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72nd EAGE Conference and Exhibition - Workshops and Fieldtrips
- Conference date: 14 Jun 2010 - 17 Jun 2010
- Location: Barcelona, Spain
- ISBN: 978-90-73781-87-0
- Published: 13 June 2010
61 - 80 of 105 results
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Virtual Outcrop Models: Case Study from the Paleozoic Sandstone Reservoir and Aquifer Analogs, Saudi Arabia
Authors O. Abdullatif and M. MakkawiExcellently exposed Paleozoic Sandstone outcropping strata in central and southern Saudi Arabia provide good outcrop analog to many subsurface formations and hydrocarbon reservoirs and groundwater aquifers. The study of these outcropping rocks provides invaluable opportunity to examine different scale of sedimentary heterogeneity and to understand their impacts on reservoir and aquifer quality and their behavior in the subsurface. This might help to refine and better characterize reservoir and aquifer geological models based on subsurface information.
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The Ainsa quarry outcrop revisited via orientation models built from LIDAR data
Authors P. Arbués, D. García-Sellés, O. Falivene, Ò. Gratacós and J. A. MuñozThe Ainsa quarry outcrop is located 1.5 km south of Ainsa town, in southern Pyrenees, Spain. The strata in the exposure are Eocene, and deposited in a submarine slope setting undergoing synchronous thrusting and related folding. They have tectonic dips of about 22º to the WSW. The succession comprises a 20 m thick turbidite sandstone body (Figure 1) sandwiched between mudstone-dominated mass-transport deposits, together representing the Ainsa-1 turbidite channel-complex. The outcrop has been the subject of numerous studies that have contributed to the global understanding of turbidite systems (Mutti and Normark, 1987; Schuppers, 1995; Clark and Pickering 1996). This succession is also important in that it has been regarded as an analogue for reservoirs in the offshore West Africa. The outcrop section is about 400 m long, and its map view shows as a very open angle, limiting the validity of 3-D reconstructions away from the outcrop face to mere extrusion. However, the quarry face is clean and allows for the observation of multiple bedding surfaces, specially the sharp soles of turbidite sandstones on top of mudstone beds (Figure 1). These surfaces were studied from their LIDAR point cloud expression. The results, a local 3-D reconstruction, will be used to revisit an existing depositional and architectural interpretation of the outcrop (Arbués et al. 2008) that had been built on the basis of conventional outcrop characterization techniques.
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LIDAR-based 3D reconstruction and modelling of a flat-topped non-rimmed carbonate platform: Aptian, Maestrat Basin, Spain
Authors T. Bover-Arnal, O. Gratacós, D. García-Sellés, O. Falivene, R. Salas and J. A. MuñozOutcrop-scale reconstruction of depositional geometries and facies distribution of carbonate systems improves our knowledge on their heterogeneity distribution, stacking patterns and stratal architecture. The collected data and derived models can be used as analogues for characterizing and modelling potential subsurface reservoirs. Traditional sedimentological analyses in cropping out carbonate systems have limited accuracy depending on exposure conditions, accessibility or past erosive processes. On the other hand, there is a need to complement classical sedimentological approaches with quantitative characterizations and models of sedimentary bodies. In this respect, processing of three-dimensional (3D) point clouds captured by terrestrial LIght Detection And Ranging (LIDAR) technology combined with real-time kinematic global positioning system offers to field geologists the possibility to construct virtual 3D digital outcrop models (DOMs), which allow for more accurate analyses, reconstructions and quantification of the outcropping facies distribution than conventional digital terrain models. We present a LIDAR 3D DOM