We present expressions to compute the inverse of a Cauchy-type singular integral equation representing the relation between a double-peaked Coulomb stress in a fault or fracture and the resulting slip gradient in two distinct collinear slip patches. In particular we consider a situation where the patches are close enough to account for the influence of the slip gradient in one patch on the slip-induced shear stress in the other patch and vice versa. This situation can occur during depletion-induced or injection-induced fault slip in subsurface reservoirs for, e.g., natural gas production, hydrogen or CO₂ storage, or geothermal operations. The theory for a single slip patch is well-developed but the situation is less clear for a configuration with two patches although the monographs of Muskhelishvili (1953) and Weertman (1996) provide earlier results. We show that the general inverse solution for the coupled two-patch problem requires six auxiliary conditions to ensure six physical requirements: boundedness of the slip gradient at the four end points of the slip patches and vanishing of the integrals of the slip gradient over the patches. Mathematically, the presence of two additional conditions, as compared to earlier formulations, corresponds to two undetermined coefficients in the general solution of the governing integral equation. Numerical simulation confirms that at least one of these is always non-zero in the coupled situation. For a coupled double-patch case with a symmetric pre-slip Coulomb stress pattern, the general inverse solution requires three auxiliary conditions. Moreover the conditions for the asymmetric case may be reduced to a set of four again, but these are different from the sets of four obtained earlier by Muskhelishvili (1953) and Weertman (1996). We illustrate the theory with a numerical example in which the evaluation of the Cauchy integrals is performed with a modified version of augmented Gauss–Chebyshev quadrature that relies on analytical inversion.

@en

We critically review the derivation of closed-form analytical expressions for elastic displacements, strains, and stresses inside a subsurface reservoir undergoing pore pressure changes using inclusion theory. Although developed decades ago, inclusion theory has been used recently by various authors to obtain fast estimates of depletion-induced and injection-induced fault stresses in relation to induced seismicity. We therefore briefly address the current geomechanical relevance of this method, and provide a numerical example to demonstrate its use to compute induced fault stresses. However, the main goal of our paper is to correct some erroneous assumptions that were made in earlier publications. While the final expressions for the poroelastic stresses in these publications were correct, their derivation contained conceptual mistakes due to the mathematical subtleties that arise because of singularities in the Green's functions. The aim of our paper is therefore to present the correct derivation of expressions for the strains and stresses inside an inclusion and to clarify some of the results of the aforementioned studies. Furthermore, we present two conditions that the strain field must satisfy, which can be used to verify the analytical expressions.

@en

Pore pressure fluctuation in subsurface reservoirs and its resulting mechanical response can cause fault reactivation. Numerical simulation of such induced seismicity is important to develop reliable seismic hazard and risk assessments. However, modeling of fault reactivation is quite challenging, especially in the case of displaced faults, i.e., faults with non-zero offset. In this paper, we perform a systematic benchmarking study to validate two recently developed numerical methods for fault slip simulation. Reference solutions are based on a semi-analytical approach that makes use of inclusion theory and Cauchy-type singular integral equations. The two numerical methods both use finite volume discretizations, but they employ different approaches to represent faults. One of them uses a conformal discrete fault model (DFM) while the other employs an embedded (non-conformal) fault model. The semi-analytical test cases cover a vertical frictionless fault, and inclined displaced faults with constant friction and slip-weakening friction. It was found that both numerical methods accurately represent pre-slip stress fields caused by pore pressure changes. Moreover, they also successfully cope with a vertical frictionless fault. However, for the case with an inclined displaced fault with a constant friction coefficient, the embedded method can not converge for the post-slip phase, whereas the DFM successfully coped with both constant and slip-weakening friction coefficients. In its current implementation, the DFM is therefore the model of choice when accurate simulation of local faulted systems is required.@en

This note provides the derivation of closed-form expressions for elastic displacements, strains, and stresses inside an inclusion. Jansen et al. (2019) and Wu et al. (2021) obtained correct expressions for the stresses inside an inclusion, but their derivation of these expressions contained mistakes. In this note, the correct derivation of expressions for the stresses inside an inclusion is presented and some of the results of the aforementioned studies are clarified.@en

