Spatial Distribution Of Permeability Research Articles

The inverse problem of permeability identification for multiphase flow in porous media

Estimating permeability heterogeneity is a key component in modeling multiphase flow in geological porous media such as aquifers and reservoirs. The inverse problem of identifying permeability has been thoroughly studied regarding single-phase flow, however, hardly in two-phase flow problems. In this work, we study the inverse problem of estimating the spatial distribution of permeability in two-phase flow, considering a known saturation distribution, and using an iterative method based on inverting the capillary pressure–permeability relationship. The method is evaluated considering many different problem parameters and shown to be accurate for many cases in both oil–water and CO2–water three-dimensional systems. Large errors are observed when there is significant water trapping due to capillary effects and when conditions are dominated by viscosity. A range of optimal parameters is determined in which the inverse method is most accurate. These parameters can be used in applications, for example, when designing coreflooding experiments for permeability estimation. The estimated permeability is then used to predict the saturation and pressure distributions of two-phase flow with different injection flow rates and fluid fractions. The models are shown to be accurate when permeability estimations are accurate. The results support the possibility of calibrating a numerical model to coreflooding experiments and then using it to replace additional experiments, e.g., for evaluating flow rate effects.

Transport mechanisms of hydrothermal convection in faulted tight sandstones

Abstract. Motivated by the unknown reasons for a kilometre-scale high-temperature overprint of 270–300 ∘C in a reservoir outcrop analogue (Piesberg quarry, northwestern Germany), numerical simulations are conducted to identify the transport mechanisms of the fault-related hydrothermal convection system. The system mainly consists of a main fault and a sandstone reservoir in which transfer faults are embedded. The results show that the buoyancy-driven convection in the main fault is the basic requirement for elevated temperatures in the reservoir. We studied the effects of permeability variations and lateral regional flow (LRF) mimicking the topographical conditions on the preferential fluid-flow pathways, dominant heat-transfer types, and mutual interactions among different convective and advective flow modes. The sensitivity analysis of permeability variations indicates that lateral convection in the sandstone and advection in the transfer faults can efficiently transport fluid and heat, thus causing elevated temperatures (≥269 ∘C) in the reservoir at a depth of 4.4 km compared to purely conduction-dominated heat transfer (≤250 ∘C). Higher-level lateral regional flow interacts with convection and advection and changes the dominant heat transfer from conduction to advection in the transfer faults for the low permeability cases of sandstone and main fault. Simulations with anisotropic permeabilities detailed the dependence of the onset of convection and advection in the reservoir on the spatial permeability distribution. The depth-dependent permeabilities of the main fault reduce the amount of energy transferred by buoyancy-driven convection. The increased heat and fluid flows resulting from the anisotropic main fault permeability provide the most realistic explanation for the thermal anomalies in the reservoir. Our numerical models can facilitate exploration and exploitation workflows to develop positive thermal anomaly zones as geothermal reservoirs. These preliminary results will stimulate further petroleum and geothermal studies of fully coupled thermo–hydro–mechanical–chemical processes in faulted tight sandstones.

Prediction of carbonate rock facies from core probe permeability measurements and well log data: a case study from carbonate reservoirs, Phu Khanh basin

Probe permeameter (also known as Mini-permeameter) has been widely used in many field and laboratory applications where in-situ measurements and spatial distributions of permeability are needed. Mini-permeameter measurements have become popular techniques for collecting localized permeability measurements in both laboratory and field applications. It is designed to obtain fast, cheap, intensive and non-destructive permeability measurements and to describe the spatial arrangement of permeability. Currently the probe permeability meter is designed and manufactured as a portable air permeability for field applications and to be used in outcrop and core samples. In this instrument, the permeability is measured by air that flows from the samples to be measured into an air chamber through the vacuum created by increasing the volume of the chamber. In carbonate reservoirs, permeability predicted from pure porosity-permeability empirical relationship is often difficult due to complex rock pore systems leading to poor porosity-permeability relations. Once the relationships between permeability and textural rock properties are clearly established in carbonates, they can provide better permeability predictions from porosity data. Rock texture is an important parameter for the understanding of the porosity and permeability characteristics of carbonate reservoirs. In addition to predicting carbonate rock facies from routine core plug porosity and permeability measurements, there is an approach to determine carbonate reservoir facies based on core-plug probe permeability. The results of the probe permeability measurements, in this paper, can be used in combination with the porosity values derived from the well logs to classify and predict rock facies in carbonate cored or uncored reservoirs in Phu Khanh basin.