of an Aptian flat-topped non-rimmed carbonate platform margin from the western Maestrat Basin (Spain). The DOM served as a departing point to perform a 3D reconstruction that shows the relationship between depositional architecture and facies distribution of the carbonate system. The reconstruction not only highlights the value of digital outcrop models to characterize virtual attributes not observable in the outcrops due to the limitations of the 2D views of the exposures, but also allows to refine outcrop-scale sequence stratigraphic analyses. In addition, the 3D sequence stratigraphic approach obtained together with the 3D facies distribution model generated can be used as an analogue for the characterization of subsurface carbonate reservoirs with similar depositional profiles. The workflow of this study followed these steps: 1) Acquisition of the outcrop 3D point data set using a ground-based terrestrial LIDAR equipped with a differential GPS; 44 overlapping scans were needed to cover the entire outcrops of the flat-topped non-rimmed carbonate system characterized, each scan has associated a high-resolution photograph. 2) Mapping stratigraphic surfaces and pseudowells describing 5 lithofacies onto each individual photograph using a CAD-based tool, the mapping is carried directly onto the photographs because manipulating the images and interpreting the details is easier than directly digitizing onto the point-cloud. 3) The features mapped onto the photographs are projected into the corresponding point-cloud in order to georeference them. 4) Locally georeferenced individual point-clouds and attached interpretations were globally georeferenced by means of the UTM coordinates of each scan. 5) The stratigraphic boundaries mapped are used reconstruct the surfaces bounding stratigraphic units. 6) Population of the internal facies distribution conditioned to the pseudowells. This methodology allows to efficiently extracting information from point clouds, and resulted in the construction of a high-resolution 3D geological model displaying the stratal architecture and facies heterogeneity of sedimentary bodies, confined within a 3D sequence stratigraphical framework.
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Application of ground-based LIDAR for the study of the Huesca Fluvial Fan (Northern Ebro Basin, Spain): modelling the Montearagón outcrop
Authors R. Calvo, P. Arbués, D. García, P. Cabello and E. RamosThe emergence of new techniques usually awakes a strong interest within the scientific community for testing its potential applications in different fields. Thus, any new tool or methodology should be validated previously to its systematic application. Validation process must be carried out in places sufficiently known in order to verify if the results are consistent with those expected. This work aims to incorporate the Light Detection And Ranging technique (LIDAR) to study sedimentary outcrops (Bellian, J. et al.; 2005). The used methodology includes both classical field study and geometric information extracted from the analysis of LIDAR-based Virtual Outcrop (VO). In this case, the chosen study area is the Montearagón outcrop. As illustrated in Fig. 1, Montearagón is located in the Northern margin of the Ebro Foreland Basin (Arenas, C. et al., 2001; Luzón, A., 2005), 11 km Northeast of Huesca (Aragón). The outcropping materials correspond to the Oligo-Miocene Huesca Fluvial Fan (Hirst, J., 1991; Nichols, G., 2004; Donselaar, M. et al., 2008), and are mainly composed by different typologies of sandstone bodies included in a matrix of flood plain shale and silt (Fig. 2). The main objective of this work is creating a 3D model of the Huesca Fluvial Fan. This model will be built using the proposed methodology and by integrating several outcrops that represent various sectors of the fan. Studying outcropping ancient fluvial systems, like the Huesca Fluvial Fan, is of big interest to the oil industry. It gives an approach to the behaviour of similar buried fluvial reservoirs that are hard to image and to model accurately.
