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  • 1
    Publication Date: 2016-08-03
    Description: Quantitative seismic interpretation has become an important and critical technology for improved hydrocarbon exploration and production. However, this is typically a resource-demanding process that requires information from several well logs, building a representative velocity model, and, of course, high-quality seismic data. Therefore, it is very challenging to perform in an exploration or appraisal phase with limited well control. Conventional seismic interpretation and qualitative analysis of amplitude variations with offset (AVO) are more common tools in these phases. Here, we demonstrate a method for predicting quantitative reservoir properties and facies using AVO data and a rock-physics model calibrated with well-log data. This is achieved using a probabilistic inversion method that combines stochastic inversion with Bayes' theorem. The method honors the nonuniqueness of the problem and calculates probabilities for the various solutions. To evaluate the performance of the method and the quality of the results, we compare them with similar reservoir property predictions obtained using the same method on seismic-inversion data. Even though both approaches use the same method, the input data have some fundamental differences, and some of the modeling assumptions are not the same. Considering these differences, the two approaches produce comparable predictions. This opens up the possibility to perform quantitative interpretation in earlier phases than what is common today, and it might provide the analyst with better control of the various assumptions that are introduced in the work process.
    Print ISSN: 1070-485X
    Electronic ISSN: 1938-3789
    Topics: Geosciences
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  • 2
    Publication Date: 2012-10-25
    Description: Modeling the elastic properties of clay-bearing rocks (shales) requires thorough knowledge of the mineral constituents, their elastic properties, pore space microstructure, and orientations of clay platelets. Information about these variables and their complex interrelationships is rarely available for real rocks. We theoretically modeled the elastic properties of synthetic clay-water composites compacted in the laboratory, including estimates of pore space topology and percolation behavior. The mineralogy of the samples was known exactly, and the focus was on two monomineralic samples comprised of kaolinite and smectite. We used differential effective medium theory (DEM) and analysis of scanning electron microscope (SEM) images of the compacted kaolinite and smectite samples. Percolation behavior was included through calculations of critical porosities from measurements of the liquid limits of the individual clay powders. Quantitative analysis of the SEM images showed that the large scale ( $$ 〉 0.1\hbox{ \hspace{0.17em} }\hbox{ \hspace{0.17em} }\mathrm{\mu m}$$ ) pore space of the smectite composite had more rounded pores (mean aspect ratio $$\alpha =0.55$$ ) than the kaolinite composite (mean pore’s aspect ratio $$\alpha =0.44$$ ). However, models that used only these large-scale pore shapes could not explain the compressional and shear velocity measurements. DEM simulations with a single pore aspect ratio showed that bulk and shear moduli are controlled by different pore shapes. Conversely, modeling results that combined critical porosity and dual porosity models into DEM theory compared well with the measured bulk and shear moduli of compacting kaolinite and smectite composites. The methods and results we used could be used to model unconsolidated clay-bearing rocks of more complex mineralogy.
    Print ISSN: 0016-8033
    Electronic ISSN: 1942-2156
    Topics: Geosciences , Physics
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  • 3
    Publication Date: 2013-04-13
    Description: Seismic reservoir characterization requires a transform of seismically derived properties such as P- and S-wave velocities, acoustic impedances, elastic impedances, or other seismic attributes into parameters describing lithology and reservoir conditions. A large number of different rock physics models have been developed to obtain this link. Their relevance is, however, constrained by the type of lithology, porosity range, textural complexity, saturation conditions, and the dynamics of the pore fluid. Because the number of rock physics parameters is often higher than the number of seismic parameters, this is known to be an underdetermined problem with nonunique solutions. We have studied the framework of inverse rock physics modeling which aims at direct quantitative prediction of lithology and reservoir quality from seismic parameters, but where nonuniqueness and data error propagation are also handled. The procedure is based on a numerical reformulation of rock physics models so that the seismic parameters are input and the reservoir quality data are output. The modeling procedure can be used to evaluate the validity of various rock physics models for a given data set. Furthermore, it provides the most robust data parameter combinations to use for either porosity, lithology, and pore fluid prediction, whenever a specific rock physics model has been selected for this cause.
    Print ISSN: 0016-8033
    Electronic ISSN: 1942-2156
    Topics: Geosciences , Physics
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  • 4
    Publication Date: 2015-11-05
    Description: Identifying type of rocks and fluids from seismic-amplitude anomalies can be challenging because of seismic nonuniqueness and rock-physics ambiguities. Lithology and fluid predictions based on seismic properties therefore are often associated with uncertainties. On the Norwegian Shelf, clay-rich source rocks and hydrocarbon-filled sandstones often show similar AVO responses. A seismic screening method based on rock physics enables one to better discriminate between these different facies. This technique is demonstrated on seismic AVO data (i.e., acoustic impedance [AI] and V P / V S ) from the Norwegian Sea. Rock-physics models for organic-rich shales and gas sandstones are calibrated using nearby well data. Then these models are used for predictions of rock parameters away from well locations. From these predictions, the likelihood of presence of organic-rich shales versus gas sandstones can be evaluated, based on a rock-physics approach. However, there are many uncertainties in the accuracy of the calibrated models and the seismic image of the target area. Hence, predictions should be evaluated along with other geologic and geophysical information before firm conclusions about these anomalies are made.
    Print ISSN: 1070-485X
    Electronic ISSN: 1938-3789
    Topics: Geosciences
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