Computational Geosciences最新文献

{"title":"A recipe to generate sustainably maintainable and extensible hydrogeological datasets to prepare large-scale groundwater models for multiple aquifer systems","authors":"Christian Siebert, Tino Rödiger, Timo Houben, Mariaines diDato, Thomas Fischer, Sabine Attinger, Thomas Kalbacher","doi":"10.1007/s10596-024-10315-9","DOIUrl":"https://doi.org/10.1007/s10596-024-10315-9","url":null,"abstract":"<p>Regional groundwater modelling can provide decision-makers and scientists with valuable information required for the sustainable use and protection of groundwater resources in the future. In order to assess and manage the impact of climate change on regional aquifer systems, numerical groundwater models are required which represent the subsurface structures of aquifers and aquitards in 3D at the regional scale and beyond in the most efficient way. A workflow to clearly generate these structural subsurface representations from a variety of data sources is introduced, applying open-source Geographical Information Systems. The resulting structural models can be used with finite element method-based simulation tools, such as the open-source environment OpenGeoSys. The preparation workflow of the structure model is presented for a large river basin in Germany, indicating the applicability of the method even in a challenging hydrogeological region with several stockworks of dipped and fractured sedimentary aquifers, partially showing significantly changing hydraulic conditions due to natural lateral facies changes.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"4 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stealth Metasomatism in Granulites from Ivrea (NW Italy): Hydration of the (Variscan) Lower Crust by Melt Flow","authors":"Stylianos Karastergios, Simona Ferrando, Barbara E. Kunz, Maria Luce Frezzotti","doi":"10.3390/geosciences14080218","DOIUrl":"https://doi.org/10.3390/geosciences14080218","url":null,"abstract":"Granulites and associated dykes from the less well-studied southern Ivrea–Verbano Zone (around Ivrea town) are characterized by combining field, macro, micro and chemical (major and trace-element mineral composition) data to identify chemical and rheological variations in the lower crust that could be relevant for geodynamic implications. The Ivrea granulites are similar to those in the Lower Mafic Complex of the central Ivrea–Verbano Zone. The mafic lithologies experienced stealth metasomatism (pargasitic amphibole and An-rich plagioclase) that occurred, at suprasolidus conditions, by a pervasive reactive porous flow of mantle-derived orogenic (hydrous) basaltic melts infiltrated along, relatively few, deformation-assisted channels. The chemical composition of the metasomatic melts is similar to that of melts infiltrating the central and northern Ivrea–Verbano Zone. This widespread metasomatism, inducing a massive regional hydration of the lowermost Southalpine mafic crust, promoted a plastic behavior in the lowermost part of the crust during the Early Mesozoic and, ultimately, the Triassic extension of the Variscan crust and the beginning of the Alpine cycle.","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"14 8","pages":"218-218"},"PeriodicalIF":0.0,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147892564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Auto-weighted Bayesian Physics-Informed Neural Networks and robust estimations for multitask inverse problems in pore-scale imaging of dissolution","authors":"Sarah Perez, Philippe Poncet","doi":"10.1007/s10596-024-10313-x","DOIUrl":"https://doi.org/10.1007/s10596-024-10313-x","url":null,"abstract":"<p>In this article, we present a novel data assimilation strategy in pore-scale imaging and demonstrate that this makes it possible to robustly address reactive inverse problems incorporating Uncertainty Quantification (UQ). Pore-scale modeling of reactive flow offers a valuable opportunity to investigate the evolution of macro-scale properties subject to dynamic processes in the context of Carbon Capture and Storage (CCS). Yet, they suffer from imaging limitations arising from the associated X-ray microtomography (X-ray <span>(mu )</span>CT) process, which induces discrepancies in the properties estimates. Assessment of the kinetic parameters also raises challenges, as reactive coefficients are critical parameters that can cover a wide range of values. We account for these two issues and ensure reliable calibration of pore-scale modeling, based on dynamical <span>(mu )</span>CT images, by integrating uncertainty quantification in the workflow. The present method is based on a multitasking formulation of reactive inverse problems combining data-driven and physics-informed techniques in calcite dissolution. This allows quantifying morphological uncertainties on the porosity field and estimating reactive parameter ranges through prescribed PDE models, with a latent concentration field, and dynamical <span>(mu )</span>CT observations. The data assimilation strategy relies on sequential reinforcement incorporating successively additional PDE constraints and suitable formulation of the heterogeneous diffusion differential operator leading to enhanced computational efficiency. We provide a robust and unbiased uncertainty quantification by straightforward adaptive weighting of Bayesian Physics-Informed Neural Networks (BPINNs), ensuring reliable micro-porosity changes during geochemical transformations. We demonstrate successful Bayesian Inference in 1D+Time calcite dissolution based on synthetic <span>(mu )</span>CT images with meaningful posterior distribution on the reactive parameters and dimensionless numbers. We eventually apply this framework to a more realistic 2D+Time data assimilation problem involving heterogeneous porosity levels and synthetic <span>(mu )</span>CT dynamical observations.