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Characterization of an analogue of fractured reservoir using LIDAR, GPR and conventional data
Authors M. Coll, D. García-Sellés, M. Grasmueck, G. P. Eberli, J. Lamarche and K. PomarThe Solvay quarry displays karstified and heavily fractured strata of peritidal platform carbonates of late Barremian age, that can serve as an analog to subsurface fractured reservoirs. In addition of being a potential analog, this study also aims to improve the methodology used in building of DOM (Digital Outcrop Model). The originality of the applied methodology is the integration of conventional outcrop analysis, LIDAR (Light Detection and Ranging) and GPR (Ground Penetrating Radar) data. The goal is to produce an accurate and efficient DOM that resolves the three-dimensional sub-seismic heterogeneity of the fracture distribution in the strata. Stratigraphic and fracture analysis with conventional methods was performed on about 2 km of exposed cliff faces that were subsequently scanned with the LIDAR equipment. Transversal and longitudinal 2D GPR lines and 6 GPR cubes were acquired on the quarry floor to correlate the quarry walls. The 2D GPR data were statically corrected using the GPS horizontal coordinates of the transects, high-resolution topography provided from LIDAR data, and a replacement velocity of 0.098m/ns. GPR and LIDAR data were loaded into 3D CAD software to interpret each horizon and to reconstruct the structural framework. To characterize the fracture distribution; scanline measures were performed along the quarry walls, 3D migrated GPR data was interpreted by delineating high amplitude zones originating from focused diffractions that define fracture surfaces (Grasmueck et al. 2005) and LIDAR point clouds were processed to reveal the main planes families that form the rough wall surface. Two of GPR cubes show the coexistence of four sub-vertical fracture families trending N-S, E-W, NW-SE and NE-SW. The NE-SW fracture family is not detected in the outcrop using the scanline method because the fracture is parallel to the direction of the quarry wall, however the LIDAR algorithm found two families planes oriented near this fracture family. This planes are related to the morphological features of NE-SW joints like twist hackles. The 3D fractures constructed with GPR data allow to filter and understand the planes computed with LIDAR data and to determine the sampling bias due to scanline orientation. Subsequently, the LIDAR data and the scanline measures allow to obtain a continuous distribution of the families fractures along the quarry allowing to characterize dip and azimuth variations.
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A workflow for the automatic characterization of geological surfaces from terrestrial LIDAR data
Authors O. Falivene, D. García-Sellés, P. Arbués, O. Gratacós, J. A. Muñoz and S. TavaniPoint clouds acquired with terrestrial LIDAR are used as a digital support to accurately and precisely georeference outcrop characterizations; as well as to resolve accessibility problems, and improve outcrop characterizations. The LIDAR data allows for an efficient visualization and analysis of the outcrop in the computer, and is also useful for revisiting field data in the office or for teaching purposes. The common practice for virtual outcrop interpretation is visual identification and manual digitalization of pointsets or polylines by using 3-D CAD-like modules. Other, less generic, approaches are oriented towards the automated or semi-automated extraction of geological features, either based on the processing of intensity or other attributes of the virtual outcrop (RGB, hyperspectral) or on geometric parameters calculated from positions. In this presentation, we propose a workflow for the automatic characterization of planar surfaces (typically stratigraphic bedding or fractures) from LIDAR data. The workflow directly uses the point cloud; therefore no decimation, smoothing, intermediate triangulated or gridded surface are required; and is designed aiming to minimize user interaction to allow for a simple, fast, objective and semi-automated use. The result of the workflow is the reconstruction of planar surfaces identified in the point cloud by means of TIN surfaces, organized into families according to their orientations. These surfaces can be used as seeds for building surface-based models of the outcrop, or can be further analysed to investigate their characteristics (geometry, morphology, spacing, dimensions, intersections, etc.). The workflow is based on planar regressions carried out for each point in the point cloud. Which allow the subsequent filtering of points based on normal vector orientation, planar regression quality, relative locations of points or their relative normal vectors differences. This is aimed at individualizing planar patches with geological signification. A coarse grid search strategy is implemented to speed up neighbouring points searches and allow handling multimillion point clouds. The workflow is illustrated using synthetic and natural examples.
