1,724 research outputs found

    Structure Segmentation and Transfer Faults in the Marcellus Shale, Clearfield County, Pennsylvania: Implications for Gas Recovery Efficiency and Risk Assessment Using 3D Seismic Attribute Analysis

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    The Marcellus Shale has become an important unconventional gas reservoir in the oil and gas industry. Fractures within this organic-rich black shale serve as an important component of porosity and permeability useful in enhancing production. Horizontal drilling is the primary approach for extracting hydrocarbons in the Marcellus Shale. Typically, wells are drilled perpendicular to natural fractures in an attempt to intersect fractures for effective hydraulic stimulation. If the fractures are contained within the shale, then hydraulic fracturing can enhance permeability by further breaking the already weakened rock. However, natural fractures can affect hydraulic stimulations by absorbing and/or redirecting the energy away from the wellbore, causing a decreased efficiency in gas recovery, as has been the case for the Clearfield County, Pennsylvania study area. Estimating appropriate distances away from faults and fractures, which may limit hydrocarbon recovery, is essential to reducing the risk of injection fluid migration along these faults. In an attempt to mitigate the negative influences of natural fractures on hydrocarbon extraction within the Marcellus Shale, fractures were analyzed through the aid of both traditional and advanced seismic attributes including variance, curvature, ant tracking, and waveform model regression. Through the integration of well log interpretations and seismic data, a detailed assessment of structural discontinuities that may decrease the recovery efficiency of hydrocarbons was conducted. High-quality 3D seismic data in Central Pennsylvania show regional folds and thrusts above the major detachment interval of the Salina Salt. In addition to the regional detachment folds and thrusts, cross-regional, northwest-trending lineaments were mapped. These lineaments may pose a threat to hydrocarbon productivity and recovery efficiency due to faults and fractures acting as paths of least resistance for induced hydraulic stimulation fluids. These lineaments may represent major transfer faults that serve as pathways for hydraulic fluid migration. Detection and evaluation of fracture orientation and intensity and emphasis on the relationship between fracture intensity and production potential is of high interest in the study area as it entails significant time and cost implications for both conventional and unconventional hydrocarbon exploration and production

    Automatic Segmentation of Sinkholes Using a Convolutional Neural Network

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    Sinkholes are the most abundant surface features in karst areas worldwide. Understanding sinkhole occurrences and characteristics is critical for studying karst aquifers and mitigating sinkhole-related hazards. Most sinkholes appear on the land surface as depressions or cover collapses and are commonly mapped from elevation data, such as digital elevation models (DEMs). Existing methods for identifying sinkholes from DEMs often require two steps: locating surface depressions and separating sinkholes from non-sinkhole depressions. In this study, we explored deep learning to directly identify sinkholes from DEM data and aerial imagery. A key contribution of our study is an evaluation of various ways of integrating these two types of raster data. We used an image segmentation model, U-Net, to locate sinkholes. We trained separate U-Net models based on four input images of elevation data: a DEM image, a slope image, a DEM gradient image, and a DEM-shaded relief image. Three normalization techniques (Global, Gaussian, and Instance) were applied to improve the model performance. Model results suggest that deep learning is a viable method to identify sinkholes directly from the images of elevation data. In particular, DEM gradient data provided the best input for U-net image segmentation models to locate sinkholes. The model using the DEM gradient image with Gaussian normalization achieved the best performance with a sinkhole intersection-over-union (IoU) of 45.38% on the unseen test set. Aerial images, however, were not useful in training deep learning models for sinkholes as the models using an aerial image as input achieved sinkhole IoUs below 3%

    Visual Ensemble Analysis of Fluid Flow in Porous Media across Simulation Codes and Experiment