Stochastic inversion of tracer test data with seismicity constraint for permeability imaging in enhanced geothermal reservoirs

Inference of permeability distribution in an enhanced geothermal reservoir is crucial for the sustainable management of geothermal energy. However, interpreting the uneven permeability distribution in a deep geothermal reservoir remains a challenging task because in practice there often are merely one or two wells available for hydrogeophysical tests. Considering that the induced seismicity data are widely captured during reservoir stimulation in enhanced geothermal systems, a framework of tracer test data inversion with the constraint of induced seismic data is developed for permeability imaging. Hydraulic diffusivity, representing the prior estimation of permeability, is inferred from the occurrence time of seismic events. This is followed by the determination of a petrophysical model, which relates hydraulic diffusivity to permeability, by tracer test data inversion based on the Markov chain Monte Carlo algorithm. Implementation of the seismicity-constraint tracer data inversion algorithm in the Habanero enhanced geothermal system, Australia, demonstrates that our inversion model allows uneven permeability estimation at field scale in shorter burn-in period and lower uncertainty than the traditional inversion model without seismicity constraint. Using the estimated permeability in the hydrothermal model enables accurate prediction of thermal performance in a 150 day trial-production test. Results indicate that this algorithm can reliably characterize the spatial distribution of permeability in deep enhanced reservoirs, based on the tracer test via doublet wells.

Permeability extraction from multiple well logs using particle swarm optimization based factor analysis

In this paper, we present an innovative factor analysis algorithm for hydrocarbon exploration to estimate the intrinsic permeability of reservoir rocks from well logs. Unlike conventional evaluation methods that employ a single or a limited number of data types, we process simultaneously all available data to derive the first statistical factor and relate it to permeability by regression analysis. For solving the problem of factor analysis, we introduce an improved particle swarm optimization method, which searches for the global minimum of the distance between the observed and calculated data and gives a quick estimation for the factor scores. The learning factors of the intelligent computational technique such as the cognitive and social constants are specified as hyperparameters and calculated by using simulated annealing algorithm as heuristic hyperparameter estimator. Instead of the arbitrary fixation of these hyperparameters, we refine them in an iterative process to give reliable estimation both for the statistical factors and formation permeability. The estimated learning parameters are consistent with literature recommendations. We demonstrate the feasibility of the proposed well-log analysis method by a Hungarian oilfield study involving open-hole wireline logs and core data. We determine the spatial distribution of permeability both along a borehole and between more wells using the factor analysis approach, which serves as efficient and reliable multivariate statistical tool for advanced formation evaluation and reservoir modeling.

Development of multi-physics numerical simulator for describing coupled thermal-hydraulicmechanical-chemical processes within fractured rocks

When investigating the long-term performance of various rock engineering projects, such as the geological disposal of high-level radioactive waste (HLW), enhanced geothermal system (EGS), it is essential to accurately predict the permeability evolution within fractured rocks due to coupled thermal-hydraulic-mechanical-mechanical (THMC) phenomena including fracture generation and subsequent geochemical creep. In this paper, we introduced our coupled THMC simulator that can explicitly introduce the fracture surfaces to describe the permeability change within fractured rocks as realistically as possible. The numerical results of long-term change in rock permeability during a disposal period of HLW computed by our simulator, showed that the permeability reduction with time was observed only within specific fractures where the geochemical creep (i.e., pressure dissolution) had been activated depending on the heterogeneous properties of each fracture. It may suggest that our simulator has a possibility to reveal the detailed spatial distribution of permeability within rock masses containing the newly generated fractures.