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Collection, processing, interpretation and modelling of digital outcrop data using VRGS: An integrated approach to outcrop modelling
By D. HodgettsMuch focus has been given to the hardware and data collection techniques for digital outcrop analogue work. The software development has, however, been left behind, with many geoscientists relying on applications designed for civil engineering or surveying purposes. Though these approaches have yielded interesting and often impressive results, without dedicated software applications the true power of digital outcrop data will never be realised. For the past 7 years software has been under development at Manchester University dedicated to 3D digital outcrop work, with a focus of being able to use very large data sets (collected from LiDAR or other digital sources) effectively and efficiently, but importantly to integrate these approaches with more traditional data collection approaches such as sedimentary logging and field mapping. The software developed facilitates processing of point cloud data from LiDAR and satellite sources (such as Digital Elevation Models), the triangulation of that data into meshes, and interpretation on both point clouds and meshes where appropriate. Interpretation tools include typical polyline mapping tools, structural measurement tools, sedimentary logging tools as well as more automated interpretation and mesh/point cloud classification approaches. Due to the nature of the rapid and large scale data collection possible using modern surveying systems and abundance of publically available satellite imagery and DEM data, digital outcrop datasets can be very large in size. This presents problems in the time taken to interpret and extract surfaces, structures and geostatistics from these data. One solution to reduce the time needed for interpretation and classification is the application of artificial intelligence to the problem. Artificial Neural networks try and replicate the same learning process used by humans and other animals. These Artificial Neural Networks (ANN) potentially provide very powerful ways of classifying data. Examples will be given showing the application of these ANN approaches to the classification of point cloud and mesh data, in particular addressing the problems of extracting structural data on plane orientations such as fracture and bedding planes. The applications of other soft computing and artificial intelligence approaches will also be presented. Integration of multiple data sources into one environment facilitates the development of new modelling approaches. A predictive approach to surface modelling will be presented relying on the use of structural data from dip-azimuth measurements from bedding planes, and polyline interpretations from key stratal surfaces. This modelling approach relies on converging a triangulated mesh, based on the control data, onto a solution matching that input data, rather than using traditional interpolation/extrapolation approaches. With the rapid evolution of computer hardware, particularly the development of high power graphics-card based computing, the application of modern graphics-card features to the processing visualisation and rendering of large digital outcrop datasets will be demonstrated. These hardware advancements will prove of significant benefit to the geosciences, but only if software applications are written to take advantage of them.
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Advances in Virtual Outcrop Geology
Authors J. A. Howell, S. Buckley, T. Kurz, A. Rittersbacher and A. SimaVirtual Outcrops, in which geological exposures are digital captured in a workstation, provide a new and rapidly emerging tool for the collection and analysis of field data. The advantages of virtual outcrop are primarily twofold; the rapid collection of accurate, spatially constrained measurements of geological features and, the improved visualization of outcrops which allows better correlation and mapping coupled with an ability to illustrate and communicate field observations to a wider audience. Virtual Outcrop geology is a rapidly expanding field of study which has grown over the last 10 years from photogrammetrry and basic digital mapping to the advanced data collection and visualization methods utilized today. This presentation addresses two recent developments: the collection and utilization of very large datasets and the integration of hyperspectral imagery to allow the remote mapping of lithology and mineralogy. To date the majority of photo-realistic virtual outcrops are generated from ground based lidar systems. While producing excellent results, these systems are limited by mobility and range, especially when studying very large outcrops. A solution to this problem is to mount the lidar system in a helicopter and scan the outcrop obliquely. This allows the rapid collection of very large volumes of data and has the added advantage of optimizing the angle at which both the scan and associated photos are taken, reducing the occurrence of scan-shadows. Very large virtual outcrops that cover 10s of km can be collected in hours. Despite the speed of acquisition, heli-based data presents a new set of challenges, not least the creation of very large datasets which cannot be visualized using conventional software. The acquisition, processing and utilization of these data will be illustrated with examples from fluvial and shallow marine systems from Utah. Airborne hyper-spectral imagery is an established method for remote sensing which utilizes the absorption characteristics of light outside the visible range (near infer-red) to identify mineralogy and other surface features (vegetation, land use etc). Mounting a similar camera on a tripod and obliquely scanning geological outcrops allows the remote mapping of lithology and mineralogy. The acquisition of oblique data from surfaces with significant topography has presented challenges for the processing of such data. Integration with the detailed terrain mapping provided by the lidar has allowed the spectral absorption response to be modelled and meaningful virtual outcrops, textured with quantitative mineralogical information to be produced. The results is a virtual outcrop which is textured with false coloured images that record mineralogy and can be accurately and rapidly investigated for quantitative information.