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    We study the question of how visual analysis can support the comparison of spatio-temporal ensemble data of liquid and gas flow in porous media. To this end, we focus on a case study, in which nine different research groups concurrently simulated the process of injecting CO2 into the subsurface. We explore different data aggregation and interactive visualization approaches to compare and analyze these nine simulations. In terms of data aggregation, one key component is the choice of similarity metrics that define the relation between the different simulations. We test different metrics and find that a fine-tuned machine-learning based metric provides the best visualization results. Based on that, we propose different visualization methods. For overviewing the data, we use dimensionality reduction methods that allow us to plot and compare the different simulations in a scatterplot. To show details about the spatio-temporal data of each individual simulation, we employ a space-time cube volume rendering. We use the resulting interactive, multi-view visual analysis tool to explore the nine simulations and also to compare them to data from experimental setups. Our main findings include new insights into ranking of simulation results with respect to experimental data, and the development of gravity fingers in simulations.Comment: arXiv preprin

    Métodos de representação virtual e visualização para informação arquitetónica e contextual em sítios arqueológicos

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    This work seeks to outline some guidelines in order to improve the use of 3D visualization applied to archaeological data of diverse nature and at different scales. One difficulty found in this process is related to the still frequent two-dimensional representation of the three-dimensional archaeological reality. Aware that the existence of data of two-dimensional nature is fundamental in the archaeological process and that they result, on the one hand, from the manual archaeological recording processes and, on the other hand, from the intense analysis and interpretation activity of the archaeological investigation team, we seek to ensure an adequate 3D representation based on 3D acquisition methods mostly available to the archaeology teams. Archaeological visualization in three-dimensional support is an increasingly frequent and necessary practice, but it continues to show some difficulties. These are substantiated in the reduced number of visualization techniques used, the use of visualization tools that are not very customized for the archaeological needs and the privileged use of visual features of the models during the archaeological process phases. Thus, the main objective of this work is to design and evaluate appropriate methods for visualizing archaeological data. To determine which visualization methods are most used during the phases of the archaeological process, an online user-survey was carried out, which allowed consolidating the 3D representation methodologies used, as well as to propose a visualization model that also categorizes the appropriate visualization techniques which increase the visual perception and understanding of the archaeological elements. Three prototypes are defined according to the different 3D data acquisition methodologies presented and visualization methodologies are designed in order to, on the one hand, take into account the scale and diversity of the archaeological elements and, on the other hand, to account for the need to ensure visualization methods which are easily assimilated by archaeologists. Each prototype was evaluated by two archaeologists with different professional background. They were proposed, through a set of previously determined tasks, to assess the interaction with 3D models and with the visualization methods and the satisfaction of the visualization results regarding the archaeological needs. The evaluation of the prototypes allowed to conclude that the presented visualization methods increase the perception of 3D models which represent archaeological elements. In addition, it was also possible to produce new objects that reveal elements of archaeological interest. It is suggested to make these methodologies available on a web-based application and on mobile platforms.Este trabalho procura esboçar algumas diretrizes no sentido de melhorar a utilização da visualização 3D aplicada aos dados arqueológicos de natureza diversa e a escalas distintas. Uma dificuldade encontrada neste processo prende-se com a, ainda frequente, representação bidimensional da realidade arqueológica tridimensional. Ciente de que a existência de dados de natureza bidimensional são fundamentais no processo arqueológico e que resultam, por um lado, dos processos manuais de registo arqueológicos e, por outro, da intensa atividade de análise e interpretação da equipa de investigação arqueológica, procuramos assegurar uma representação 3D adequada, com base em metodologias de aquisição de dados 3D geralmente disponíveis às equipas de arqueologia. A visualização arqueológica em suporte tridimensional é uma prática cada vez mais frequente e necessária, mas que continua a evidenciar algumas dificuldades. Estas substanciam-se no reduzido número de técnicas de visualização usadas, na utilização de ferramentas de visualização pouco adaptadas às necessidades arqueológicas e na utilização preferencial de características visuais dos modelos durante as fases do processo arqueológico. Assim, o objetivo primordial deste trabalho é desenhar e avaliar métodos adequados à visualização de dados arqueológicos. Para determinar que métodos de visualização são mais utilizados durante as fases do processo arqueológico realizou-se um questionário online que permitiu consolidar as metodologias de representação 3D usadas, bem como propor um modelo de visualização que também categoriza as técnicas de visualização adequadas para aumentar a perceção e a compreensão visual dos elementos arqueológicos. Definem-se três protótipos de acordo com as distintas metodologias de aquisição de dados 3D apresentados e são desenhadas metodologias de visualização que, por um lado, têm em conta a escala e a diversidade dos elementos arqueológicos e, por outro, a necessidade de assegurar métodos de visualização facilmente assimilados pelos arqueólogos. Cada protótipo foi avaliado por dois arqueólogos com experiências profissionais distintas. O que lhes foi proposto, através de um conjunto de tarefas previamente estabelecidas, foi aferir da facilidade de interação com os modelos 3D e com os métodos de visualização e adequação dos resultados de visualização às necessidades dos arqueólogos. A avaliação dos protótipos permitiu concluir que os métodos de visualização apresentados aumentam a perceção dos modelos 3D que representam elementos arqueológicos. Para além disso foi possível produzir também novos objetos que revelam elementos com interesse arqueológico. É sugerida a disponibilização destas metodologias em ambiente web e plataformas móveis.Programa Doutoral em Informátic

