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Florian Wellmann - One of the best experts on this subject based on the ideXlab platform.

  • GemPy 1.0: open-source stochastic Geological Modeling and inversion
    Geoscientific Model Development, 2019
    Co-Authors: Miguel De La Varga, Alexander Schaaf, Florian Wellmann
    Abstract:

    Abstract. The representation of subsurface structures is an essential aspect of a wide variety of geoscientific investigations and applications, ranging from geofluid reservoir studies, over raw material investigations, to geosequestration, as well as many branches of geoscientific research and applications in Geological surveys. A wide range of methods exist to generate Geological models. However, the powerful methods are behind a paywall in expensive commercial packages. We present here a full open-source geoModeling method, based on an implicit potential-field interpolation approach. The interpolation algorithm is comparable to implementations in commercial packages and capable of constructing complex full 3-D Geological models, including fault networks, fault–surface interactions, unconformities and dome structures. This algorithm is implemented in the programming language Python, making use of a highly efficient underlying library for efficient code generation (Theano) that enables a direct execution on GPUs. The functionality can be separated into the core aspects required to generate 3-D Geological models and additional assets for advanced scientific investigations. These assets provide the full power behind our approach, as they enable the link to machine-learning and Bayesian inference frameworks and thus a path to stochastic Geological Modeling and inversions. In addition, we provide methods to analyze model topology and to compute gravity fields on the basis of the Geological models and assigned density values. In summary, we provide a basis for open scientific research using Geological models, with the aim to foster reproducible research in the field of geoModeling.

  • GemPy 1.0: open-source stochastic Geological Modeling and inversion
    2018
    Co-Authors: Miguel De La Varga, Alexander Schaaf, Florian Wellmann
    Abstract:

    Abstract. The representation of subsurface structures is an essential aspect of a wide variety of geoscientific investigations and applications: ranging from geofluid reservoir studies, over raw material investigations, to geosequestration, as well as many branches of geoscientific research studies and applications in Geological surveys. A wide range of methods exists to generate Geological models. However, especially the powerful methods are behind a paywall in expensive commercial packages. We present here a full open-source geoModeling method, based on an implicit potential-field interpolation approach. The interpolation algorithm is comparable to implementations in commercial packages and capable of constructing complex full 3-D Geological models, including fault networks, fault-surface interactions, unconformities, and dome structures. This algorithm is implemented in the programming language Python, making use of a highly efficient underlying library for efficient code generation (theano) that enables a direct execution on GPU's. The functionality can be separated into the core aspects required to generate 3-D Geological models and additional assets for advanced scientific investigations. These assets provide the full power behind our approach, as they enable the link to Machine Learning and Bayesian inference frameworks and thus a path to stochastic Geological Modeling and inversions. In addition, we provide methods to analyse model topology and to compute gravity fields on the basis of the Geological models and assigned density values. In summary, we provide a basis for open scientific research using Geological models, with the aim to foster reproducible research in the field of geoModeling.

  • 3-D Structural Geological models: Concepts, methods, and uncertainties
    Advances in Geophysics, 2018
    Co-Authors: Florian Wellmann, Guillaume Caumon
    Abstract:

    Abstract The Earth below ground is the subject of interest for many geophysical as well as Geological investigations. Even though most practitioners would agree that all available information should be used in such an investigation, it is common practice that only a part of Geological and geophysical information is actually integrated in structural Geological models. We believe that some reasons for this omission are (a) an incomplete picture of available Geological Modeling methods, and (b) the problem of the perceived static picture of an inflexible Geological representation in an image or Geological model. With this work, we aim to contribute to the problem of subsurface interface detection through (a) the review of state-of-the-art Geological Modeling methods that allow the consideration of multiple aspects of Geological realism in the form of observations, information, and knowledge, cast in geometric representations of subsurface structures, and (b) concepts and methods to analyze, quantify, and communicate related uncertainties in these models. We introduce a formulation for Geological model representation and interpolation and uncertainty analysis methods with the aim to clarify similarities and differences in the diverse set of approaches that developed in recent years. We hope that this chapter provides an entry point to recent developments in Geological Modeling methods, helps researchers in the field to better consider uncertainties, and supports the integration of Geological observations and knowledge in geophysical interpretation, Modeling and inverse approaches.