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3D Digital Outcrop Modeling and aquifer/reservoir characterization of a slope system tufa complex. La Peña del Manto, Soria (Spain)
Field surveys had been performed on an excellent outcrop of a Quaternary perched springline (slope system) tufa complex (La Peña del Manto, Soria, Spain) integrating LIDAR (Laser Imaging Detection and Ranking), DGPS (differential global position system), GPR (Ground penetrating Radar), ERT (Electrical resistivity tomography) technologies and conventional field studies. The later include: 1) detailed GIS-based geological and geomorphological mapping; 2) description and characterization of sedimentary facies; 3) logging of stratigraphic sections; 4) palaeocurrent measurement; 5) sampling for petrographic, microtextural, geochemical and geochronological analysis; together with 5) sampling for petrophysical characterization (porosity and hydraulic conductivity analysis) of the different lithofacies that will be carried out in a following step of research project. PETREL sowftware (Schlumberger) is being used to integrate the data set and to build a digital outcrop model (DOM) and a 3D facies model of this sloped tufa complex. These models will allow the accurate reconstruction of sedimentary geometries and quantification of the spatial distribution of lithofacies and their physical properties. These models are envisaged as a highly valuable tool for unraveling the sedimentological development and evolution of the cascade tufa complex and their aquifer characterization, providing key insights for understanding the geomorphological evolution during the Quaternary of the fluvial drainage network of the area. In addition, the results will help to improve the current knowledge and understanding of tufa sedimentary systems (comparatively much less studied that other carbonate sedimentary systems) and will provide valuable information for aquifer and reservoir analogs of comparable sedimentary bodies.
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Methods for Analyzing High Resolution 3D Digital Outcrop Geology: Deepwater Jackfork Sandstone at Big Rock Quarry, Arkansas
Authors C. L. V. Aiken, M. I. Olariu, M. Wang, J. P. Bhattacharya and J. F. FergusonQualitative facies distributions and quantitative bed/channel dimensions in three-dimensional virtual outcrops using ground-based remote sensing and analysis of terrain surfaces is a basis for geologic mapping and interpretation of deepwater deposits at Big Rock Quarry, Arkansas located in the southeastern part of the Ouachita Mountains in North Little Rock, Arkansas (Fig 1). Three-dimensional views of the lower part of the upper Jackfork Group (Olariu et al, 2008) allows three-dimensional reconstruction of facies architectural elements, stacked channels that lack levees and overflow deposits, a submarine channel complex deposited at the base of slope estimated as 9.6 km by 16 to 24 km pinching out 4 km north of the quarry. Flow indicators are oriented west-southwest.