Combining autoencoder neural network and Bayesian inversion to estimate heterogeneous permeability distributions in enhanced geothermal reservoir: Model development and verification

Determining permeability distributions in reservoirs is critical for the management of limited earth resources. While hydraulic fracturing is widely used to enhance the permeability of deep geothermal, gas and oil reservoirs, it remains challenging to infer heterogeneous distributions of permeability. Typically, a limited number of boreholes are available at which reservoir imaging and tracer testing can be conducted. The number of observations is often far fewer than the number of estimable permeability parameters, making model inversion ill-posed. To overcome this problem, the autoencoder neural network was combined with a Bayesian inversion algorithm based on Markov Chain Monte Carlo (MCMC) sampling, in order to estimate the spatial distributions of permeability in an enhanced geothermal reservoir, conditional to temperature and outflow rate observations from a single-well-injection-withdrawal test (SWIW). The autoencoder neural network was used to reduce parameter dimensionality by four orders of magnitude. MCMC sampling was used to estimate low-dimensional parameters via inversion of SWIW observations. A high-resolution permeability distribution was reconstructed from the low-dimensional parameterization through reapplication of the autoencoder neural network. Application to a synthetic enhanced geothermal system demonstrated that the methodology achieved rapid stabilization and low permeability estimation error (<10%). By combining deep-learning method with Bayesian inversion, permeability distributions in geo-energy reservoirs can be estimated from a limited set of borehole data.

Numerical and Experimental Study to Determine the Permeability Anisotropy in Porous Rocks from Probe Permeameter Measurements

Probe permeameter has been widely used to obtain measurements and spatial distributions of permeability in both the laboratory and field outcrop applications. It provides cheap, fast, intensive, and nondestructive permeability measurements. In the literature, the difference between steady-state and unsteady-state measurements and the effects of heterogeneity and anisotropy on probe permeameter measurements have been investigated both numerically and experimentally. However, the available work provides a method for the determination of the permeability in two principal directions only. This study fills such a gap by providing a novel solution for the steady-state single-phase flow problem for the determination of permeability anisotropy in the three principal directions using probe permeameter measurements. The solution was obtained by solving the diffusivity equation describing the steady-state flow of a single-phase fluid in a three-dimensional (3D) rectangular system. Different permeability anisotropy ratios were tested for different anisotropy cases starting from a fully isotropic sample to a fully anisotropic sample. The obtained results are presented graphically in a dimensionless space. The dimensionless parameters include the dimensionless pressure and anisotropy ratios in different flow directions. A practical procedure based on the solution is then described to evaluate the permeability in a 3D rectangular rock sample. This method requires a few measurements of steady-state flow rate and pressure drop conducted using the probe permeameter at different directions on a rectangular rock sample. The applicability of the proposed solution and developed technique is demonstrated by conducting probe permeameter measurements on three different directions of one cubical cement sample and two outcrop carbonate samples. The results obtained from the proposed method show good match (an average root-mean-square error of 0.653 mD) when compared to the reference permeability values measured on directional plugs by conventional nitrogen permeameter. The procedure described in this work can be used to have a quick and robust evaluation of permeability anisotropy from rock samples in either outcrop or laboratory studies.