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"32 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A modified Flux Corrected Transport method coupled with the MPFA-H formulation for the numerical simulation of two-phase flows in petroleum reservoirs using 2D unstructured meshes","authors":"Phillipe C. G. da Silva, Gustavo L. S. S. Pacheco, Pedro V. P. Albuquerque, Márcio R. A. Souza, Fernando R. L. Contreras, Paulo R. M. Lyra, Darlan K. E. Carvalho","doi":"10.1007/s10596-024-10306-w","DOIUrl":"https://doi.org/10.1007/s10596-024-10306-w","url":null,"abstract":"<p>The numerical simulation of multiphase and multicomponent flows in oil reservoirs is a significant challenge, demanding robust and computationally efficient numerical formulations. Particularly, scenarios with high mobility ratios between injected and resident fluids can lead to Grid Orientation Effects (GOE), where numerical solutions strongly depend on the alignment between flow and computational grid and mobility ratio. This phenomenon relates to an anisotropic distribution in truncation error tied to the numerical approximation of the transport term. Although the oil industry commonly uses linear Two Point Flux Approximation (TPFA) for diffusive fluxes and the First Order Upwind (FOU) method for advective fluxes, both lack rotational invariance and TPFA struggles with non-k-orthogonal grids. This paper proposes a comprehensive cell-centered finite-volume formulation to simulate reservoir oil-water displacements, integrating the classical IMPES (Implicit Pressure Explicit Saturation) segregate approach with unstructured, non-k-orthogonal meshes. Diffusive flux discretization employs a Multipoint Flux Approximation with Harmonic Points (MPFA-H), capable of handling heterogeneous and strongly anisotropic media. A modified second-order Flux Corrected Transport (FCT) approach curbs artificial numerical diffusion for transport term discretization. Additionally, we incorporate a Flow-Oriented Scheme (FOS) for computing low-order and high-order approximations of the numerical fluxes to enhance multidimensional approximation and reduce GOE. The proposed strategy is validated through benchmark problems, yielding precise outcomes with reduced numerical diffusion and GOE effects, underscoring its efficiency for complex reservoir flow simulations.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"77 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141934950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel hierarchical model calibration method for deep water reservoirs under depletion and aquifer influence","authors":"Ao Li, Faruk Omer Alpak, Eduardo Jimenez, Tzu-hao Yeh, Andrew Ritts, Vivek Jain, Hongquan Chen, Akhil Datta-Gupta","doi":"10.1007/s10596-024-10314-w","DOIUrl":"https://doi.org/10.1007/s10596-024-10314-w","url":null,"abstract":"<p>An ensemble of rigorously history matched reservoir models can help better understand the interactions between heterogeneity and fluid flows, improve forecasting reliability, and locate infill-drilling opportunities to support field development plans. However, developing efficient calibration methods for complex, multi-million cell deep-water models remains a challenge. This paper presents a hierarchical global-local assisted-history matching (AHM) approach with new elements, applied to a complex deep-water reservoir. The method consists of two stages: global and local. In the global stage, the reservoir energy is matched using an evolutionary approach to calibrate the model parameters with build-up and average reservoir pressures. In the local stage, the permeability field is calibrated to production data using a novel streamline-based sensitivity-driven AHM method to ascertain the spatial variability and geologic continuity of local updates. The sensitivity for each streamline is weighted by the water fraction and constrained by a time-of-flight cutoff to focus on water intrusion regions within the near wellbore region. The proposed method is field-tested in a complex deep-water reservoir. The evolutionary approach generates an ensemble of models with well-matched oil production rates and build-up/reservoir pressure using global model parameters. Local updates using streamline-based gradients are then conducted to match the water cut for each ensemble member while maintaining overall pressure match quality. Results show that the hierarchical AHM method significantly reduces the data misfit and is well-suited to primary recovery in a deep-water setting with few producers and under the influence of mild/weak aquifers.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"14 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141968998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medial Access Path Search (MAPS) for pore-network extraction","authors":"Yuze Zhang, Jie Liu, Tao Zhang, Shuyu Sun","doi":"10.1007/s10596-024-10307-9","DOIUrl":"https://doi.org/10.1007/s10596-024-10307-9","url":null,"abstract":"<p>Over the past few decades, pore-network models (PNMs) have emerged as a pivotal tool in the investigation of fluid flow within porous media. The crux of PNM lies in the extraction of the topological structure of porous media, as abstracted from geological scans, commonly referred to as the pore network. Conventional methods for pore-network extraction rely on pixel-based techniques and necessitate high-quality images to accurately capture pore information. In recent times, the flashlight search medial axis (FSMA) algorithm has been introduced, offering a novel approach to extract pore networks within continuous spatial domains. This innovation enables the algorithm to operate independently of specific pixels, thereby significantly reducing computational complexity. Building upon the foundational principles of the FSMA algorithm, this paper presents an efficient search algorithm in conjunction with string methods. This algorithm facilitates the precise determination of pore and throat center locations within porous media using a minimal number of computational points and can accurately compute the positions of pore medians. Furthermore, this algorithm can effectively circumvent the issue of dead-end pores encountered in the FSMA algorithm, a feature of paramount importance in the study of multiphase flow within porous media.