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Automated Methods for Fully Exploring and Interpreting LIDAR Data Points
By S. ViseurThe LIDAR scanning combined with digital photograph mapping techniques (Bellian et al. 2005) has become a privileged tool to obtain a 3D georeferenced reconstruction of an outcrop, often termed as DOM (Digital Outcrop Model). For several years, many geoscientist applications use DOMs as support for manual interpretations of strata or fractures and facies mapping. However, the LIDAR tool produces huge data sets that become easily difficult to manipulate interactively and then to interpret. A new challenge in geomodelling is then to extract, in an automated way, geological features from a DOM. Different kinds of strategies have been proposed in the litterature based on both LIDAR points or DOMs. For example, some authors have proposed to use maximum curvature values (Ahlgren et al., 2003) in order to obtain statistics about fracture networks (orientations, density). Automated detection methods have been presented in Kudelski et al. (2009), Viseur (2008) and Viseur et al. (2009). They are applied on DOMs and they aim at extracting as polygonal lines the strata or fracture paths observed along the outcrop. Other authors (Garcia-Selles et al., 2008; Franceschi et al., 2009) use properties computed (geometrical attributes) or available (intensity) from LIDAR data points to highlight or detect geological features. Finally, authors have proposed approaches based on the ”ant tracking” algorithms applied on the colours of the mapped pictures (Monsen et al., 2007). In this paper, a series of algorithms are presented. They are integrated into a workflow to fully explore and interpret numerical outcrops from data points to horizon or fracture surface constructions. Indeed, working on DOMs requires to build surfaces from very dense multivalued XYZ data points which is time consuming and generally leads to mesh decimation in order to obtain triangulated surfaces light to manipulate. These operations may damage the information contained in the topography geometry. Therefore, working directly onto the XYZ data points may be a good alternative and allows the display of subtle relief signals. Moreover, the LIDAR engin is experiencing new developments and LIDAR data points with RGB flags are increasingly provided. The proposed approach aims at first extracting as polygonal lines the limits of geological objects from the LIDAR data points. Then, surfaces may be built to model the detected fractures or strata interfaces.
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GeoAnalysis Tools - ArcScene Extension for the Analysis of 3D Geological Outcrop Models
Authors L. White, C. Aiken, M. Alfarhan and J. ClineGeoAnalysis Tools is an ESRI ArcScene extension developed by Geological & Historical Virtual Models, LLC, based upon research performed in collaboration with the University of Texas at Dallas. GeoAnalysis Tools allows for the interactive analysis of orientation and deformation features of a 3D model of a geological outcrop. The model can be either a photorealistic solid model constructed by draping photographs on a triangulated irregular network (TIN) derived from a LIDAR point cloud or it can be the point cloud itself. Basic field measurements such as strike-dip, trend-plunge, and bedding thickness can be made on the 3D model. The program provides for the extrusion of features in a trend-plunge direction to facilitate the nature of the deformation. Down-plunge cross sections are rapidly created from traces of features such as bedding contacts and displayed in ArcMap.
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Challenges and Pitfalls of Modelling Old and Deep Petroleum Systems: Examples from North Africa and the Middle East
Authors J. Craig, D. Grigo, A. Rebora, G. Serafini and E. TebaldiOlder and deeply buried petroleum systems are usually characterised by complex geological histories, and this is certainly the case for the Neoproterozoic and Palaeozoic petroleum systems of North Africa and the Middle East. In these systems, the efficiency of the source rocks and the potential to generate, migrate and trap hydrocarbons in a time frame that allows hydrocarbons to be retained are often the most critical risks. Hydrocarbons can usually only be trapped for a few tens of millions of years because even the most perfect seals are permeable over longer periods of time. One of the most critical issues determining the efficiency of older and/or deeply buried petroleum systems is, therefore, their burial history, and specifically the existence of a ‘late’ burial phase that can allow hydrocarbons to be generated, expelled, migrated and trapped in a suitably recent timeframe. Exceptions, such as the Neoproterozoic petroleum system of the Amadeus and Officer basins of Australia or the Late Neoproterozoic-Early Cambrian petroleum systems of Oman and the Indian Sub-continent generally occur where evaporite super-seals are present and/or where the post–trapping history is dominated by extreme tectonic stability.
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Automated reconstructions of sedimentary basins in frontier area
Authors L. H. Rüpke and D. W. SchmidThe self consistent reconstruction of the thermal, tectonic, and stratigraphic evolution of sedimentary basins is a challenging task. Good results have been obtained (e.g., Bellingham and White 2002, Fjeldskaar et al. 2004, Kooi et al. 1992, Poplavskii et al. 2001, Rüpke et al. 2008) based on McKenzie’s pioneering work (1978). However, with the current petroleum prospects moving further and further into frontier areas, characterized by deep water and extreme stretching of the lithosphere, the McKenzie approach does not suffice any longer to obtain a valid reconstruction. Required additional physics include depth dependent stretching, formation of new oceanic crust, and mineral phase transitions. We have implemented all standard as well as these frontier area relevant mechanisms in a software package called TECMOD2D. TECMOD2D allows for automated thermotectonostratigraphic reconstructions of sedimentary basins. Key to this is the coupling of a forward model to an inverse scheme for automated parameter update. The forward model resolves simultaneously for lithosphere processes (e.g. thinning, flexure, temperature) and sedimentary basin processes (e.g. sedimentation, compaction, maturation). The inverse algorithm automatically updates crustal and mantel thinning factors as well as paleo-water depth until the input stratigraphy is fitted to a desired accuracy.
