedure to model such complex recovery method is needed. Therefore, this study focused on identifying the shortcomings of the current reservoir simulators to improve the simulation formulation of the cycle-dependent three-phase relative- permeability hysteresis.

To achieve this objective, several core-scale water-alternating-gas (WAG) injection experiments were analysed to identify the trends and behaviours of oil recovery by the different WAG cycles. Furthermore, these experiments were simulated to identify the limitations of the current commercial simulators available in the industry. Based on the simulation efforts to match the observed experimental results, a new methodology to improve the modelling process of WAG injection using the current simulation capabilities was suggested. Then the WAG injection core-flood experiments utilized in this study were simulated to validate the new approach.

The results of unsteady-state WAG injection experiments performed at different conditions were used in this simulation study. The simulation of the WAG injection experiments confirmed the positive impact of updating the three-phase relative-permeability hysteresis parameters in the later WAG injection cycles. This change significantly improved the match between simulation and WAG experimental results. Therefore, a systematic workflow for acquiring and analyzing the relevant data to generate the input parameters required for WAG injection simulation is presented. In addition, a logical procedure is suggested to update the simulation model after the third injection cycle as a workaround to overcome the limitation in the current commercial simulators.

This guideline can be incorporated in the numerical simulators to improve the accuracy of oil recovery prediction by any cycle-dependent three-phase process using the current simulation capabilities.
An Artificial Intelligence-Based Nonlinear Solver for Hydrocarbon Reservoir Simulations
Authors: Ebadi Mohammad , Bezyan Yashar , Zabihifar Seyed Hassan , Koroteev Dmitry
Published: June 2020

The reservoir simulation is based on the solving of second-order nonlinear Partial Differential Equations (PDEs). Following the high-level of nonlinearity or irregular boundaries, analytical solutions are not applicable to solve the supposed PDEs. To numerically solve the PDEs, applying nonlinear solvers are recommended. Dependencies on derivatives and proper initial guesses are the main disadvantages of classic solvers. To overcome the mentioned obstacles, solving supposed equations based on Adaptive Neural Network (ANN) has been introduced.

The algorithm starts by introducing an initial set into the Nonlinear Simultaneous Algebraic Equations (NSAE). The outputs are compared with the desired matrix of zeros to generate the required error. The calculated vectors of errors and its derivation are firstly employed to update the ANN weights through applying the adaption laws, and secondly, create the input vector to run the ANN. The outputs of the ANN are considered as corrections to be made to the initial set. Then, the corrected initial set is reintroduced into equations. The procedure continues iteratively until the outputs of equations meet the required level of accuracy.

By taking advantages of the adaptive laws, the outputs of the presented algorithm have successfully been matched with answers of the classic solvers, but with less computational costs. The convergence of the shown algorithm has practically been examined by assuming various mathematical types of initial sets. The implemented algorithm has been robust enough to converge for different forms of the initial sets, even for invalid values like minus numbers. However, records indicate that the convergence rates are strongly dependent on the values of initial sets. Following the sensitivity analysis over the primary model of ANN lead to the optimized network, which could solve the supposed NSAE three times faster. It has been interpreted that the number of neurons (NN), the diagonal coefficient matrix of error (λ), and the adaptive coefficient (Fw) have the most significant impacts on the performance of the algorithm.

In contrast to Newton's method as the most well-known nonlinear solver, the launched algorithm does not require any proper initial guesses. Moreover, the absolute independence of computing the partial derivatives of the Jacobian matrix and its inversion, which causes a notable reduction of computational costs, is the other remarkable advantage of the proposed approach. The represented algorithm can be taken as the platform to develop the next generation of simulators working based on machine learning.
Study of Plugging Capability and Seepage Characteristics of Air Foam Flooding in Low Permeability Reservoirs
Authors: He Minxia He , Sun Zheng , Chen Yu , Hu Yongle , Li Xiangfang , Zhou Yingfang
Published: June 2020

Foam flooding is an effective method to control water channeling in low permeability reservoirs. However, due to injection difficulty and poor foam plugging ability encountered in the application of foam flooding in field scale, oilfield production has not achieved expected effects. Therefore, it is of great significance to carry out research on foam plugging ability and multi-cycle gas-liquid alternating fluid seepage law to improve the development effect of foam flooding.