Miguel De La Varga - One of the best experts on this subject based on the ideXlab platform.

  • GemPy 1.0: open-source stochastic Geological Modeling and inversion
    Geoscientific Model Development, 2019
    Co-Authors: Miguel De La Varga, Alexander Schaaf, Florian Wellmann
    Abstract:

    Abstract. The representation of subsurface structures is an essential aspect of a wide variety of geoscientific investigations and applications, ranging from geofluid reservoir studies, over raw material investigations, to geosequestration, as well as many branches of geoscientific research and applications in Geological surveys. A wide range of methods exist to generate Geological models. However, the powerful methods are behind a paywall in expensive commercial packages. We present here a full open-source geoModeling method, based on an implicit potential-field interpolation approach. The interpolation algorithm is comparable to implementations in commercial packages and capable of constructing complex full 3-D Geological models, including fault networks, fault–surface interactions, unconformities and dome structures. This algorithm is implemented in the programming language Python, making use of a highly efficient underlying library for efficient code generation (Theano) that enables a direct execution on GPUs. The functionality can be separated into the core aspects required to generate 3-D Geological models and additional assets for advanced scientific investigations. These assets provide the full power behind our approach, as they enable the link to machine-learning and Bayesian inference frameworks and thus a path to stochastic Geological Modeling and inversions. In addition, we provide methods to analyze model topology and to compute gravity fields on the basis of the Geological models and assigned density values. In summary, we provide a basis for open scientific research using Geological models, with the aim to foster reproducible research in the field of geoModeling.

  • GemPy 1.0: open-source stochastic Geological Modeling and inversion
    2018
    Co-Authors: Miguel De La Varga, Alexander Schaaf, Florian Wellmann
    Abstract:

    Abstract. The representation of subsurface structures is an essential aspect of a wide variety of geoscientific investigations and applications: ranging from geofluid reservoir studies, over raw material investigations, to geosequestration, as well as many branches of geoscientific research studies and applications in Geological surveys. A wide range of methods exists to generate Geological models. However, especially the powerful methods are behind a paywall in expensive commercial packages. We present here a full open-source geoModeling method, based on an implicit potential-field interpolation approach. The interpolation algorithm is comparable to implementations in commercial packages and capable of constructing complex full 3-D Geological models, including fault networks, fault-surface interactions, unconformities, and dome structures. This algorithm is implemented in the programming language Python, making use of a highly efficient underlying library for efficient code generation (theano) that enables a direct execution on GPU's. The functionality can be separated into the core aspects required to generate 3-D Geological models and additional assets for advanced scientific investigations. These assets provide the full power behind our approach, as they enable the link to Machine Learning and Bayesian inference frameworks and thus a path to stochastic Geological Modeling and inversions. In addition, we provide methods to analyse model topology and to compute gravity fields on the basis of the Geological models and assigned density values. In summary, we provide a basis for open scientific research using Geological models, with the aim to foster reproducible research in the field of geoModeling.

Jeanfrancois Rainaud - One of the best experts on this subject based on the ideXlab platform.

  • Earth models for underground resource exploration and estimation
    2013
    Co-Authors: Michel Perrin, Jeanfrancois Rainaud, Sandrine Grataloup
    Abstract:

    This chapter introduces a certain number of Geological concepts that are reused in the rest of the book. It depicts the Geological objects classically explored for underground resources exploitation (hydrocarbon, water, storage of energy or wastes) such as sedimentary basins, aquifers or reservoirs. Aim and use of Geological Modeling are presented. Some of the input data and some characteristics of Geological models such as components and versioning are described.

  • a semantic repository for Geological Modeling workflows
    International Conference on Web Services, 2009
    Co-Authors: Nabil Belaid, Yamine Aitameur, Jeanfrancois Rainaud
    Abstract:

    Nowadays, many engineering studies are conducted to securely exploit depleted Oil Fields for CO2 Storage.These studies follow complex workflows of data processing services described by geologists. If no explicit semantics is applied to describe these workflows, it is not possible to share them between geologists by reusing existing ones or for composing new ones. The focus of our work is to make the semantics explicit in order to facilitate the geologists daily work. In this article, we first explain how geologists operate today. Then, we enrich such workflows with semantic indexes through ontology based characterizations.