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Basin modelling of the Ghana transform margin: implications for the structural, thermal and hydrocarbon evolution of the Tano Basin
Authors L. H. Rüpke, D. W. Schmid, E. H. Hartz and B. MartinsenThis study explores the structural and thermal evolution of the Ghana transform margin. The main objective is to explore how the opening of the Atlantic Ocean and subsequent interaction with the Mid-Atlantic Ridge (MAR) has affected the margin’s structural and thermal evolution. Two representative evolution scenarios are described: a reference case that neglects the influence of continental break up and a second scenario that does account for a possible heat influx during the passage of the MAR as well as magmatic underplating. These two scenarios have further been analyzed for the implications for the hydrocarbon potential of the region. The scenario analysis builds on a suite of 2D realizations performed with TECMOD2D, a modeling software for automated basin reconstructions. Taking the presently observed stratigraphy as input, the structural and thermal evolution of a basin is automatically reconstructed. This is achieved through the coupling of a lithosphere scale forward model with an inverse algorithm for model parameter optimization. We find that lateral heat transport from the passing MAR in combination with flexure of the lithosphere can explain the observed uplift of the margin. These results were obtained for a broken plate elasticity solution with a relative large value for the effective elastic thickness (Te=15) and necking level (15km). Lateral heat flow from oceanic lithosphere is clearly visible in elevated basement heat flow values up to 50km away from the OCT. This influx of heat does, however, not seem to have significantly affected the maturation history along the margin. Only the deepest sediments close to the OCT show slightly elevated vitrinite reflectances in simulations that account for the passage of the MAR. In conclusion, it appears that that lateral heat transport from the oceanic lithosphere is instrumental for shaping the Ghana transform margin but seems to have only limited control on the maturation history.
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What can we expect from process-based source rock modelling: Examples from high and low resolution data sets
By U. MannIn order to be able to quantify geological processes in a distinct part of a sedimentary basin, two prerequisites are essential: first, a reasonable description of the most relevant processes taking place, and second, the description of these processes in 3 dimensions. The process-based source rock modelling software OF-Mod 3D aims at predicting source rocks units in sedimentary basins in terms of distribution and properties. It simulates the most important processes relevant for organic matter accumulation in sediments, and the interactions between them. Modelled processes are: supply and distribution of marine and terrigenous organic matter, degradation in the water column, burial efficiency at the sea floor under oxic and anoxic (oxygen minimum zones, anoxic bottom water) conditions, as well as dilution of the organic matter with siliciclastic sediments. The results can be calibrated to or just compared with analytical data from well samples. The advantage of such process-based modelling of organic sedimentation is that the process descriptions substitute to some degree for missing data and therewith the modelling has predictive power. In addition, complex parameter interactions are considered and the influence of each control parameter can be identified easily. In terms of petroleum systems modelling, it is also notable that the process-based forward modelling approach results in initial, not maturity-altered source rock properties. This is important since often geochemical data from exploration wells are heavily maturity altered and thus provide no further information on source rock properties that can be used as input into hydrocarbon generation and migration modelling.