This paper establishes a resistance factor model to evaluate foam plugging ability and analyzes sensitivity parameters. By studying the characteristics of gas phase relative permeability under multiple cycles of gas-liquid alternate injection, the reason for the difficulty of gas injection during foam flooding process is clarified from a theoretical view, and it provides an alternate strategy for adjustment of development plan.

The results show that the resistance factor has an S-shaped relationship with the pore radius, a linear relationship with the liquid viscosity, an L-shaped relationship with the bubble radius, and an n-shaped relationship with the gas-liquid ratio, and the foam resistance factor is extremely sensitive to parameter changes. Investigation on gas relative permeability has shown that as the number of alternate cycle increases, the relative permeability of gas phase generally decreases. At the same injection volume, gas phase relative permeability in the long-period cycle is higher than that in the short-period cycle.
Application of Numerical Flow Simulation Methods to Risk-Based Well Decommissioning Design
Authors: Johnson Caroline , Haghighat Sefat Morteza , Davies David
Published: June 2020

The global oil and gas industry will experience intensive well decommissioning activities, with tens of thousands of well plug and abandonment (P&A) operations forecast to be executed worldwide, over the next few decades. In the North Sea alone, 2,624 wells are expected to be decommissioned over the next decade (OIL&GAS_UK 2019). With the increasing levels of activity in P&A operations, new, fit-for-purpose, P&A design tools and operational technologies have become essential elements in the petroleum engineer's toolbox to ensure safe and cost-effective solutions, especially in today's environment. This paper introduces a novel tool to support risk-based evaluation of well P&A designs using a numerical, grid-based, fluid-flow simulation methodology. The risk-based modelling framework covers the full range of North Sea P&A design scenarios and tracks the long-term evolution of hydrocarbon movement in the P&A well over several thousand years. A visualization engine identifies the dominant hydrocarbon flow-paths, while Monte Carlo methods are used to account for uncertainties in the model input parameters; allowing multiple design options to be ranked with respect to the risk of a hydrocarbon leak.

Transient flow modelling of the well P&A system allows new key performance indicators (KPIs) to be developed, e.g. evolution of hydrocarbon saturations within the P&A well over time and the time hydrocarbons reach the surface. These KPIs are not provided by steady-state P&A models. Results presented in this paper demonstrate the value derived from applications of the developed framework to: Optimally allocate resources by identifying fit-for-purpose P&A designs (e.g. the number, location and length of wellbore barriers, and the value of remedial operations on annular flow barriers).Support risk-based decision-making via investigation and comparison of how multiple P&A design options perform for given well/reservoir conditions.Identify critical modelling parameters and optimally allocate data gathering resources to reduce uncertainty. The "likelihood of occurrence" of each cement defect type is one such critical, but very uncertain, model input parameter.
Polymer Injection for EOR: Influence of Mobility Ratio and Slug Size on Final Oil Recovery
Authors: Juárez José Luis , Bertin Henri , Omari Abdelaziz , Romero Carolina , Bourdarot Gilles , Jouenne Stephane , Morel Danielle , Neillo Valerie
Published: June 2020

Among the many parameters needed to optimize a polymer flood is the choice of polymer viscosity, mobility ratio and polymer slug size that should be injected to maximize oil recovery. In this paper, a new polymer flooding experimental study is addressed to answer two questions. Firstly, considering a given crude oil, what optimal polymer solution viscosity should be injected? And secondly how much polymer solution should be injected during the polymer flood to maximise recovery?

Experiments were carried out using 1D homogeneous Bentheimer cores of similar properties. The cores were oil flooded using crude oil (µo = 120cP at T=60°C) and aged to obtain intermediate wet conditions. The polymer was a partially hydrolysed polyacrylamide (HPAM) dissolved in a moderate salinity brine. The polymer solutions were prepared at different concentrations (from 1500ppm to 3000ppm) to cover a large range of viscosity ratio (Rμ=μoμp from 2 to 18) which correspond to end-point mobility ratios of 0.5 and 5.4, respectively.

