Seismic Interpretation and structural modeling
We create detailed models that allow a better understanding of hydrocarbon reservoir, adjusting the volumetric estimates, proposing directional wells, and refine field development strategies.
We guarantee that the structural model is consistent with the geological framework and the available data, free from geometric defects, and ready to host quantitative information of rock and fluid properties obtained through Quantitative Geosolutions´s workflows.
Quantitative GeoSolutions has experienced interpreters and
The use of geometric attributes allows us to delineate the most subtle seismic discontinuities, facilitating the interpretation of primary and secondary faults, as well as zones associated with fractures. The results can be used as a reference framework in later stages, as well as in the integration with products of quantitative processes.
Seismic Data Conditioning To Perform Quantitative Analysis
The success of the quantitative analysis and processes depends on the quality of the available seismic information. Therefore, seismic data conditioning process is mandatory, even knowing that it is not possible to fully resolve the deficiencies related to seismic surveying limitations
The main challenges that must be faced in the data preparation stage are related to the improvement of S/N ratio, the attenuation of residual multiple events and the optimization of the seismic signals, specially, in the context of far offsets.
The figure illustrates the seismic conditioning workflow applied by Quantitative GeoSolutions to prepare seismic data for quantitative studies.
Workflow for seismic conditioning.
Seismic Inversion And Rock Physics Analysis
Quantitative GeoSolutions uses integral solution schemes in the execution of quantitative studies that link seismic and well data in the context of various scales and domains.
These links, in addition to their physical and mathematical characteristics, are also relations between DIRECT and INVERSE processes through the rock audit, which serves as a bridge between elastic and reservoir properties.
The general seismic characterization process, based on inversion and rock physics modeling, is shown schematically in the image below.
General workflow of seismic inversion and rock physics modeling
In general, if PS wave seismic data of good quality is available, the joint simultaneous seismic inversion PP-PS allows to generate shear impedance and density with higher quality than those obtained by means of purely PP inversion.
Amplitude varies with azimuth. It is widely recognized that, in rocks affected by fractures, the azimuthal variation of properties is remarkable and measurable. In general, fractures induce anisotropy. Depending on how they affect the rocks, it is possible to set various anisotropic arrangements of high or low symmetry. Tha azimuthal inversion workflow is shown below.
General inversion engine
The azimuthal seismic inversion allows the identification of areas with strong or weak anisotropic behavior induced by fractures. Quantitative GeoSolutions manages to define these scenarios by doing a combined analysis of attributes related to azimuthal inversion. These results are extremely useful in the process of identifying areas with high or low hydraulic connectivity, stress directions, and main flow directions.
Integration Of Results And Prediction Of Reservoir Properties
Artificial intelligence has proved to be a very effective tool because it does not assume a priori physical relationships between rock properties and characteristics of geological environments. The predictions are made based on the intelligent recognition of non-linear patterns.
In order to establish relevant physical links between the microstructural characteristics of rocks and the elastic properties, Quantitative GeoSolutions uses advanced algorithms that simulate reservoir characteristics.
These algorithms are used to establish relationships between pore shape (in various rock types), fracture intensity, fluid type, mineral content and P and S impedance and density. Rock physics models are constructed from the microstructural rock components (solid and fluid phases), following strict physical criteria and rules. As an example, the figure below presents a rock physics model for carbonate rocks.
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Stress field from integrated seismic-geomechanical studies
Integration of probabilistic and artificial intelligence techniques for prediction of limits and intrinsic reservoir characteristics.
Reservoir intrinsic characteristics and geometry prediction
Fluid saturation prediction in low porosity reservoirs
TRAINING
Rock physics applied to the oil industry
In this course, the foundations of rock physics are introduced. We also show the direct applications in reservoir properties prediction. We also discuss the potential of rock physics workflows in the context of reservoir storage and flow capacity in porous rocks.
Seismic anisotropy applied to the oil industry
In this course the foundations of elastic anisotropy are introduced, based on classic observations of earth’s crust rocks. In addition, we show diverse elastic scenarios to which a certain symmetry arrangement can be integrated for modeling and seismic inversion purposes. This approach can be used to detect anisotropic anomalies that can be linked to potential reservoirs properties.
Multicomponent seismic (theoretical and practical aspects)
This course introduces the basic concepts of wave conversion phenomena a how they can be affected by geological interfaces. Special emphasis is given to the types of PS conversion (fast and slow), how to recognize it and physics involved in the process. The course also focus on the processing workflow of PS converted waves, the limitations of processing algorithms currently available in the industry. Direct applications in reservoir characterization are discussed.
Fundamentals of seismic inversion
In this course the seismic inversion foundations are introduced. A didactic review of the most relevant methods is made. We talk about the boundary conditions, the advantages and limitations. The “trues and lies” are discussed. The potential of seismic inversion is shown in an objective manner, based on our intrinsic knowledge of the “hidden” algorithms.