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"20 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pore-scale study on the permeability characteristics of fractured rock under hydraulic-chemical coupling","authors":"Zheng Chen, Chuan-Yong Zhu, Bo Yu, Liang Gong","doi":"10.1007/s10596-024-10308-8","DOIUrl":"https://doi.org/10.1007/s10596-024-10308-8","url":null,"abstract":"<p>The permeability characteristics of fractured rock significantly influence the efficient development of subsurface energy resources. Under subsurface environmental conditions, the evolution of fractured rock permeability is affected by both fluid flow and chemical reactions. Traditional models like the Kozeny-Carman model are no longer suitable for accurately predicting the permeability under hydraulic-chemical coupling. In this study, a two-dimensional fractured rock model is constructed and combined with the lattice Boltzmann method, a pore-scale hydraulic-chemical coupling model is developed to explore the evolution characteristics of the pore structure and permeability of fractured rocks under different conditions. The results show that due to the comprehensive influence of seepage flow and chemical reactions, the distribution characteristics of pore structure in fractured rocks are different during the evolution process, including diffusion-controlled, convection-controlled, and reaction-controlled. Additionally, pore structure variations result in permeability differences among fractured rock with identical porosity. Finally, an efficient model is proposed to predict the porosity–permeability relationships of fractured rocks under hydraulic-chemical coupling. The relative error between the predicted value and the value calculated using the formula falls within the range of ± 15%.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"78 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141872604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling alterations in relative permeability curves due to salinity using artificial neural networks","authors":"Vinicius Czarnobay, Luis Fernando Lamas, Damianni Sebrão, Luiz Adolfo Hegele","doi":"10.1007/s10596-024-10312-y","DOIUrl":"https://doi.org/10.1007/s10596-024-10312-y","url":null,"abstract":"<p>We propose data-driven models based on artificial neural networks (ANN) to predict changes in water-oil relative permeability curves given a salinity reduction in the injection water. The ANN consisted of a multilayer feedforward structure with backpropagation. For validation, a database from a semi-empirical correlation was created, and models with added noise were used to analyze the influence of the data dispersion. Then, a survey of experimental relative permeability curves was performed to produce a real database for sandstone and carbonate rocks, utilized in the training of the final models, with hyperparameter optimization and cross-validation. The initial model was able to consistently reproduce the original correlation, with a mean squared error (MSE) on the order of <span>(10^{-6})</span>. In the noise-trained model, the error measured was lower than the analytical error expected from random dispersion. In models trained with real data, the adopted strategy led to a final training MSE on the order of <span>(10^{-3})</span>, with better performance in networks with two hidden layers. The obtained models are useful in modeling relative permeabilities for low-salinity and engineered water injection projects. Training can be continuously updated with new data, and the methodology can be applied to other properties or even other multivariate regression problems.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"38 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Consistent prediction of well paths and geological surfaces","authors":"Ariel Almendral Vázquez, Pål Dahle, Petter Abrahamsen, Audun Sektnan","doi":"10.1007/s10596-024-10310-0","DOIUrl":"https://doi.org/10.1007/s10596-024-10310-0","url":null,"abstract":"<p>We propose a smooth stochastic process for modeling the vertical well path uncertainty. This process describes the accumulation of measurement errors along the well path. We combine the stochastic process with a stochastic model for surfaces into a consistent framework for simultaneous prediction of well paths and surfaces. We show properties of the proposed stochastic process and provide examples of interaction between wells and surfaces.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"13 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141772074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A numerical model for offshore Geological Carbon Storage (GCS) undergoing hydrate formation","authors":"Yufei Wang, Eric Flauraud, Anthony Michel, Véronique Lachet, Clémentine Meiller","doi":"10.1007/s10596-024-10311-z","DOIUrl":"https://doi.org/10.1007/s10596-024-10311-z","url":null,"abstract":"<p>We propose a nonisothermal reactive multicomponent multiphase flow model for simulating offshore geological carbon dioxide (CO<span>(_2)</span>) storage. The model considers CO<span>(_2)</span> hydration as well as CO<span>(_2)</span> dissolution in water in the low-temperature high-pressure deep-ocean environment. This model comprises a chemistry module responsible for all chemical reactions among different phases and a flow module responsible for mass and energy transfer. The chemistry module is based on the mass action law that considers the inhibition effect of salt on CO<span>(_2)</span> hydration and dissolution. We implement this model in an open-source Matlab-based code <span>MRST-HYD</span> using a sequential iteration approach. The code has been validated through tests against one theoretical solution and one numerical code, <span>Geoxim</span>, developed at IFP Energies nouvelles. Finally, we apply this code to simulate CO<span>(_2)</span> injection into one-dimensional and two-dimensional deep-ocean sediments.</p>","PeriodicalId":10662,"journal":{"name":"Computational Geosciences","volume":"22 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141772076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}