We consider steady-state single-phase confined flow through a subsurface porous layer containing a displaced, fully conductive fault causing a sudden jump in the flow path, and we employ (semi-)analytical techniques to compute the corresponding pressures and fault stresses. In particular, we obtain a new solution for the pressure field with the aid of conformal mapping and a Schwarz–Christoffel transformation. Moreover, we use an existing technique to compute the poro-elastic stress field with the aid of inclusion theory. The additional resistance to fluid flow provided by a displaced fault, relative to the resistance in a layer without a fault, is a function of dip angle, fault throw divided by reservoir height, and reservoir width divided by reservoir height. Fluid flow has a larger effect on fault stresses in case of injection than in case of depletion, where injection with up-dip flow results in increased zones of fault slip near the bottom of the reservoir. Opposedly, injection with down-dip flow results in increased slip near the top of the reservoir. An order-of-magnitude estimate of the effect of steady-state flow across displaced faults in the Groningen natural gas reservoir shows that the effect on fault stresses is probably negligible. A similar estimate of the effect in low-enthalpy geothermal doublets indicates that steady-state flow may possibly play a small role, in particular close to the injector, but site-specific assessments will be necessary to quantify the effect.

@en

This note provides unregularized and regularized closed-form analytical expressions for the depletion-induced or injection-induced pre-slip Coulomb stresses in two-dimensional displaced dip-slip faults. The regularization serves to remove logarithmic singularities and jump-discontinuities in the unregularized formulation. The expressions are identical to those in Appendices A and B of Jansen & Meulenbroek (2022): Netherlands Journal of Geosciences 101 e13, except for the correction of a small error in the regularized formulation. In numerical examples the difference of the correction is hardly noticeable, but it ensures that the corrected formulation is internally consistent in the sense that integrals of stresses and pressure along a fault are identical for the unregularized and regularized expressions.@en

Recent laboratory and field studies suggest that temporal variations in injection patterns (e.g., cyclic injection) might trigger less seismicity than constant monotonic injection. This study presents results from uniaxial compressive experiments performed on Red Felser sandstone samples providing new information on the effect of stress pattern and rate on seismicity evolution. Red Felser sandstone samples were subjected to three stress patterns: cyclic recursive, cyclic progressive (CP), and monotonic stress. Three different stress rates (displacement controlled) were also applied: low, medium, and high rates of 10⁻⁴ mm/s, 5 × 10⁻⁴ mm/s, and 5 × 10⁻³ mm/s, respectively. Acoustic emission (AE) waveforms were recorded throughout the experiments using 11 AE transducers placed around the sample. Microseismicity analysis shows that (i) Cyclic stress patterns and especially cyclic progressive ones are characterized by a high number of AE events and lower maximum AE amplitude, (ii) among the three different stress patterns, the largest b-value (slope of the log frequency-magnitude distribution) resulted from the cyclic progressive (CP) stress pattern, (iii) by reducing the stress rate, the maximum AE energy and final mechanical strength both decrease significantly. In addition, stress rate remarkably affects the detailed AE signature of the events classified by the distribution of events in the average frequency (AF)—rise angle (RA) space. High stress rates increase the number of events with low AF and high RA signatures. Considering all elements of the AE analysis, it can be concluded that applying cyclic stress patterns in combination with low-stress rates may potentially lead to a more favourable induced seismicity effect in subsurface-related injection operations.

@en

An increasing number of geo-energy applications require the quantitative prediction of hydromechanical response in subsurface. Integration of mass, momentum, and energy conservation laws becomes essential for performance and risk analysis of enhanced geothermal systems, stability assessment of CO2 sequestration and hydrogen storage, resolving the issue of induced seismicity. The latter problem is of particular interest because it exposes safety risks to people and surface infrastructure.

Implicit coupling of conservation laws is computationally demanding and the solution procedure often uses different numerical methods for different laws that complicates simulation. Recently developed Finite Volume (FV) schemes for poromechanics present a unified approach for the modeling of conservation laws in geo-energy applications. Contact mechanics at faults requires special attention due to the inequality constraints it imposes and nonlinear friction laws that strongly affect the occurrence of seismicity.

