Ne perdez pas de temps à choisir un horizon, maîtrisez notre technologie RGT (temps géologique relatif) et créez de la valeur à partir de l'ensemble de votre cube sismique en un clic ! Adoptez notre approche globale et semi-automatique de l'interprétation sismique, basée sur un processus itératif de création de modèles de grille et de temps géologique relatif.
This comprehensive method utilizes a three-step computer-aided workflow :
- Autotracking: our powerful algorithm converts all seismic reflections into horizons and organizes them stratigraphically.
- QC and Iteration: flexibility and ownership is given to the interpreter who can interactively edit auto-tracked horizons and update the Model-Grid in real-time to obtain a fit-for-purpose solution. Repeated cycles of adjustments enable to refine the product to the desired degree.
- A Relative Geological Time (RGT) model is consecutively computed from the seismic based on the aforementioned refined Model-Grid. The RGT model plays a central role in PaleoScan integrated workflows as many interpretative applications are directly derived from it.
Experience our RGT-based attributes!
From the RGT workflow, you can instantly visualize more than 30 attributes and realize more than 40 attributes derived from seismic or RGT model.
Whether you are at the dawn or the dusk of your interpreter career, our 3-star workflow relies on our “body and soul” stratigraphic attributes: Spectral Decomposition and Thinning.
- Spectral decomposition is a technique relying on the transformation of each individual 1D seismic trace into a 2D time-frequency representation using either Short Time Fourrier Transform (STFT) or Continuous Wavelet Transform (CWT). It aims at extracting discrete frequency magnitudes to tune beds according to their thicknesses and provides high precision imaging of source-to sink systems and reservoir complexity and heterogeneities.
- The thinning attribute is the vertical derivative of the RGT Model. It shows for every seismic sample the instantaneous variation of the relative geological ages. It highlights zones of strata convergence and divergence leading to the interpretation of geometrical relationships within sedimentary units, relative accommodation space variations and seismic stacking patterns.
Wondering about how to quickly assess your depositional environment and target sweetspot areas at early stage? Try our quick and pragmatic method!
Explore your seismic volumes faster, further and beyond the seismic sampling!
One of the main applications derived from the RGT model is the ability of extracting an infinite number of iso-age surfaces gathered within a so-called “Horizon stack” product. This high-density stratal slicing enables to interactively tie any key surface to major events and dynamically flatten or sculpt the data allowing you to accelerate data recognition, detection and characterization of fine-scale geologic features.
Map your attributes on any horizon and start screening through your geomorphological data in no time!
The vast range of attributes, including Spectral and Frequency decomposition, and the excellent color blending functionality make high quality and fast attribute analysis. Vizualise geological bodies from large scale source-to-sink systems to reservoir scale features by assigning attributes or frequency decomposition to each channel. Save time and effort on focusing more on integrating your knowledge and understanding your depositional history.
Build your structural framework at the speed of a blink!
Handling dense and complex fault networks is at your fingertips with our incredibly fast and hands-on Automated Fault Extraction (AFE) workflow.
Our innovative solution proposes an optimized computation of variance values at a given voxel location using different scanning orientations (dips/azimuth) to automatically extract set of faults from a seismic volume. PaleoScan™’s technology gives you the control to investigate and identify optimal parameter settings every step of the way!
Fault management tools such as Fault Merge Assistant and dip/azimuth filtering stereonet are tremendously useful to speed up the interpretation time and extraction of meaningful and valuable fault sets. The resulted extracted faults can then be used to optimally constrain the RGT model and the Geocellular grid.
Sealing mechanisms and fault geomechanical properties are crucial information in prospect evaluation and productivity enhancement and can be preliminary assessed through our Fault throw attribute and Allan diagram tool.
Strengthen your 3D chronostratigraphic framework, pinpoint your key stratigraphic surfaces, apprehend the spatial and lateral evolution of your megasequences and their intrinsic depositional environments through our Seismic Stratigraphy module.
Wheeler diagrams, or chronostratigraphic charts, provide a useful way to look at stratigraphic temporal relationships, particularly with regards to understanding the location and timing of erosional and non-depositional events.
Our wheeler transform optimized algorithm allows a direct translation of stacking patterns and systems tracts into relative geological times by flattening the seismic data along chronostratigraphic surfaces. In this way, the sedimentary layers can be considered in terms of base level changes and sedimentation interplay, unconformities and hiatuses allowing you to be more predictive in locating reservoir, seal and source-rock facies.
Build a robust stratigraphic framework, control and predict your facies distribution and reservoir quality by integrating stratigraphic markers and well log data to your seismic data.
PaleoScan™ provides a toolkit for visualizing, editing and analyzing well data. Create geological cross-sections, quality check your results and use markers and surfaces to simultaneously flatten your well correlation panels, cubes and lines.
Scan, detect and extract 3D geobodies using our seismic facies-based workflow available on the Cross-plot functionality.
Interactive cross plotting of attributes and well log data is a fundamental tool for lithofacies classification and fluid substitution effects understanding.
Both manual and automatic classification methods are available to create and organize your lithology or facies classes. By thoroughly and interactively analyzing seismic signatures, you can select a meaningful range of values within your cube and extricate the associated geobodies.
Lithofacies classification performed from well log data results in the creation of discrete well logs that can be further used in quantitative reservoir evaluation.
Bridge the gap from seismic interpretation to reservoir modelling by performing an initial assessment of the three-dimensional distribution of the reservoir heterogeneities and petrophysical properties through the incorporation of all available information derived from well-logging data.
To bring a step-forward structural interpretation, PaleoScan™ offers unique method to directly generate vector space models from RGT-driven geological layers and fault networks. The newly computed Watertight model is then meshed in 3D to obtain sealed fault-surface contacts. These contacts form the basis for fault polygon extraction and layers juxtaposition display within an Allan diagram.
Using the same RGT-driven layers and faut networks input combined with stratigraphic termination management and stacking pattern assignment, a Geocellular grid can be computed and populated with seismic facies or rock properties. This regular stratigraphic grid of corner point type manages stair-stepped fault modeling.
The thorough well analysis from all types of wireline logs achieved by PaleoScan’s classification “Cross-plot” tool leads to static reservoir property extraction. Our Property Modeling module proposes several propagation methods to interpolate between well logs such as inverse distance, kriging and co-kriging which can be visualized on real time on a surface or a cross-section along wells.
One of our signature workflows uses a priori Impedance Acoustic cubes from property modeling to constrain Colored Inversion and Deterministic Inversion processes. The subsequent results are finally used to populate the Geocellular grid with porosity and fluid content properties.