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Which equations to pick: a comparison of equations for calculating marine organic carbon deposition
More LessAny quantitative description of a geological process requires a mathematical model describing the relevant processes, as well as values for the input parameters. The processes involved in the deposition and preservation of marine organic matter include the flux of the primary produced organic matter from the sea surface to the sea floor, burial efficiency of the material that reaches the bed, and finally the amount of total marine organic carbon that is preserved in the deposit. These three processes are commonly modelled using empirical equations, mostly derived from fits to modern data sets. A range of equations exists for each process, derived by different authors from different data sets (although older data sets are commonly included in newer derivations). This means that a range of answers can be expected when using different combinations of equations to describe marine organic carbon deposition in a given area. The input parameters for equations describing these processes are primary productivity, water depth, sedimentation rate, and oxygen conditions at the bed. For present-day simulations, input parameters are available from measurements. This is unfortunately not the case for simulations of the geological past, but in this case they can be estimated from data measured in cores. The parameter estimation can be done using the same empirical equations as used for the process descriptions. As a range of equations exists, again a range of estimated values can be expected.Several equations and combinations of equations were used to investigate the range of answers that different approaches give. The different equations were used in a Monte Carlo simulation of the calculation of marine organic carbon values, to estimate values of primary productivity with published core data (other input parameters were obtained from the core measurements), and to simulate the spatial distribution of marine organic matter with the forward model OF-Mod (Organic Facies Model).
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Numerical Modelling of Hydrothermal Fault-Related Dolomitization
Authors F. H. Nader, J. -M. Daniel, O. Lerat and B. DoligezClassical diagenesis studies make use of a wide range of methods and analytical techniques in order to suggest conceptual models that explain specific, relatively time-framed, diagenetic processes (like dolomitisation) and their impacts on reservoirs. Modern techniques usually combine petrographic analyses (by means of conventional, cathodoluminescence, fluoresence, and scanning electron microscopic techniques), geochemical measurements (major/trace elements, micro-probe, stable oxygen and carbon isotopes, Sr radiogenic isotopes) and fluid inclusion analyses, providing independent arguments to support the proposed model. Still, conceptual models are qualitative and do not yield "real" data for direct use by reservoir engineers for rock-typing and geomodelling. This contribution provides new insights into numerical modelling of hydrothermal dolomitisation.
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Challenges in the modelling of hydrocarbon systems from seismic cubes
By Ø. SyltaSeismic data have for a long time been used to build geologic models for basin modeling purposes. The basin models used in migration studies have typically been built as 2D section profiles (Figure 1), but over the last 10 years we have seen 3D stratigraphic geometries being built from interpreted seismic horizons. The interpretations have been depth-converted and merged into a 3D structural framework, and the "inside" of the layers have thereafter been populated with flow properties from geological libraries. These libraries will often be very elementary in their representation of the flow properties, resulting perhaps in too simple hydrocarbon migration flow patterns in modeled basins.
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Integration between Pore Pressure Prediction and Petroleum System Modelling Methodologies
Authors P. Sibin, M. Della Martera, M. Tonetti and C. AndreolettiThe necessity to satisfy the world needs of oil & gas presses Oil Companies to drill in conditions that are getting harder and harder in terms of geopressure environment. In exploration, pore pressure prediction is critical for the evaluation of vertical and lateral sealing, the estimation of maximum possible column of hydrocarbons in place, and consequently to rank the prospects and evaluate the economics. Moreover, the overpressures have created serious problems during drilling operations in the past and also at the present time; for all these reasons, the geopressures prediction is important to define the best well design in order to reduce NPT, costs and reservoir damages. In order to build the appropriate model and to face this complex problem in the right way, the
necessary information have to be collect, interpreted, elaborated and evaluated by several disciplines and for this kind of item, geology, geophysics and engineering have to be strongly integrated to give the best. We know from several years that information about geopressure can be derived from seismic velocities, and several relationships exist and applied with considerable success, but generally, in complex and deep areas, conventional velocity fields derived from seismic time processing are often
not accurate enough to make a correct pore pressure prediction. For this reason, several methods have been developed trying to obtain more appropriate velocity fields.
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