We develop a cell-centered FV scheme for the purpose of integrated simulation in Delft Advanced Research Terra Simulator (DARTS) platform. The scheme proposes a unified numerical framework capable to resolve conservation laws in a fully implicit manner using a single collocated grid. Coupled multi-point flux and multi-point stress approximations provide mass, momentum, and heat fluxes at the faces of the computational grid. We use a conformal discrete fracture model to incorporate faults, where the multi-point approximations of fluxes respect the discontinuity in displacements. The block-partitioned preconditioner that takes the advantage of linear structure of the coupled problem is developed to facilitate the performance of the simulation.

The proposed numerical scheme are validated against analytical and numerical solutions in a number of test cases. The convergence and stability of the schemes are investigated. It is found that the developed scheme is indeed accurate, stable, and efficient. Thereafter, we demonstrate the applicability of the approach to model fault reactivation at the laboratory scale. In a core injection test, we validate the results of simulation against experimental measurements. Next, we investigate the performance of the different preconditioning strategies. The proposed block-partitioned preconditioning strategy demonstrates the scalability and efficiency of the numerical framework.@en

A smoothed embedded finite-volume modeling (sEFVM) method is presented for faulted and fractured heterogeneous poroelastic media. The method casts a fully coupled strategy to treat the coupling between fault slip mechanics, deformation mechanics, and fluid flow equations. This ensures the stability and consistency of the simulation results, especially, as the fault slip is implicitly found through an iterative prediction-correction procedure. The computational grid is generated independently for embedded faults and rock matrix. The efficiency is further enhanced by extending the finite-volume discrete space by introducing only one degree of freedom per fault element. The embedded approach can lead to an oscillatory stress field at the fault, which damages the robustness of the implicit slip detection strategy. To resolve this challenge, a smoothed embedded strategy is devised, in which the stress and slip profiles are post processed within the iterative loops by fitting the best curve based on a least-square error criterion. The sEFVM provides locally conservative mass flux and stress fields, on staggered grid. Its performance is further investigated for several proof-of-the-concept test cases, including a multiple fault system in a heterogeneous domain. Results indicate that the method develops a promising approach for field-scale relevant simulation of induced seismicity.

@en

We address aseismic fault slip and the onset of seismicity resulting from depletion-induced or injection-induced stresses in reservoirs with pre-existing vertical or inclined faults. Building on classic results, we discuss semi-analytical modelling techniques for fault slip including dislocation theory, Cauchy-type singular integral equations and the use of Chebyshev polynomials for their solution and an eigenvalue-based stability analysis. We consider slip patch development during depletion for faults with zero, constant static and slip-weakening friction, and our results confirm earlier findings based on numerical simulation, in particular the aseismic growth of two slip patches that may subsequently merge and/or become unstable resulting in nucleation of seismic slip. New findings include improved approximate expressions for the induced seismic moment per unit strike length and a description of the effect of coupling between the slip patches which affects both forward simulation and eigenvalue computation for high values of the ratio of fault throw to reservoir height. Our implementation based on analytical inversion and semi-analytical integration with Chebyshev polynomials is more efficient and more robust than our numerical integration approach. It is not yet well suited for Monte Carlo simulation, which typically requires sub-second simulation times, but with some further development that option seems to be within reach. Moreover, our results offer a possibility for embedded fault modelling in large-scale numerical simulation tools.

@en

We present a scalable collocated Finite Volume Method (FVM) to simulate induced seismicity as a result of pore pressure changes. A discrete system is obtained based on a fully-implicit fully-coupled description of flow, elastic deformation, and contact mechanics at fault surfaces on a flexible unstructured mesh. The cell-centered collocated scheme leads to a convenient integration of the different physical equations, as the unknowns share the same discrete locations on the mesh. Additionally, a generic multi-point flux approximation is formulated to treat heterogeneity, anisotropy, and cross-derivative terms for both flow and mechanics equations. The resulting system, though flexible and accurate, can lead to excessive computational costs for field-relevant applications. To resolve this limitation, a scalable processing algorithm is developed and presented. Several proof-of-concept numerical tests, including benchmark studies with analytical solutions, are investigated. It is found that the presented method is indeed accurate and efficient; and provides a promising framework for accurate and efficient simulation of induced seismicity in various geoscientific applications.

@en

We explore and develop a Proper Orthogonal Decomposition (POD)-based deflation method for the solution of ill-conditioned linear systems, appearing in simulations of two-phase flow through highly heterogeneous porous media. We accelerate the convergence of a Preconditioned Conjugate Gradient (PCG) method achieving speed-ups of factors up to five. The up-front extra computational cost of the proposed method depends on the number of deflation vectors. The POD-based deflation method is tested for a particular problem and linear solver; nevertheless, it can be applied to various transient problems, and combined with multiple solvers, e.g., Krylov subspace and multigrid methods.