Groundwater recharge to a structurally complex aquifer system on the island of Tobago (Republic of Trinidad and Tobago)

Trinidad and Tobago is a developing two-island nation in the Lesser Antilles of the Caribbean. Tobago is the smaller island and has small highly heterogeneous aquifers composed of igneous and metamorphic crystalline rock with strong structural controls on the spatial distribution of permeability. Hydrogeologic analyses of the water budget and groundwater production suggest that portions of the island are underlain by prolific fractured-rock aquifer systems. This study quantifies the amount and spatial distribution of recharge, as well as the fraction of recharge captured by groundwater pumping, using historical data, new field data, remote sensing data, multiple storage quantification methods and stable isotope analysis. Despite extensive freshwater withdrawals, groundwater production reaches only ~10% of annual groundwater recharge. Groundwater capture zones are created using a first-order hydrologic balance approach and with backward particle tracking in a steady-state groundwater model. Both approaches to generating capture zones suggest that many wells capture water from outside their topographic watershed. The location of sustainable, high yield, fresh potable groundwater wells less than 1 km from the coast, that have fractured bedrock intakes well below sea level, supports the concept of a rigorous and active groundwater flow system. Understanding the hydrogeology of small bedrock island aquifers is critical to evaluating groundwater resources, especially in the Caribbean where there is strong seasonality in precipitation, finite surface-water storage and increases in potable water demand.

Prediction of Spatial Distribution of Coal Seam Permeability Based on Key Interpolation Points: A Case Study from the Southern Shizhuang Area of the Qinshui Basin

Accurate prediction of the spatial distribution of permeability of coal reservoirs using scare data from wells for coalbed methane exploration and development can lay a foundation for evaluating its gas production potential. By taking the #3 coal seam in the southern Shizhuang area in Qinshui Basin (Shanxi Province, China) as a research area, 23 key interpolation points that control the permeability of the coal seam were identified using a method that combines staged stripping of the structural stress field and structural curvature superposition. Permeability at the key interpolation points was calculated by combining the geological strength index (GSI) and regression of logging curve. The prediction method for spatial distribution of permeability (i.e., the combination of staged stripping of the structural stress field, determination of key interpolation points, and permeability prediction at key interpolation points) was developed. The differences in the spatial distribution of permeability using a key point and different methods (i.e., kriging interpolation method, intersection method of prospecting network at an equal interval, and random point selection for the same number of wells) were compared with that of 90 wells in the study area. The results indicate that the key control points for permeability of the coal seam can be identified by staged stripping of the structural stress field and structural curvature superposition: The permeability at the key interpolation points can be predicted by GSI. In addition, the key interpolation points can predict the high-value, sub-high-value, sub-low-value, and low-value zones of permeability of the coal seam in the study area using the same data points. The spatial distribution of permeability predicted by the key interpolation points was more accurate than that predicted by the intersection method of the prospecting network at an equal space and random point selection method, and it is closer to the predicted results using four sets of data. This research provides a method and reference for predicting changes in the permeability of a coal seam under limited drilling data.

Permeability's response to dolomitization, clues from Permian–Triassic reservoirs of the central Persian Gulf

Understanding the pattern of spatial permeability distribution in carbonate reservoirs strongly depends on its relationships to geological factors. Despite this importance, the relationship between dolomitization and permeability changes is poorly understood. This study represents the effects of dolomitization on permeability variations in carbonate Permian–Triassic strata of the central Persian Gulf. Porosity and permeability measured on 1389 plug samples using Boyle and Darcy lows, respectively. Petrographical studies under a polarizing microscope showed that various types of facies are recognizable including boundstone, mudstone, wackestone, packstone and grainstone. Dolomitization and dissolution are the main diagenetic processes. Permeability increases along with dolomite content in the samples with higher than 1 mD permeability. Dolomitization of the allochems increased the interparticle spaces and so improved the pore connectivity. High permeability is also due to the intercrystalline pores between dolomite crystals and vuggy porosities which have been created as the result of high degree of dolomitization. Classifying the dolomitic rocks based on dolomite crystal shapes indicates that nonplanar dolomites are more frequent in the samples with less than 0.001 mD permeability while samples with more than 1 mD permeability have more euhedral dolomites. The subhedral dolomites are more frequent in the sample with 0.1–1 mD permeabilities. Nonplanar dolomites are more abundant in K1 and K3 units which are non-reservoir parts. Also, pore spaces in coarse crystal dolomites are connected to each other more effectively, which mainly occurs in K2 and K4 reservoir units. Pore typing in the studied carbonates demonstrates that moderate amounts of dolomites (about 50%) connect the other pore types while they produce a contiguous pore network in higher quantities. In the samples with more than about 60% dolomites, the intercrystalline pores are combined together and touching vugs are created, which strongly increase the permeability of the samples.