Corefloods results show as expected, that the polymer is more efficient in terms of oil recovery when viscosity ratio is low. In line with polymer flooding theory, we observed at intermediate wettability conditions, that a maximum oil recovery is reached at M =1 (Rµ = 5) and that oil recovery did not increase when reducing the ratio to M = 0.5 (Rµ= 2). However, when considering aspects such as polymer mass required, injectivity concerns and flow stability, we observe two favorable conditions, corresponding Rµ= 5 and Rµ = 10, for a mobility ratios of 1 and 7, respectively.

Different polymer slug sizes were injected in the cores at the above conditions (Rµ = 5 and Rµ = 10) followed by water flooding (chase water). Both injections (polymer and water injection) were carried out at same flow rate to minimize miscible viscous fingering at the rear of the polymer slug. Results show that an optimal polymer slug size exists for which one can obtain the same microscopic oil recovery than that of continuous polymer injections at Rµ=5 and Rµ=10, an important finding that can impact the economic viability of the process.

In conclusion, our experimental study shows that at 1D scale, optimal values of viscosity ratio, polymer slug size and polymer mass injected lead to the same maximum oil recovery obtained by continuous polymer injection. A necessary starting point before upscaling a polymer flood and studying the impact of heterogeneities.
The Role of Back Pressure and Perforation Hole Erosion on the Magnitude of the Coefficient of Discharge in Hydraulic Fracturing Stimulation
Authors: Yosefnejad Davood M. , Fricke Bernd , Loehken Joern , McNelis Liam
Published: June 2020

Hydraulic fracturing or fracking is a well stimulation technique for extracting hydrocarbons from naturally low (extra low) permeable oil and gas reservoirs. In this process water, proppant and chemicals are injected through the wellbore and from the perforation hole into the reservoir. The main goal of this treatment is to create artificial fluid path conduits in the formation and finally increase the permeability (and productivity) of the reservoirs.

One of the important factors which affects the near wellbore fluid pressure drop is the coefficient of discharge (Cd) which is a characteristic of the perforated hole in the wellbore tubular. The coefficient of discharge is defined as the ratio of the measured mass flow to the theoretical mass flow. The Cd depends on many factors and may change with time due to erosion caused by the injected sand, which was pumped into the formation. In this research, we investigated some of the factors that can affect the coefficient of discharge like the erosion of the perforated hole and the backpressure given by the fracture.

For this purpose, we have developed a new high-pressure high-flow rate setup for examining the effect of the following parameters which can alter the coefficient of discharge. More specifically we have investigated the effect of perforation hole size, perforation hole geometry and perforation shape on the Cd value at ambient conditions and with backpressure, before and after sand erosion. To do so, in a first step we have used machined holes with a clearly defined geometry and then compared the results with real perforated holes which were generated using various shaped charge designs. The coefficient of discharge was measured using water or gelled water with different pressure differentials and back-pressures. In our study, we have injected sand slurry for 30 minutes with a constant concentration. The flow rate and pressure drop were also recorded simultaneously during the injection of the sand.

Our results show how the erosion directly affects the Cd value and the subsequent pressure drop near the perforated hole. A clear increase of the Cd magnitude becomes visible only due to a change of the inlet geometry without changing the diameter. Also, the backpressure, which represents real fracking conditions, leads to a significant increase compared to the measurements at ambient outlet pressures.

The measured values before and after the erosion for real perforation holes differ from simple drilled holes. From the recorded results, it also seems that certain perforation shapes or geometries are more effected by erosion than others.
Machine Learning Clustering of Reservoir Heterogeneity with Petrophysical and Production Data
Authors: Konoshonkin Dmitry , Shishaev Gleb , Matveev Ivan , Volkova Aleksandra , Rukavishnikov Valeriy , Demyanov Vasily , Belozerov Boris
Published: June 2020

Reservoir development decisions strongly depend on our understanding on reservoir heterogeneity, which is often subject to sparse and conflicting data, interpretational bias and constraints imposed by the modelling assumptions. The work tackles a challenging task of accurately and quickly identifying and describing uncertainty in the spatial distribution of reservoir heterogeneity derived from geological well data and with respect to a geological concept. We propose a metric based machine-learning approach to identify and describe spatial trends in reservoir heterogeneity/facies property distribution using wireline and production data.

