PetroMod petroleum systems modeling software combines seismic, well, and geological information to model the evolution of a sedimentary basin. PetroMod software will predict if, and how, a reservoir has been charged with hydrocarbons, including the source and timing of hydrocarbon generation, migration routes, quantities, and hydrocarbon type in the subsurface or at surface conditions.
PetroMod software is the most advanced commercially available oil and gas migration modeling technology and the only commercial system with fully PVT-controlled modeling of ncomponent 3-phase relationships during the entire migration process. Multiple simulation methods, i.e., Darcy, flow path (ray tracing), invasion percolation (IP), and the PetroMod software hybrid Darcy-flow path-IP simulator, can be used with the same data models. The 2D and 3D migration modeling technology uses flash calculations throughout the entire model and its geological history. This delivers an improved understanding and prediction of petroleum properties and oil versus gas probability assessments.
PetroMod 2021.1 is also available in the DELFI cognitive E&P environment as part of the Petrotechnical Suite.
PetroMod 2021.1 combines a state-of-the-art user interface with high-simulation performance that enables you to perform sophisticated analyses of the dynamic temperature, pressure, and migration history of complex geological systems in a fast and intuitive, process-focused workflow. The unification of the 2D and 3D model builder and viewer capabilities allow a fast switch between 2D and 3D model setup and analyses, saving you time and costs.
In PetroMod 2021.1, we offer the very first commercial release of a new way of defining local grid refined (LGR) models. This new volume of interest (VOI) LGR technology enables you to limit the high-resolution local model or child model or both to a minimum of only one single layer of interest.
Any number of additional overburden and underburden layers is possible. The simulator will use these layers from the regional model instead.
You are now able to edit the extracted boundary conditions (overlays) on all 6 sides of your nested model in PetroBuilder 3D to generate very fast scenarios and to better calibrate the high-resolution child model.
Viewer 2D and 3D
In the 2D and 3D Viewers, you now have a new and very efficient way to check the calibration precision of your modeled scenarios. When using the 1D extraction tool, a preview plot will appear in a side panel of the viewer. If a well location was chosen, all corresponding calibration data will be displayed, and calibration accuracy is calculated and reported.
The 1D preview will interactively update to changes of overlays, timesteps, and new
locations. You have the option to open the full extraction as usual in 1D Viewer by selecting the corresponding button in the side panel.
In the output organizer, you can now project any polygon (hand-drawn, existing cultural data, drainage areas) to the top of any layer. Previously, all polygons were displayed in 3D view at sea level. Now, projected polygons allow you to overcome the previous limitations for better communication and decision making during your model analysis.
We added two new data columns to the calibration data table. Defining the measurement method and quality markers results in calibration quality control, and you can filter calibration data in displays (see 1D preview extractions).
The project browser is accessed from the Command Menu. It displays a list of all models in your project. When you select a listed model, you will be given all relevant information to differentiate models from each other and to select the model you would like to modify, view, or even delete. Once selected, you can directly open the model input or output in the corresponding applications.
In the simulator interface, you will receive an estimated run time prior to simulation. The prediction is interactive. If you change simulation settings, such as migration method, the number of CPUs or specific tools, the predicted run time will be adjusted accordingly. If you rerun the same model, the prediction will learn from the previous runs, delivering a more precise prediction.