Pore pressure pulse migration in microcracked andesite recorded with fibre optic sensors

Pore pressure has a major influence on the effective stress and thus on the mechanical behaviour of rocks. In this study, we focus on the hydro-mechanical behaviour of a low porosity andesitic rock heat-treated to 930 °C to induce thermal cracks and increase the permeability of the samples. First, we show that permeability decreases from 8 × 10−16 m2 to 1.5 × 10−17 m2 with a confining pressure (Pc) increase from 2 MPa to 40 MPa (pore pressure being approximately 0.2 MPa). Then, we used fibre optic pressure sensors to monitor pore pressure diffusion at three points along the sample during the propagation of a pore pressure pulse under hydrostatic (Pc=40 MPa) and triaxial stresses (Pc=40 MPa, differential stress of 356 MPa). When the pore pressure pulse was applied, the fibre optic sensors showed a sudden pore pressure increase one after the other as a function of their location along the sample. Pore pressure increase downstream was very smooth under hydrostatic stress and almost zero after the duration of the experiment (50 min) under triaxial stresses. This lack of downstream pore pressure increase under triaxial stresses is due to the fact that a differential stress of 356 MPa decreased permeability from approximately 10−17m2 to approximately 10−19m2. Finally, the pore pressure diffusion process was modelled considering a uniform spatial distribution of permeability in the andesite sample and the dead volume attached at the downstream side.

Observational and Critical State Physics Descriptions of Long-Range Flow Structures

Using Fracture Seismic methods to map fluid-conducting fracture zones makes it important to understand fracture connectivity over distances greater 10–20 m in the Earth’s upper crust. The principles required for this understanding are developed here from the observations that (1) the spatial variations in crustal porosity are commonly associated with spatial variations in the magnitude of the natural logarithm of crustal permeability, and (2) many parameters, including permeability have a scale-invariant power law distribution in the crust. The first observation means that crustal permeability has a lognormal distribution that can be described as κ ≈ κ 0 exp ( α ( φ − φ 0 ) ) , where α is the ratio of the standard deviation of ln permeability from its mean to the standard deviation of porosity from its mean. The scale invariance of permeability indicates that αϕο = 3 to 4 and that the natural log of permeability has a 1/k pink noise spatial distribution. Combined, these conclusions mean that channelized flow in the upper crust is expected as the distance traversed by flow increases. Locating the most permeable channels using Seismic Fracture methods, while filling in the less permeable parts of the modeled volume with the correct pink noise spatial distribution of permeability, will produce much more realistic models of subsurface flow.

Permeability of coal associated with cleat and bedding structure: measurement and modeling

ABSTRACT The permeability of coal shows anisotropic features due to its cleat and bedding structures. This work measured methane permeability of three cylindrical coal specimens, which represents the three orthogonal axes of the coal seam about bedding plane and cleat (face cleat and butt cleat). Twenty-seven permeability measurement tests were conducted under the different confining pressures and axial compression (4, 6, and 8 MPa) at different gas pressures (0.5, 1, and 1.5 MPa). Results clearly revealed the anisotropy in permeability of the tested coal specimens under test conditions. The specimen parallel to the bedding plane in face cleat direction shows the highest permeability while the specimen perpendicular to the bedding plane shows the lowest permeability. Within gas pressure range from 0.5 to 1.5 MPa, the lower the gas pressure the higher the measured coal permeability. Spatial permeability distribution around coal mine methane drainage borehole is obtained through a three-dimensional permeability model. The spatial permeability around drainage borehole parallel to butt cleat direction is much higher than that parallel to face cleat direction. In-mine methane drainage boreholes parallel to bedding plane in the butt cleat direction are recommended to use in engineering application.