We demonstrate how the proposed method can help to partition reservoir heterogeneity and discover and verify spatial trends for a real mature producing field in the Western Siberia. The obtained clustering of reservoir facies based on the wireline logs (alpha-SP) demonstrated a good agreement with the reservoir zonation based on manual log interpretation and the geological concept. Clustering based on individual well production profiles has confirmed the reservoir partitioning and matched some of the reservoir features aligned with the prevailing geological concept. The outcome of the proposed method helps to improve the facies distribution model by integrating the discovered spatial trends into a geostatistical model and account for uncertainty in the depositional scenario that is difficult to quantify based on manual interpretation.
Parallel Framework for Complex Reservoir Simulation with Advanced Discretization and Linearization Schemes
Authors: Li Longlong , Khait Mark , Voskov Denis , Abushaikha Ahmad
Published: June 2020

The continuous progress of reservoir monitoring technology provides encouraging capacities to reduce uncertainties in the subsurface characterization and to mitigate risks in field development applying the reservoir simulation approach. However, it is always challenging to take full advantage of the observation data, since an accurate representation of strong heterogeneities requires a high-resolution grid. Most of the discretization methods cannot handle full tensor permeability, and high nonlinearity introduced by complex physical process drastically reduces simulation efficiency. In this work, we develop an advanced parallel framework for reservoir simulation with the implementation of state of the art discretization and linearization methods. We apply the multipoint flux approximation (MPFA) method to handle the full tensor permeability in unstructured grids. To keep the fidelity of the geological model and improve computational efficiency, we use massively parallel computations via Message Passing Interface (MPI). Complex subsurface physics is described by mass-based formulations making the framework flexible for general-purpose reservoir simulation. However, the representation of phase behavior introduces additional workload when compared with the phase-based formulations in the traditional approach. Here, we apply the Operator-Based Linearization (OBL) approach which not only overcomes this drawback but also turns it to an advantage. In this method, the conservation equations are described in an operator form. By constructing a library of tabulated operators, the repeated work spent on complex phase behavior and property evaluation can be significantly reduced. We benchmark the parallel framework with analytical solutions under single-phase flow and multiphase flow. The results demonstrate that the parallel framework provides accurate simulation results for structured and unstructured grids. We validate that MPFA implemented in our parallel framework converges to real solutions when the permeability is a full tensor. Besides, several realistic cases have been rigorously tested confirming high computational capacity, efficiency, and accuracy of the advanced massively parallel framework for general-purpose reservoir simulation. With the implementation of MPFA and OBL approaches, the parallel framework is fully equipped for the simulation of problems with full tensor permeability, high-heterogeneities, and complex physical processes.
A Practical Probabilistic Upscaling Workflow for Compositional Reservoir Simulations of Miscible Gas Injection
Authors: de Souza Rios Victor , de Souza Rios Vinicius , Schiozer Denis José , Schmall dos Santos Luiz Otávio
Published: June 2020

Numerical reservoir simulation often requires upscaling of fine-scale detailed models and coarse-scale models are necessary to reduce computational time for dynamic evaluations. However, these simplifications may degenerate results due to loss of resolution of the small-scale phenomena, averaging of sub-grid heterogeneity and numerical dispersion, especially in oil fields where miscible gas is injected.

Most of the existing upscaling techniques focus on reproducing the results of a specific geological realization, in a deterministic approach. Nowadays, however, reservoir simulation studies commonly include uncertainty quantifications, which is performed by simulating multiple geological realizations. For that, the use of fine-scale models can be computationally prohibitive and this requires a proper procedure to upscale the coarse-scale simulation models in multiple realizations environment.

In this work, we propose and test an ensemble-level upscaling technique for compositional systems with miscible gas injection. The new approach considers the classical Koval factor, calculated for the fine-scale models, as a guide for selecting representative fine-scale models to train pseudo-functions for the coarse-models. Only a few fine models are simulated (about 1%), and the uncertainty quantification process with coarse-scale models can be significantly improved.

The proposed workflow is guided by ranking the fine-scale models in increasing order of their Koval Factor. We selected representative models and applied a two-step methodology to improve upscaled coarse-scale results for these models. We then propose a consistent procedure to expand the fitted pseudo-functions to all the coarse models, providing an effective ensemble-level upscaling.

The correlation between Koval factor and oil recovery is a useful guide to extrapolate the pseudo-functions obtained for each selected representative model, enabling better coarse-scale simulation results when multiple realizations are considered. This procedure can be applied for continuous miscible gas injection and can be adapted for WAG scheme.