  • ICWS - A Semantic Repository for Geological Modeling Workflows
    2009 IEEE International Conference on Web Services, 2009
    Co-Authors: Nabil Belaid, Yamine Ait-ameur, Jeanfrancois Rainaud
    Abstract:

    Nowadays, many engineering studies are conducted to securely exploit depleted Oil Fields for CO2 Storage.These studies follow complex workflows of data processing services described by geologists. If no explicit semantics is applied to describe these workflows, it is not possible to share them between geologists by reusing existing ones or for composing new ones. The focus of our work is to make the semantics explicit in order to facilitate the geologists daily work. In this article, we first explain how geologists operate today. Then, we enrich such workflows with semantic indexes through ontology based characterizations.

  • knowledge driven applications for Geological Modeling
    Journal of Petroleum Science and Engineering, 2005
    Co-Authors: Michel Perrin, Jeanfrancois Rainaud, Beiting Zhu, Sebastien Schneider
    Abstract:

    Abstract Oil and gas exploration relies for a good part on 3D earth Modeling operated from raw seismic data and from information issued from drillings. At present, the resulting models have to be shared by various potential users, who must be able to possibly extend, update, revise or rebuild them in view of additional Geological data or according to new Geological interpretations. The present paper proposes an knowledge-driven approach for “Shared Earth Models” [SEM, 1998, Shared Earth Model project web site http://www.posc.org/workprgm/sem.shtml.] building which ambitions to share throughout the workflow not only raw data and the various representations of the geometrical objects included in a definite model but also the Geological interpretation related to this model. This approach rests on a Geo-Ontology that identifies and formalises the structural geologists' expert knowledge and on a derived abstract descriptor (Geological Evolution Scheme), which enables full sharing of the user's Geological interpretation between the various applications. Geological assemblages result from a definite history made of various successive events, which create Geological objects. For this reason, the arrangements of these objects and, in consequence, the arrangements of the various Geological surfaces present in 3D models verify specific rules, which define a “Geological syntax” [Perrin, M.,1998. Geological consistency: an opportunity for safe surface assembly and quick model exploration. 3D Modeling of Natural Objects, A Challenge for the 2000's, 3 (4–5) 1998 June.] . The proposed Geo-Ontology takes into account this particular chrono-spatial structure of Geological models. The paper describes the main concepts that are used and defines the syntactic rules to which they must obey. Moreover, it is possible to deduce from the Geo-Ontology that we have defined, a standard Geological descriptor (Geological Evolution Scheme=GES), which records the geologist's interpretation of any given Geological assemblage and which can be used for automatically building the related 3D model. The resulting methodology (“Geological pilot”) is exposed and illustrated through an example, showing how a GES can be used all along the workflow that goes from raw data to shared structural and stratigraphical models fully exportable for reuse by other geologists. The knowledge-driven approach presented and the resulting “Geological pilot” methodology appear very promising for producing a new generation of earth models, able to be fully shared by multiple, possibly distant users. 3D-model updating or revision will be much easier and the proposed methodology is also promising for kinematics (4D) Modeling.

Alexander Schaaf - One of the best experts on this subject based on the ideXlab platform.

  • GemPy 1.0: open-source stochastic Geological Modeling and inversion
    Geoscientific Model Development, 2019
    Co-Authors: Miguel De La Varga, Alexander Schaaf, Florian Wellmann
    Abstract:

    Abstract. The representation of subsurface structures is an essential aspect of a wide variety of geoscientific investigations and applications, ranging from geofluid reservoir studies, over raw material investigations, to geosequestration, as well as many branches of geoscientific research and applications in Geological surveys. A wide range of methods exist to generate Geological models. However, the powerful methods are behind a paywall in expensive commercial packages. We present here a full open-source geoModeling method, based on an implicit potential-field interpolation approach. The interpolation algorithm is comparable to implementations in commercial packages and capable of constructing complex full 3-D Geological models, including fault networks, fault–surface interactions, unconformities and dome structures. This algorithm is implemented in the programming language Python, making use of a highly efficient underlying library for efficient code generation (Theano) that enables a direct execution on GPUs. The functionality can be separated into the core aspects required to generate 3-D Geological models and additional assets for advanced scientific investigations. These assets provide the full power behind our approach, as they enable the link to machine-learning and Bayesian inference frameworks and thus a path to stochastic Geological Modeling and inversions. In addition, we provide methods to analyze model topology and to compute gravity fields on the basis of the Geological models and assigned density values. In summary, we provide a basis for open scientific research using Geological models, with the aim to foster reproducible research in the field of geoModeling.

