Thorough comprehension of flow behavior in underground porous media is fundamental for several applications such as oil and gas production, Underground Gas Storage, CO2 storage, and Enhanced ...Geothermal Systems. Macroscale petrophysical parameters, as well as hydraulic parameters, are strongly linked to the microstructure of the rock.
In this paper, we present a methodology for the geometric analysis and characterization of the pore structure of 3D binary images of rocks. The geometric analysis is based on the A∗ pathfinding algorithm extended to 3D domains and on the measurement of the pore radius along the identified paths. The analysis is carried out for the main flow directions to obtain a tensorial representation of tortuosity, effective porosity, and representative pore radius, to provide permeability estimation and effective characterization of anisotropy. Moreover, the approach provides the analysis of pore size distribution and constriction.
The methodology was applied to synthetic but realistic rock samples, generated through the QSGS algorithm. Two case studies, representative of an isotropic and an anisotropic porous media, are presented. Validation was carried out through comparison with FVM hydrodynamic modeling. Analysis of the results shows that the presented geometric approach can provide thorough and reliable characterization of the porous media.
•Interdisciplinary approach for microstructure and transport properties characterization.•Pore structure analysis through path-finding technique derived from graph theory.•Determination of tortuosity, permeability and effective porosity in tensor form.•Anisotropy estimation from geometrical analysis.•Application to 3D realistic rock images generated with QSGS.
Pore-scale analysis and characterization of reservoir rocks provide valuable information for the definition and management of underground hydrogen storage and CO2 storage or sequestration.
This ...article presents an optimized implementation of the A* algorithm, the most popular pathfinding method in the presence of obstacles. In this context, the algorithm is applied to recognize the minimum length connected paths through each flow direction of 3D images of a porous medium representative of a reservoir rock. The identification of the main paths allows the characterization of the pore space and the calculation of fundamental petrophysical properties such as tortuosity and effective porosity, which can be used for permeability estimation. Compared to other algorithms available for pore-scale characterization, such as the pore centroid, A* provides a better approximation of the pore space available for the flow and, therefore, a reliable characterization of the petrophysical properties. On the other hand, path identification is significantly consuming in terms of time and memory. In this paper, an efficient and optimized implementation based on C++/OpenMP programming language is presented.
The proposed implementation aims to the analysis of large-scale models profiting from parallelization, memory optimization, and enhanced managing of dead paths. Three test cases of increasing sizes are presented, to analyze the advantages and the disadvantages of the algorithm as the number of explored points increases. The 3D binary images analyzed are related to a synthetic domain (1 million voxels) and two actual sandstone samples (about 4 and 64 million voxels respectively). The code is validated against a Matlab serial implementation, showing a significant improvement in efficiency. Remarkable test cases of several millions of voxels were afforded, overcoming the memory and execution slowness issues. Moreover, the proposed implementation is suitable for large pore-scale models run in HPC environments.
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•Computer-aided geometric characterization of porous media images.•Pathfinding algorithm implementation applied to Digital Rocks Physics.•Parallel computing optimization for native serial algorithms.•Validation on real sample binary representations.•Geometrical properties computation for underground storage.
AbstractThe goal of this study is the quantitative characterization of the degree of natural alteration of marble samples by using image analysis for the automatic characterization and comparison of ...the pore structure of rock samples before and after weathering. The proposed methodology is based on a pore exploration path-finding algorithm for the identification of paths developing within the porous domain of marble samples in both natural conditions and after weathering. Along each identified path, the pore radius is measured, providing a thorough description of the pore space statistical distribution. The A* path-finding approach was developed and applied to binarized images obtained from two-dimensional (2D) thin sections of marble samples in both natural conditions and after 10 years of natural decay. The results are expressed in terms of 2D porosity and statistical distributions of the pore radius of the samples preweathering and postweathering. A comparison with the information obtained from standardized laboratory tests used for the physical and mechanical characterization of stone material is also provided. From a computational point of view, the presented approach is highly parallelizable. The presented approach works wells in complex porous structures characterized by high path tortuosity, pore-size heterogeneity, and pore surface roughness. Moreover, the methodology is less affected by small-scale pore features and noise produced during image binarization, compared with other algorithms for pore structure morphological analysis such as skeleton-based and maximal ball approaches.