This work was motivated by the lack of practical procedures to improve coarse-scale results at the ensemble-level. With our approach, we can better represent uncertainty quantification using coarse-scale models with reduced computational cost and requiring only a few fine-scale simulation runs.
Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach
Authors: Cumming J A , Botsas T , Jermyn I H , Gringarten A C
Published: June 2020

Objectives/Scope

A stable, single-well deconvolution algorithm has been introduced for well test analysis in the early 2000’s, that allows to obtain information about the reservoir system not always available from individual flow periods, for example the presence of heterogeneities and boundaries. One issue, recognised but largely ignored, is that of uncertainty in well test analysis results and non-uniqueness of the interpretation model. In a previous paper (SPE 164870), we assessed these with a Monte Carlo approach, where multiple deconvolutions were performed over the ranges of expected uncertainties affecting the data (Monte Carlo deconvolution).

Methods, Procedures, Process

In this paper, we use a non-linear Bayesian regression model based on models of reservoir behaviour in order to make inferences about the interpretation model. This allows us to include uncertainty for the measurements which are usually contaminated with large observational errors. We combine the likelihood with flexible probability distributions for the inputs (priors), and we use Markov Chain Monte Carlo algorithms in order to approximate the probability distribution of the result (posterior).

Results, Observations, Conclusions

We validate and illustrate the use of the algorithm by applying it to the same synthetic and field data sets as in SPE 164870, using a variety of tools to summarise and visualise the posterior distribution, and to carry out model selection.

Novel/Additive Information

The approach used in this paper has several advantages over Monte Carlo deconvolution: (1) it gives access to meaningful system parameters associated with the flow behaviour in the reservoir; (2) it makes it possible to incorporate prior knowledge in order to exclude non-physical results; and (3) it allows to quantify parameter uncertainty in a principled way by exploiting the advantages of the Bayesian approach.
A Comparison of Multi-Objective Optimization and Optimization with Constraints as a Tool for Reservoir History Matching and Characterization: Application to an Aquifer Gas Storage Case
Authors: Thomas Schaaf , Delphine Sinoquet
Published: June 2020

One of the final goals of any reservoir characterization study is to deliver reliable production forecasts. This is definitely a challenging task as the fluid flow dynamics is governed by non-linear equations: a small perturbation in the reservoir model inputs might have a large impact on the modelling outputs, thus the forecasts. Also, depending on the maturity of a project, engineers have various amounts and types of data to deal with and to history match through an optimization process.

Considering the case of a mature asset, for which massive datasets of various types are available, the standard history matching process is based on the minimization of a single objective function (history matching criteria), computed through weighted least squares formulation. The difficulty is then to (user) define properly the weight of each data set before the summation itself into the single objective function is performed.

To avoid this difficulty, two currently available but yet prospective – in geosciences application - optimization techniques are considered. The former is based on the definition of multiple objective functions (based on data types and/or location on the field) coupled to an optimization process. If all the objective functions minimize trends together, the user has still the flexibility to assess one by one the individual objective functions minimization. On the contrary, if the objective functions are minimizing/maximizing trends in competition (e.g. because of noisy data), then the derived Pareto front (in 2D case) would identify the location of optimal compromises. The latter is a sequential optimization approach based on single-objective constrained optimizations: optimize each objective at a time with constraints on the other objectives. The thresholds defined for the constraints on the objectives are derived from the results of the previous optimization results. This pragmatic approach allows to prioritize the objectives and tunes the expected accuracy on each data type.

Both approaches are applied to a real field gas storage asset with more than 40 years of exploitation history and various data types e.g. pressures, saturations as well as gas breakthrough of control wells, leading to the definition of multiple (possibly more than 2) objective functions. Both show promising results in terms of history matching quality and in terms of flexibility as the user might be able to consider, define and update dynamically alternative history matching strategies. These approaches might be considered as alternatives to the standard one for the history matching process, preliminary to the production forecasts computation, even if the associated challenges and complexity are growing accordingly to the number of objective functions.
A New Methodology for Naturally Fractured Reservoir Characterization: Use of Multi-Well Interference Tests Interpretation
Authors: Vincent Philippe , Portier Eric
Published: June 2020

