Applied science of creating computerized representations of portions of the Earth's crust
Geological mapping software displaying a screenshot of a structure map generated for an 8500ft deep gas &Oil reservoir in the Earth field,Vermilion Parish,Erath, Louisiana. The left-to-right gap, near the top of thecontour map indicates aFault line. This fault line is between the blue/green contour lines and the purple/red/yellow contour lines. The thin red circular contour line in the middle of the map indicates the top of the oil reservoir. Because gas floats above oil, the thin red contour line marks the gas/oil contact zone.
Geological modelling,geologic modelling orgeomodelling is theapplied science of creatingcomputerized representations of portions of the Earth'scrust based ongeophysical andgeological observations made on and below the Earth surface. A geomodel is the numerical equivalent of a three-dimensionalgeological map complemented by a description ofphysical quantities in the domain of interest.[1]Geomodelling is related to the concept of Shared Earth Model;[2] which is a multidisciplinary, interoperable and updatable knowledge base about the subsurface.
Geomodelling is commonly used for managingnatural resources, identifyingnatural hazards, and quantifyinggeological processes, with main applications tooil and gas fields, groundwateraquifers andore deposits. For example, in theoil and gas industry, realistic geological models are required as input toreservoir simulator programs, which predict the behavior of the rocks under varioushydrocarbon recovery scenarios. A reservoir can only be developed and produced once; therefore, making a mistake by selecting a site with poor conditions for development is tragic and wasteful. Using geological models andreservoir simulation allowsreservoir engineers to identify which recovery options offer the safest and most economic, efficient, and effective development plan for a particular reservoir.
In 2-dimensions (2D), ageologic formation or unit is represented by a polygon, which can be bounded by faults, unconformities or by its lateral extent, or crop. In geological models a geological unit is bounded by 3-dimensional (3D) triangulated or gridded surfaces. The equivalent to the mapped polygon is the fully enclosed geological unit, using a triangulated mesh. For the purpose of property or fluid modelling these volumes can be separated further into an array of cells, often referred to asvoxels (volumetric elements). These 3D grids are the equivalent to 2D grids used to express properties of single surfaces.
Geomodelling generally involves the following steps:[3]
Preliminary analysis of geological context of the domain of study.
Interpretation of available data and observations as point sets or polygonal lines (e.g. "fault sticks" corresponding to faults on a vertical seismic section).
Construction of a structural model describing the main rock boundaries (horizons, unconformities, intrusions, faults)[4]
Definition of a three-dimensional mesh honoring the structural model to support volumetric representation of heterogeneity (seeGeostatistics) and solving thePartial Differential Equations which govern physical processes in the subsurface (e.g.seismic wave propagation, fluid transport in porous media).
Incorporating the spatial positions of the major formation boundaries, including the effects offaulting,folding, anderosion (unconformities). The major stratigraphic divisions are further subdivided into layers of cells with differing geometries with relation to the bounding surfaces (parallel to top, parallel to base, proportional). Maximum cell dimensions are dictated by the minimum sizes of the features to be resolved (everyday example: On a digital map of a city, the location of a city park might be adequately resolved by one big green pixel, but to define the locations of the basketball court, the baseball field, and the pool, much smaller pixels – higher resolution – need to be used).
Each cell in the model is assigned a rock type. In a coastalclastic environment, these might be beach sand, high water energy marineupper shoreface sand, intermediate water energy marinelower shoreface sand, and deeper low energy marinesilt andshale. The distribution of these rock types within the model is controlled by several methods, including map boundary polygons, rock type probability maps, or statistically emplaced based on sufficiently closely spaced well data.
Reservoir quality parameters almost always includeporosity andpermeability, but may include measures of clay content, cementation factors, and other factors that affect the storage and deliverability of fluids contained in the pores of those rocks.Geostatistical techniques are most often used to populate the cells with porosity and permeability values that are appropriate for the rock type of each cell.
Most rock is completelysaturated withgroundwater. Sometimes, under the right conditions, some of the pore space in the rock is occupied by other liquids or gases. In the energy industry,oil andnatural gas are the fluids most commonly being modelled. The preferred methods for calculating hydrocarbon saturations in a geological model incorporate an estimate of pore throat size, thedensities of the fluids, and the height of the cell above thewater contact, since these factors exert the strongest influence oncapillary action, which ultimately controls fluid saturations.
An important part of geological modelling is related togeostatistics. In order to represent the observed data, oftennot on regular grids, we have to use certain interpolation techniques. The most widely used technique iskrigingwhich uses the spatial correlation among data and intends to construct the interpolation via semi-variograms. To reproduce more realistic spatial variability and help assess spatial uncertainty between data, geostatistical simulation based on variograms, training images, or parametric geological objects is often used, e.g.[5]
Geologists involved inmining andmineral exploration use geological modelling to determine the geometry and placement ofmineral deposits in the subsurface of the earth. Geological models help define the volume and concentration of minerals, to whicheconomic constraints are applied to determine the economic value of themineralization. Mineral deposits that are deemed to be economic may be developed into amine.