Tortuosity (
τ
) is one of the key parameters controlling flow and transport in porous media. Although the concept of tortuosity is straightforward, its estimation in porous media has yet been ...challenging. Most models proposed in the literature are either empirical or semiempirical including some parameters whose values and their estimations are in prior unknown. In this study, we modified a previously presented geometric tortuosity (
τ
g
) model based on percolation theory and validated it against a methodology based on the pathfinding A* algorithm. For this purpose, we selected 12 different porous materials including four sandstones, three carbonates, one salt, and four synthetic media. For all samples, five sub-volumes at different lengths with fifty iterations were randomly selected except one carbonate sample for which three sub-volumes were extracted. Pore space properties, such as pore radius, throat radius, throat length, and coordination number distributions were determined by extracting the pore network of each sub-volume. The average and maximum coordination numbers and minimum throat length were used to estimate the
τ
g
. Comparison with the A* algorithm results showed that the modified model estimated the
τ
g
accurately with absolute relative errors less than 28%. We also estimated the
τ
g
using two other models presented in the literature as well as the original percolation-based tortuosity model. We found that our proposed model showed a significantly higher accuracy. Results also indicated more precise estimations at the larger length scales demonstrating the effect of uncertainties at the smaller scales.
•Interdisciplinary approach for pore structure characterization.•Pore structure analysis through path-finding technique derived from graph theory.•Fluid dynamics simulation based on the Lattice ...Boltzmann method.•Estimation of effective porosity and tortuosity.•Applications to real rock images.
Characterization of underground porous media parameters at the micro and macro scales is fundamental in geosciences. A thorough comprehension of flow phenomena requires analyses and observations at the micro scale through adoption of micromodels as representative as possible of real geological formations. In this paper we focus on the analysis of 2D binary images of real rock thin sections to characterize pore network geometry and to estimate effective porosity, pore size distribution and tortuosity with the aim of providing suitable information for designing micromodels. To this end, a geometrical analysis of the pore structure, based on the identification and characterization of the set of the shortest geometrical pathways between inlets and outlets pairs, was implemented. The geometrical analysis is based on a path-finding algorithm derived from graph theory. Results provided by geometrical analysis were validated against hydrodynamic numerical simulation via the Lattice Boltzmann Method (LBM). Results show that the path-finding approach provides reasonable and reliable estimates of tortuosity and can be successfully applied for analyzing the distribution of effective pore radius, as well as for estimating the effective porosity.
In reservoir engineering, one of the main sources of information for the characterization of reservoir and well parameters is well testing. An alternative to the standard drawdown/buildup test is ...Harmonic Pulse Testing (HPT) because it can provide well performance and reservoir behavior monitoring without having to interrupt field production, which is appealing from an economic standpoint. Recorded pressure analysis is performed in the frequency domain by adopting a derivative approach similar to conventional well testing. To this end, pressure and rate data must be decomposed into harmonic components. Test interpretability can be significantly improved if pressure data are detrended prior to interpretation, filtering out non periodic events such as discontinuous production from neighboring wells and flow regime variations that did not respect the designed test periodicity. Therefore, detrending offers the possibility of overcoming the limitation of HPT applicability due to the difficulty of imposing a regularly pulsing rate for the whole test duration (typically lasting several days). This makes HPT attractive for well performance monitoring, especially in gas reservoirs converted to underground gas storage. In this paper, different detrending methodologies are discussed and applied to synthetic and real data. Results show that, if a proper detrending strategy is adopted, information provided by HPT interpretation can be maximized and/or improved.
Stratigraphic forward modelling (SFM) provides the means to produce geologically coherent and realistic models. In this paper, we demonstrate the possibility of matching lithological variability ...simulated with a basin-scale advection-diffusion SFM to a data-rich real-world setting, i.e. the Holocene Rhine-Meuse fluvio-deltaic system in the Netherlands. SFM model calibration to real-world data in general has proven non-trivial. This study focuses on a novel inversion process constrained by the top surface and the sand proportion observed at specific pseudo-wells in the study area. Goodness-of-fit expressed by a new fitness function gives the error calculated as the average of two calibration constraints. Computational efficiency was increased significantly by implementing a new optimization process in two hierarchical steps: a) optimization in terms of sediment load and discharge, which are the most influential parameters having the largest uncertainty and b) optimization with respect to the remaining uncertain parameters, these being sediment transport parameters. The calibration process described allows for the most optimal combination of achieving acceptable levels of goodness-of-fit, feasible runtimes and multiple (non-unique) solutions to obtain synthetic stratigraphic output best matching real-world datasets.