Static and dynamic conceptual model of a complexly fractured crystalline rock aquifer

AbstractA conceptual model of anisotropic and dynamic permeability is developed from hydrogeologic and hydromechanical characterization of a foliated, complexly fractured, crystalline rock aquifer at Gates Pond, Berlin, Massachusetts. Methods of investigation include aquifer‐pumping tests, long‐term hydrologic monitoring, fracture characterization, downhole heat‐pulse flow meter measurements, in situ extensometer testing, and earth tide analysis. A static conceptual model is developed from observations of depth‐dependent and anisotropic permeability that effectively compartmentalizes the aquifer as a function of foliation intensity. Superimposed on the static model is dynamic permeability as a function of hydraulic head in which transient bulk aquifer transmissivity is proportional to changes in hydraulic head due to hydromechanical coupling. The dynamic permeability concept is built on observations that fracture aperture changes as a function of hydraulic head, as measured during in situ extensometer testing of individual fractures, and observed changes in bulk aquifer transmissivity as determined from earth tides during seasonal changes in hydraulic head, with higher transmissivity during periods of high hydraulic head, and lower transmissivity during periods of relatively lower hydraulic head. A final conceptual model is presented that captures both the static and dynamic properties of the aquifer. The workflow presented here demonstrates development of a conceptual framework for building numerical models of complexly fractured, foliated, crystalline rock aquifers that includes both a static model to describe the spatial distribution of permeability as a function of fracture type and foliation intensity and a dynamic model that describes how hydromechanical coupling impacts permeability magnitude as a function of hydraulic head fluctuation. This model captures important geologic controls on permeability magnitude, anisotropy, and transience and therefor offers potentially more reliable history matching and forecasts of different water management strategies, such as resource evaluation, well placement, permeability prediction, and evaluating remediation strategies.

Feasibility study to optimize a near-surface sensor network design for improving detectability of CO2 leakage at a geologic storage site

We explored the feasibility of an improved design of a CO2 leakage monitoring network at a geologic storage site. To effectively represent CO2 pathways, a rule-based percolation model was adopted rather than the rigorous multiphase flow model based on Darcy’s equation. Five different monitoring network designs were compared using a few scenarios and multiple correlated random field realizations. The ensemble results showed that given the detection uncertainty across the entire sensor network, regular spacing deployment of sensors is the most effective method when a sufficient number of sensors is available. The results also showed that an aggressive monitoring design based on information of the spatial permeability distribution near the surface can be a viable method when a limited number of sensors is employed. However, such an aggressive design can lead to elevated uncertainty in leakage detectability.

Coupled thermo-hydro-mechanical modeling on well pairs in heterogeneous porous geothermal reservoirs

Production water reinjection plays an important role in geothermal reservoir management. Heterogeneous porous geothermal reservoir models considering the spatial distributions of permeability and rock heat capacity are generated. In total, 200 realizations with different permeability fields were considered. A fully coupled modeling of reservoir deformation, fluid flow, and heat transport was performed on each realization using the finite element method. The results showed that heterogeneity induced channeling appears in the geothermal reservoirs with increasing heterogeneity of permeability, through which the injected production can quickly reach the production well. This causes the shorter thermal breakthrough time at production wells, and the lower reservoir surface settlement. In geothermal reservoir models considering the correlation between heat capacity and permeability, the thermal breakthrough curves and the reservoir surface settlement were the same as the reservoir models of the constant heat capacity. With increasing correlation length, the possibility of flow channels appearing in well pair system increases, causing a short average thermal breakthrough time and a lower surface settlement around the injection well. The existence of preferential flow channels between injection and production wells indicates that an equivalent flow channel model can be approximately simulate geothermal doublets in heterogeneous reservoirs.