Geomodelling andCAD share a lot of common technologies. Software is usually implemented using object-oriented programming technologies inC++,Java orC# on one or multiple computer platforms. The graphical user interface generally consists of one or several 3D and 2D graphics windows to visualize spatial data, interpretations and modelling output. Such visualization is generally achieved by exploitinggraphics hardware. User interaction is mostly performed through mouse and keyboard, although 3D pointing devices andimmersive environments may be used in some specific cases. GIS (Geographic Information System) is also a widely used tool to manipulate geological data.
Geometric objects are represented with parametric curves and surfaces or discrete models such aspolygonal meshes.[4][6]
Defining an appropriateOntology to describe geological objects at various scales of interest,
Integrating diverse types of observations into 3D geomodels: geological mapping data, borehole data and interpretations, seismic images and interpretations, potential field data, well test data, etc.,
Better accounting for geological processes during model building,
Characterizing uncertainty about the geomodels to help assess risk. Therefore, Geomodelling has a close connection toGeostatistics andInverse problem theory,
Applying of the recent developed Multiple Point Geostatistical Simulations (MPS) for integrating different data sources,[9]
Automated geometry optimization and topology conservation[10]
In the 70's, geomodelling mainly consisted of automatic 2D cartographic techniques such as contouring, implemented asFORTRAN routines communicating directly withplotting hardware. The advent of workstations with3D graphics capabilities during the 80's gave birth to a new generation of geomodelling software with graphical user interface which became mature during the 90's.[11][12][13]
Since its inception, geomodelling has been mainly motivated and supported by oil and gas industry.
Software developers have built several packages for geological modelling purposes. Such software can display, edit, digitise and automatically calculate the parameters required by engineers, geologists and surveyors. Current software is mainly developed and commercialized by oil and gas or mining industry software vendors:
Mira Geoscience provides GOCAD Mining Suite, a 3D geological modelling software that compiles, models, and analyzes for valid interpretation that honours all data.
Seequent provides Leapfrog 3D geological modeling &Geosoft GM-SYS and VOXI 3D modelling software.
Maptek provides Vulcan, 3D modular software visualisation for geological modelling and mine planning
Micromine is a comprehensive and easy to use exploration and mine design solution, which offers integrated tools for modelling, estimation, design, optimisation and scheduling.
GEOREKA Software is affordable 3D geological modelling aimed at mining, aggregates and mineral exploration. It provides a free geology viewer, or a full version combining traditional modelling methods with modern implicit modelling techniques such as RBFs and machine learning.
Moreover, industry Consortia or companies are specifically working at improving standardization and interoperability of earth science databases and geomodelling software:
Standardization:GeoSciML by the Commission for the Management and Application of Geoscience Information, of the International Union of Geological Sciences.
Faure, Stéphane, Godey, Stéphanie, Fallara, Francine and Trépanier, Sylvain. (2011). Seismic Architecture of the Archean North American Mantle and Its Relationship to Diamondiferous Kimberlite Fields. Economic Geology, March–April 2011, v. 106, p. 223–240.http://econgeol.geoscienceworld.org/content/106/2/223.abstract
Fallara, Francine, Legault, Marc and Rabeau, Olivier (2006). 3-D Integrated Geological Modeling in the Abitibi Subprovince (Québec, Canada): Techniques and Applications. Exploration and Mining Geology, Vol. 15, Nos. 1–2, pp. 27–41.[1]
de Kemp, E.A. (2007). 3-D geological modelling supporting mineral exploration. In: Goodfellow, W.D., ed., Mineral Deposits of Canada: A Synthesis of Major Deposit Types, District Metallogeny, the Evolution of Geological Provinces, and Exploration Methods: Geological Association of Canada, Mineral Deposits Division, Special Publication 5, p. 1051–1061.https://web.archive.org/web/20081217170553/http://gsc.nrcan.gc.ca/mindep/method/3d/pdf/dekemp_3dgis.pdf
^abCaumon, G., Collon-Drouaillet, P., Le Carlier de Veslud, C., Sausse, J. and Viseur, S. (2009), Surface-based 3D modeling of geological structures,Mathematical Geosciences, 41(9):927–945
^Mallet, J.-L., Geomodeling, Applied Geostatistics Series. Oxford University Press.ISBN978-0-19-514460-4
^Caumon, G., Towards stochastic time-varying geological modeling (2010),Mathematical Geosciences, 42(5):(555-569)
^Perrin, M., Zhu, B., Rainaud, J.F. and Schneider, S. (2005), Knowledge-driven applications for geological modeling, "Journal of Petroleum Science and Engineering", 47(1–2):89–104
^M.R. Alvers, H.J. Götze, B. Lahmeyer, C. Plonka and S. Schmidt, 2013,Advances in 3D Potential Field Modeling EarthDoc, 75th EAGE Conference & Exhibition incorporating SPE EUROPEC 2013
^J. L. Mallet, P. Jacquemin, and N. Cheimanoff (1989). GOCAD project: Geometric modeling of complex geological surfaces, SEG Expanded Abstracts 8, 126,doi:10.1190/1.1889515