Reservoir characterization is a key aspect during the appraisal and production phases of a field development. Understanding the reservoir property distribution and dynamic behavior reduces uncertainties and helps to improve recovery while optimizing investments. Modern seismic and logging tools, combined with core data, provide multi-disciplinary teams with better data quality. However, the reservoir heterogeneity and connectivity, often remain uncertain until several years of production have been achieved. This is true of naturally fractured reservoirs, for which fracture connectivity can only be characterized dynamically. In order to provide earlier dynamic connectivity information in a field development, interference tests have been developed to define whether parts of a reservoir are in communication, and to estimate reservoir properties between wells which is not possible from log measurements and correlations.

Interference tests are ideally conducted when a reservoir is in equilibrium with homogeneous and fully stabilized pressure through the entire field. This paper describes a new methodology for interference test interpretation when reservoir pressure is not stabilized, and also describes how to optimize multi-well interference operation sequencing. First, the observation well is tested, and second, active wells are produced in a sequence while the observation well bottom hole pressure (BHP) is still building up. Pressure changes only related to the interference are extracted from the pressure measurements at the observation well by removal of the build-up effects. Interpretation is subsequently performed to quantify reservoir properties such as matrix and fracture permeability and porosity to match interference time lag (also named time of flight), pressure and depletion amplitude. Permeability anisotropy and fracture connectivity are defined and quantified at the field scale.

The application of this new methodology to multi-well interference tests performed on a naturally fractured gas reservoir is presented in this paper. Using this methodology can prove connectivity through open natural fractures and quantify the fracture network properties even when there is a very small interference amplitude. Defining the extent of a natural fracture network and its contribution to the hydrocarbon production is crucial for naturally fractured reservoir development and reservoir management. In addition the described methodology was applied to calculate gas volumes dynamically connected to the wells.

The capability to interpret an interference test performed while the pressure measured at the observation well is still building up allows a significant operational time and cost reduction while ensuring accurate interpretation of reservoir parameters. This methodology can be applied to an interference test including a well pair or multiple wells.
Static and Dynamic Considerations for Perched Water and the Consequence in Reservoir Modelling
Authors: Larsen Alex , Ahmadhadi Faram , Øian Erlend , Nerbøvik Sivert
Published: June 2020

The initial water saturation in a reservoir is important for both hydrocarbon volume estimation and distribution of multi-phase flow properties such as relative permeability. Often, a practical reservoir engineering approach is to relate relative permeability to flow property regions by binning of the initial water saturation. The rationale behind this approach is that initial water saturation is related to both the pore-throat radius distribution and the wettability of the rock, both of which impact relative permeability. However, pore-throat radius and wettability are usually not explicitly included in geomodel property modelling. Therefore, the saturation height model (SHM) should not only capture an average hydrocarbon pore volume (HCPV), but also reflect the underlying mechanisms from hydrocarbon migration history and its impact on initial water saturation distribution.

This work defines a new terminology, "excess water", for more precise classification of SHM-scenarios in reservoirs where multiple mechanisms have interacted and caused a complex water saturation distribution. The physical basis for drainage and imbibition transition zones connected to both regional and perched aquifers is given. The distribution of initial water saturation in reservoirs containing excess water is demonstrated through numerical modelling of oil migration over millions of years.

High permeable reservoirs are more likely to have locally trapped water due to lower capillary forces. A static situation occurs in areas where the capillary forces cannot maintain a high enough water saturation for further water drainage. On the other hand, both high and low permeability reservoirs may have significant excess water due to still ongoing dynamical effects. In both cases, long distances for water to drain laterally to a regional aquifer enhances the possibility for a dynamic excess water situation.