Comparative investigation of the spatial distribution of past weathering impacts on sandstone masonry

Inspection of the deterioration of both natural outcrops and historical built stone facades reveals that patterns of disruption are not uniform, indicating the influence of material and environmental properties. Sandstones have a spatial variability in weathering response. For this reason, geostatistical techniques have been applied to studies of sandstone properties, mineralogical and structural, that influence susceptibility to decay. For this study, a comparative analysis of permeability data acquired from a ‘quarry fresh’ stone and a weathered sample is undertaken.The depositional processes that resulted in the formation of sandstone also create structures of spatial variation such as laminations or larger bedding planes within the material. Using geostatistical techniques, the permeability variance observed within ‘quarry fresh’ blocks of sandstone indicates the subsampling of larger geological structures when cut from the quarry face. Once blocks have been emplaced within a building they will be subjected to the increased stress of the urban environment. These conditions result in exacerbated weathering through processes such as salt and chemical weathering. Weathering can alter material properties such as permeability with the creation of a secondary permeability produced by the opening pores and alteration of pore connectivity. Through the application of geostatistics in the analysis of permeability data observed from the weathered block, variography reveals the presence of smaller scale structures. This suggests that alteration of the sandstone's permeability has led to the creation of new weathering structures within the stone, overwriting the initial sedimentary structures.These weathering-related structures will affect both the magnitude and spatial distribution of permeability within the weathered block. The interconnected pathways of permeability, created by past weathering, facilitate the migration of moisture and salts in solution through the substrate. This work has demonstrated that through a geostatistical approach with the application of co-kriging, these potential moisture pathways can be identified and visualised.

In-plane permeability distribution mapping of isotropic mats using flow front detection

In-plane permeability of textile fabrics is often characterized by one-dimensional rectilinear flow experiments, displaying limitations related to potential race-tracking effects and the need to run experiments at several fiber volume fractions. We propose a practical approach to alleviate these drawbacks. Resin flow front location is detected by image processing of videos and coupled to a Control Volume Finite Element solver with an error minimization routine based on Levenberg-Marquardt method comparing numerical and experimental fill times of all control volumes. Permeability of an isotropic random mat was characterized through reference experiments: cases with intentionally introduced race-tracking and cases with varying permeability along the resin flow direction with three different sections and fiber volume fractions. The method led to an efficient permeability determination and provided valuable insights on the statistics of spatial permeability distribution while highlighting the benefits of a thresholding algorithm for interpretation of permeability experiments in the presence of race-tracking.

Fully coupled inversion on a multi-physical reservoir model – Part II: The Ketzin CO2 storage reservoir

Reliable monitoring of CO2 storage reservoirs requires a combination of different observation methods. However, history matching is typically limited to CO2 pressure data alone. This paper presents a multi-physical inversion of hydraulic pressure, CO2 pressure, CO2 arrival time and geoelectrical crosshole observations of the Ketzin pilot site for CO2 storage, Germany. Multi-physical inversion has rarely been reported for CO2 storage reservoirs. In contrast to previous studies, there is no need for pre-inversion of geophysical datasets as these are now directly included in a fully coupled manner. The deteriorating impact of structural noise is effectively mitigated by preconditioning of the observation data. A double regularisation scheme provides stability for insensitive parameters and reduces the number of required model runs during inversion. The model shows fast and stable convergence and the results provide a good fit to the multi-physical observation dataset. It has certain predictive power as the known migration direction of the CO2 plume is captured. These results clarify two long discussed issues of the Ketzin CO2 storage reservoir: (1) The pre-existing hypothesis of an existing hydraulic barrier became unsubstantial as the data series suggesting weak hydraulic communication are identified as erroneous. (2) Salt precipitation around the injection well doubles the injection overpressure compared to salt free conditions, which is equivalent to a well skin of 10. The presented framework allows to integrate various types of observations into a single multi-physical model leading to an increased confidence in the spatial permeability distribution and, in perspective, to improved predictive assessments of CO2 storage reservoirs.