@en

We develop a collocated Finite Volume Method (FVM) to study induced seismicity as a result of pore pressure fluctuations. A discrete system is obtained based on a fully-implicit coupled description of flow, elastic deformation, and contact mechanics at fault surfaces on a fully unstructured mesh. The cell-centered collocated scheme leads to convenient integration of the different physical equations, as the unknowns share the same discrete locations on the mesh. Additionally, a multi-point flux approximation is formulated in a general procedure to treat heterogeneity, anisotropy, and cross-derivative terms for both flow and mechanics equations. The resulting system, though flexible and accurate, can lead to excessive computational costs for field-relevant applications. To resolve this limitation, a scalable parallel solution algorithm is developed and presented. Several proof-of-concept numerical tests, including benchmark studies with analytical solutions, are investigated. It is found that the presented method is indeed accurate, stable and efficient; and as such promising for accurate and efficient simulation of induced seismicity.

@en

This booklet provides additional information to the work of art 'Soft Layer' located in front of the faculty of Civil Engineering and Geosciences. This piece of art is an initiative of students and alumni of the Mijnbouwkundige Vereeniging and has been revealed on the 24th of February, 2020.@en

In data assimilation problems, various types of data are naturally linked to different spatial resolutions (e.g., seismic and electromagnetic data), and these scales are usually not coincident to the subsurface simulation model scale. Alternatives like upscaling/downscaling of the data and/or the simulation model can be used, but with potential loss of important information. Such alternatives introduce additional uncertainties which are not in the nature of the problem description, but the result of the post processing of the data or the geo-model. To address this issue, a novel multiscale (MS) data assimilation method is introduced. The overall idea of the method is to keep uncertain parameters and observed data at their original representation scale, avoiding upscaling/downscaling of any quantity. The method relies on a recently developed mathematical framework to compute adjoint gradients via a MS strategy in an algebraic framework. The fine-scale uncertain parameters are directly updated and the MS grid is constructed in a resolution that meets the observed data resolution. This formulation therefore enables a consistent assimilation of data represented at a coarser scale than the simulation model. The misfit objective function is constructed to keep the MS nature of the problem. The regularization term is represented at the simulation model (fine) scale, whereas the data misfit term is represented at the observed data (coarse) scale. The computational aspects of the method are investigated in a simple synthetic model, including an elaborate uncertainty quantification step, and compared to upscaling/downscaling strategies. The experiment shows that the MS strategy provides several potential advantages compared to more traditional scale conciliation strategies: (1) expensive operations are only performed at the coarse scale; (2) the matched uncertain parameter distribution is closer to the “truth”; (3) faster convergence behavior occurs due to faster gradient computation; and (4) better uncertainty quantification results are obtained. The proof-of-concept example considered in this paper sheds new lights on how one can reduce uncertainty within fine-scale geo-model parameters with coarse-scale data, without the necessity of upscaling/downscaling the data nor the geo-model. The developments demonstrate how to consistently formulate such a gradient-based MS data assimilation strategy in an algebraic framework which allows for implementation in available computational platforms.

@en

We present an efficient workflow that combines multiscale (MS) forward simulation and stochastic gradient computation - MS-StoSAG - for the optimization of well controls applied to waterflooding under geological uncertainty. A two-stage iterative Multiscale Finite Volume (i-MSFV), a mass conservative reservoir simulation strategy, is employed as the forward simulation strategy. MS methods provide the ability to accurately capture fine scale heterogeneities, and thus the fine-scale physics of the problem, while solving for the primary variables in a more computationally efficient coarse-scale simulation grid. In the workflow, the construction of the basis fuctions is performed at an offline stage and they are not reconstructed/updated throughout the optimization process. Instead, inaccuracies due to outdated basis functions are addressed by the i-MSFV smoothing stage. The Stochastic Simplex Approximate Gradient (StoSAG) method, a stochastic gradient technique is employed to compute the gradient of the objective function using forward simulation responses. Our experiments illustrate that i-MSFV simulations provide accurate forward simulation responses for the gradient computation, with the advantage of speeding up the workflow due to faster simulations. Speed-ups up to a factor of five on the forward simulation, the most computationally expensive step of the optimization workflow, were achieved for the examples considered in the paper. Additionally, we investigate the impact of MS parameters such as coarsening ratio and heterogeneity contrast on the optimization process. The combination of speed and accuracy of MS forward simulation with the flexibility of the StoSAG technique allows for a flexible and efficient optimization workflow suitable for large-scale problems.@en