  • GemPy 1.0: open-source stochastic Geological Modeling and inversion
    2018
    Co-Authors: Miguel De La Varga, Alexander Schaaf, Florian Wellmann
    Abstract:

    Abstract. The representation of subsurface structures is an essential aspect of a wide variety of geoscientific investigations and applications: ranging from geofluid reservoir studies, over raw material investigations, to geosequestration, as well as many branches of geoscientific research studies and applications in Geological surveys. A wide range of methods exists to generate Geological models. However, especially the powerful methods are behind a paywall in expensive commercial packages. We present here a full open-source geoModeling method, based on an implicit potential-field interpolation approach. The interpolation algorithm is comparable to implementations in commercial packages and capable of constructing complex full 3-D Geological models, including fault networks, fault-surface interactions, unconformities, and dome structures. This algorithm is implemented in the programming language Python, making use of a highly efficient underlying library for efficient code generation (theano) that enables a direct execution on GPU's. The functionality can be separated into the core aspects required to generate 3-D Geological models and additional assets for advanced scientific investigations. These assets provide the full power behind our approach, as they enable the link to Machine Learning and Bayesian inference frameworks and thus a path to stochastic Geological Modeling and inversions. In addition, we provide methods to analyse model topology and to compute gravity fields on the basis of the Geological models and assigned density values. In summary, we provide a basis for open scientific research using Geological models, with the aim to foster reproducible research in the field of geoModeling.

Guillaume Caumon - One of the best experts on this subject based on the ideXlab platform.

  • 3-D Structural Geological models: Concepts, methods, and uncertainties
    Advances in Geophysics, 2018
    Co-Authors: Florian Wellmann, Guillaume Caumon
    Abstract:

    Abstract The Earth below ground is the subject of interest for many geophysical as well as Geological investigations. Even though most practitioners would agree that all available information should be used in such an investigation, it is common practice that only a part of Geological and geophysical information is actually integrated in structural Geological models. We believe that some reasons for this omission are (a) an incomplete picture of available Geological Modeling methods, and (b) the problem of the perceived static picture of an inflexible Geological representation in an image or Geological model. With this work, we aim to contribute to the problem of subsurface interface detection through (a) the review of state-of-the-art Geological Modeling methods that allow the consideration of multiple aspects of Geological realism in the form of observations, information, and knowledge, cast in geometric representations of subsurface structures, and (b) concepts and methods to analyze, quantify, and communicate related uncertainties in these models. We introduce a formulation for Geological model representation and interpolation and uncertainty analysis methods with the aim to clarify similarities and differences in the diverse set of approaches that developed in recent years. We hope that this chapter provides an entry point to recent developments in Geological Modeling methods, helps researchers in the field to better consider uncertainties, and supports the integration of Geological observations and knowledge in geophysical interpretation, Modeling and inverse approaches.

  • towards stochastic time varying Geological Modeling
    Mathematical Geosciences, 2010
    Co-Authors: Guillaume Caumon
    Abstract:

    The Modeling of subsurface geometry and properties is a key element to understand Earth processes and manage natural hazards and resources. In this paper, we suggest this field should evolve beyond pure data fitting approaches by integrating Geological concepts to constrain interpretations or test their consistency. This process necessarily calls for adding the time dimension to 3D Modeling, both at the Geological and human time scales. Also, instead of striving for one single best model, it is appropriate to generate several possible subsurface models in order to convey a quantitative sense of uncertainty. Depending on the Modeling objective (e.g., quantification of natural resources, production forecast), this population of models can be ranked. Inverse theory then provides a framework to validate (or rather invalidate) models which are not compatible with certain types of observations. We review recent methods to better achieve both stochastic and time-varying geoModeling and advocate that the application of inversion should rely not only on random field models, but also on Geological concepts and parameters.