By removing model realizations which are geologically unrealistic, calibrated SFM models provide a multiscale stratigraphic framework for reconstructing static models of reservoirs which are consistent with the palaeogeographic layout, basin-fill history and external drivers (e.g. sea level, sediment supply). The static reservoir models that are matched with highest certainty therefore contain the highest geological realism and may be used to improve deep subsurface reservoir or aquifer property prediction.
The new methodology was applied to the well-established Holocene Rhine-Meuse dataset, which allows a rigorous testing of the optimization; the calibrated SFM allows investigation of controls of the Holocene development on the sedimentary system.
•Lithological variability from SFM, is matched to the Holocene Rhine-Meuse dataset.•Efficient model calibration is achieved through a two-stage optimization process.•Calibrated SFM outputs allow both testing and improve deep characterization.
Concerning the emerging power-to-gas technologies, which are considered the most promising technology for seasonal renewable energy storage, Underground Hydrogen Storage (UHS) has gained attention in ...the last few years. For safe and efficient storage, possible hydrogen losses due to dissolution into the aquifer must be estimated accurately. Due to safety concerns, experimental measurements of hydrogen solubility in brine at reservoir conditions are limited. In this study, a PVT cell is used to characterize the solubility of hydrogen and its mixtures with methane in saline water/brine. The experiments were carried out at 45, 50, and 55°C and from 1 bar up to 500 bar, mimicking a significant range of possible reservoir conditions. Two brine samples representative of two different reservoirs were tested. Two mixtures of methane and hydrogen (10 mol% H 2 and 50 mol% H 2 , respectively) were considered, along with pure hydrogen, to account for the presence of methane in the primary phase of hydrogen storage in a depleted gas reservoir. In the current paper, a comparison of the experimental results with literature models is provided. At the experiment conditions, the impact of the differences in the composition of the two analyzed brines as well as the impact of the analyzed range of temperatures was not significant. Conversely, a non-negligible variation in terms of the slope of the solubility curve was observed as a function of the gas mixture composition: the curve increased more steeply as the percentage of hydrogen reduced.
•Advanced methodology for thermal front monitoring in ATES•Interpreting harmonic pulse testing in frequency domain in radial composite scenario•Diagnostic loglog plot analogous to conventional ...Pressure Transient Analysis•Methodology does not require production/injection interruption
Seasonal storage of heat in shallow aquifers for increasing the efficiency of geothermal energy systems requires a proper monitoring strategy. We expanded our earlier work on harmonic pulse testing (HPT) to incorporate the effect of a temperature front moving into the reservoir due to injection of hot (or cold) water. Our analytical solutions were applied to monitor the thermal front evolution in a doublet system. Thermal front position and average temperature around the injector could indeed be characterized through the application of the proposed HPT interpretation. Additional analyses were carried out adding noise to evaluate the robustness of the interpretation methodology.
Current static reservoir models are created by quantitative integration of interpreted well and seismic data through geostatistical tools. In these models, equiprobable realizations of structural ...settings and property distributions can be generated by stochastic simulation techniques. The integration of regional (or basin) scale knowledge in reservoir models is typically performed qualitatively or semi-quantitatively (for example, through the definition of regional property trends or main channel-belt orientations). This limited use of regional information does not allow an assessment of the impact of the uncertainties associated with the regional knowledge on the overall uncertainty of the reservoir model.
A novel approach is proposed in this study, which allows us to consistently integrate basin-scale information into reservoir models. A new type of data, related to the distribution of the potential hydrocarbon-bearing volumes at basin scale, was obtained from a 2-DH process-based stratigraphic forward model (SFM) and integrated as a soft constraint in the geostatistical reservoir modeling. As a consequence, reservoir models are quantitatively consistent with the large-scale geological setting defined by the SFM output. Furthermore, the uncertainty associated with each SFM parameter can be propagated to reserve estimation. Thus the partitioning of the overall uncertainty affecting a reservoir model into the contributions of the uncertainties at the basin and reservoir scales can be quantitatively assessed.
Several synthetic case studies were carried out with and without conditioning to SFM output, which verified the effectiveness of the method. A logical next step is to apply the proposed methodology to a real-world case.
•Stratigraphic Forward Model (SFM) provides channel body volumetrics at basin scale.•Basin-scale constraints from the SFM were integrated into reservoir models.•Uncertainty of basin-fill parameters was propagated to reserve estimation.•Inference of basin-fill parameters from reservoir data reduced their uncertainty.
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