An enhanced-oil-recovery (EOR) pilot test has multiple goals, among them to be profitable (if possible), demonstrate oil recovery, verify the properties of the EOR agent in situ, and provide the information needed for scaleup to an economical process. Given the complexity of EOR processes and the inherent uncertainty in the reservoir description, it is a challenge to discern the properties of the EOR agent in situ in the midst of geological uncertainty. We propose a numerical case study to illustrate this challenge: a polymer EOR process designed for a 3D fluvial-deposit water/oil reservoir. The polymer is designed to have a viscosity of 20 cp in situ. We start with 100 realizations of the 3D reservoir to reflect the range of possible geological structures honoring the statistics of the initial geological uncertainties. For a population of reservoirs representing reduced geological uncertainty after 5 years of waterflooding, we select three groups of 10 realizations out of the initial 100, with similar water-breakthrough dates at the four production wells. We then simulate 5 years of polymer injection. We allow that the polymer process might fail in situ and viscosity could be 30% of that intended. We test whether the signals of this difference at injection and production wells would be statistically significant in the midst of geological uncertainty. Specifically, we compare the deviation caused by loss of polymer viscosity with the scatter caused by the geological uncertainty using a 95% confidence interval. Among the signals considered, polymer-breakthrough time, minimum oil cut, and rate of rise in injection pressure with polymer injection provide the most-reliable indications of whether a polymer viscosity was maintained in situ.

@en

We propose a novel adaptive, adjoint-based, iterative multiscale finite volume (i-MSFV) method. The method aims to reduce the computational cost of the smoothing stage of the original i-MSFV method by selectively choosing fine-scale sub-domains (or sub-set of primary variables) to solve for. The selection of fine-scale primary variables is obtained from a goal-oriented adjoint model. An adjoint-based indicator is utilized as a criterion to select the primary variables having the largest errors. The Lagrange multipliers from the adjoint model can be interpreted as sensitivities of the objective function value with respect to deviations from the constraints. In case of adjoining the porous media flow equations with Lagrange multipliers, this implies that the multipliers are the sensitivities of the objective function with respect to the residuals of the flow equations, i.e., to the residual error that remains after approximately solving linear equations with the aid of an iterative solver. This allow us to recognize at which locations the solution contains more errors. More specifically, we propose a modification to the i-MSFV method to adaptively reduce the size of the fine-scale system that must be smoothed. The aim is to make the fine-scale smoothing stage less computationally demanding. To that end, we introduce a goal-oriented, adjoint-based fine-scale system reduction criterion. We demonstrate the performance of our method via single-phase, incompressible flow simulation models with challenging geological settings and using a history-matching like misfit objective function as the goal. The performance of the newly introduced method is compared to the original i-MSFV method. We investigate the adaptivity versus accuracy of the method and demonstrate how the solution accuracy varies by varying the number of unknowns selected to be smoothed. It is shown that the method can provide accurate solutions at reduced computational cost. The proof-of-concept applications indicate that the method deserves further investigations.@en

We introduce a semi-analytical iterative multiscale derivative computation methodology that allows for error control and reduction to any desired accuracy, up to fine-scale precision. The model responses are computed by the multiscale forward simulation of flow in heterogeneous porous media. The derivative computation method is based on the augmentation of the model equation and state vectors with the smoothing stage defined by the iterative multiscale method. In the formulation, we avoid additional complexity involved in computing partial derivatives associated to the smoothing step. We account for it as an approximate derivative computation stage. The numerical experiments illustrate how the newly introduced derivative method computes misfit objective function gradients that converge to fine-scale one as the iterative multiscale residual converges. The robustness of the methodology is investigated for test cases with high contrast permeability fields. The iterative multiscale gradient method casts a promising approach, with minimal accuracy-efficiency tradeoff, for large-scale heterogeneous porous media optimization problems.

@en