The impact of excess water on well test results are demonstrated with focus on calculation of the product of permeability and sand thickness.
Numerical Modelling of Radial Crack Propagation in Cement Sheath During Hydraulic Fracturing
Authors: Yan Yan , Guan Zhichuan , Xu Yuqiang , Zhang Xuan , Yan Weijun
Published: June 2020

The cement sheath are damaged around the hole after perforation, and the micro-cracks in the cement sheath will cause fluid channeling during hydraulic fracturing. Focused on this problem, a numerical model was set up to calculate the crack propagation length in cement sheath during hydraulic fracturing by using the Cohesive Zone Method (CZM). Then the influence of different parameters on the unsealing length of cement sheath during hydraulic fracturing was analyzed. The results show that higher casing pressure can help to reduce the unsealing length of cement sheath. It is significant to perforate with lower density and phase to ensure the sealing integrity of the cement sheath. This research can evaluate the sealing performance of the cement sheath during hydraulic fracturing and give some guiding for the design of fracturing schemes.
Increasing Oil Recovery from Unconventional Shale Reservoirs Using Cyclic Carbon Dioxide Injection
Authors: Fakher Sherif , El-Tonbary Ahmed , Abdelaal Hesham , Elgahawy Youssef , Imqam Abdulmohsin
Published: June 2020

Unconventional shale reservoirs have become and large unconventional supplier of oil and gas especially in North America. They are usually produced from using hydraulic fracturing which produces and average of 7-10% per well. This research studies the application of carbon dioxide (CO2) enhanced oil recovery (EOR) in shale reservoirs to increase oil recovery to more than 20%. Cyclic CO2 injection was used to conduct all experiments rather than flooding. The main difference between both procedures and the advantage of cyclic injection over flooding in shale reservoirs is explained. A specially designed vessel was constructed and used to mimic the cyclic CO2 injection procedure. The effect of CO2 soaking pressure, CO2 soaking time, and number of soaking cycles on oil recovery was investigated. Results showed that cyclic CO2 injection can increase oil recovery substantially, however there are some points that must be taken into consideration including optimum soaking pressure and time in order to avoid a waste of time and capital with no significant increase in oil recovery. This research not only provides an experimentally backed conclusion on the ability of cyclic CO2 injection to increase oil recovery from shale reservoirs, it also points to some major issue that should be considered when applying this EOR method in unconventional shale in order to optimize the overall procedure.
Conformance Gel Design for High Temperature Reservoirs
Authors: Juárez José Luis , Rodriguez María Rosario , Montes Jesús , Trujillo Francisco Daniel , Monzòn Jorge , Dupuis Guillaume , Gaillard Nicolas
Published: June 2020

A gel conformance treatment is a complex process that has to be adapted to reservoir conditions such as pH, temperature and salinity. For instance, high temperature and low salinity reduce gelation time making field operations difficult. Understanding the interactions between functional groups of polymers, crosslinkers and retardants is essential to control the gelation process considering kinetic, strength and stability of the gel.

The objective of this work is to better understand chemistry mechanisms in gel formation to design an optimal gelation system for in-depth conformance treatment in a high temperature reservoir.

The target reservoir conditions are a low salinity water (TDS 6 g/L) and a temperature of 100°C. The ultimate goal is to select a polymer / crosslinker / retardant system with a gelation time above 7h, and Sydansk's gel strength of "G" that is stable over more than one week.

This work contains a stepwise process to design a conformance gel based on the understanding of the chemical interactions between polymers and crosslinkers. In a first step, a rheology evaluation of different polymers containing ATBS was performed. Then, a wide range of combinations between polymers and crosslinkers with and without retardants was studied. The study of the formation of gels was carried out in bottle test (Sydansk's gel-strength code) in order to provide information about the gel formation, the gel kinetics, the gel strength and the stability of gel as function of time.

Finally, the best gelant solutions were selected to further study the evolution of the complex viscosity over time using a rheometer with a high pressure cell that mimics the reservoir conditions.

This study provides new knowledge of polymer gelation at high temperature; the main findings are the following: Gelation depends on the chemical composition of polymer and crosslinker.Gelation time depends on the particular polymer / crosslinker system and not only on whether the crosslinker is organic or not.Concentration plays a very important role in the formation of certain gels.The polymer molecular mass dependence is not as clear as it might be assumed at first. The kinetics of the polymer / PEI crosslinker systems can be delayed by retardants that contain inhibitor groups.

This positive laboratory results will be complemented with simulation studies to assess the field implementation of these new conformance gels.

The main novelty of this work is the use of thermal resistant polymers that combined with the adequate crosslinkers and retardants allowed the generation of a conformance gel at 100°C. The information provided in this study will be useful for the design of conformance treatment for other field conditions. The close communication and integration between polymer manufacturers and operators was crucial for the interpretation of the results and gel optimization.