    Model Calibration, Drainage Volume Calculation and Optimization in Heterogeneous Fractured Reservoirs

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    We propose a rigorous approach for well drainage volume calculations in gas reservoirs based on the flux field derived from dual porosity finite-difference simulation and demonstrate its application to optimize well placement. Our approach relies on a high frequency asymptotic solution of the diffusivity equation and emulates the propagation of a 'pressure front' in the reservoir along gas streamlines. The proposed approach is a generalization of the radius of drainage concept in well test analysis (Lee 1982), which allows us not only to compute rigorously the well drainage volumes as a function of time but also to examine the potential impact of infill wells on the drainage volumes of existing producers. Using these results, we present a systematic approach to optimize well placement to maximize the Estimated Ultimate Recovery. A history matching algorithm is proposed that sequentially calibrates reservoir parameters from the global-to-local scale considering parameter uncertainty and the resolution of the data. Parameter updates are constrained to the prior geologic heterogeneity and performed parsimoniously to the smallest spatial scales at which they can be resolved by the available data. In the first step of the workflow, Genetic Algorithm is used to assess the uncertainty in global parameters that influence field-scale flow behavior, specifically reservoir energy. To identify the reservoir volume over which each regional multiplier is applied, we have developed a novel approach to heterogeneity segmentation from spectral clustering theory. The proposed clustering can capture main feature of prior model by using second eigenvector of graph affinity matrix. In the second stage of the workflow, we parameterize the high-resolution heterogeneity in the spectral domain using the Grid Connectivity based Transform to severely compress the dimension of the calibration parameter set. The GCT implicitly imposes geological continuity and promotes minimal changes to each prior model in the ensemble during the calibration process. The field scale utility of the workflow is then demonstrated with the calibration of a model characterizing a structurally complex and highly fractured reservoir

    3D Seismic, Attribute-Assisted, Structural Interpretation for Hydrocarbon Exploration and Production: Southwest Pennsylvania, Central Appalachian Basin

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    High quality 3D seismic data provides critical information vital to the delineation of structural fabrics and depositional facies, and it is therefore important to the development of ideas associated with structural and facies architecture and growth history of the Appalachian foreland basin. Traditional wiggle trace imagery is limited by its dominant frequency and low signal-to-noise ratio; while conventional seismic attributes, such as instantaneous amplitude, RMS and frequency methods are not effective at defining fracture intensity and orientation and spatial and temporal relations between faults and folds which are crucial in achieving the hydrocarbon exploration objective in the basin. To overcome these limitations advanced seismic attributes such as volumetric curvature, ant tracking and waveform model regression were applied in a multi-attribute analysis to increase the resolution of stratigraphic and structural features including geometries, orientations, boundaries and intensities of faulting, folding and fracturing. Saw-tooth forethrust to backthrust patterns and small-scale, intra-interval, shear zones or detachment faults were observed within the Devonian intervals. From these discontinuities, the primary stress orientation during the Devonian was defined at approximately 105° to 120° azimuth which may affect drilling orientations in the hydraulic fracturing process. This effort may be used as an analog for other shale plays as it demonstrates the importance of 3D seismic analysis to understanding the relationship between subsurface structural features and hydrocarbon systems, which are fundamental to the success of future exploration for and production of oil and gas, both conventional and unconventional, in the Appalachian Basin
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