With the structural framework built, you must populate each individual 3D cell with discrete (facies) and continuous (porosity, permeability) reservoir properties. Scale Up Well Logs
: Distribute petrophysical properties like porosity and permeability using algorithms such as Sequential Gaussian Simulation.
. Below is a high-level "story" or workflow for a typical project, ranging from initial setup to dynamic modeling. 1. Project Setup and Interface
In a tutorial setting, users should practice importing a small subset: one SEG-Y cube, three wells with gamma ray and resistivity logs, and five interpreted horizons. Petrel’s Import wizard handles most formats, but critical details—such as units, sampling rates, and null values—must be checked manually. A common mistake is ignoring the vertical datum; ensuring all data shares the same reference (e.g., mean sea level or subsea) prevents later misalignments. petrel tutorial
Displays geological cellular grids, properties, and upscaled data generated during modeling.
Select the Guided picking or Manual picking tool. Click along a continuous reflector (amplitude peak or trough) on an inline or crossline section.
Once the framework is built, you populate it with geological properties. With the structural framework built, you must populate
: Familiarize yourself with the ribbon tabs. You will spend most of your time toggling between Stratigraphic , Seismic Interpretation , Structure Modeling , and Property Modeling . 📥 Step 2: Data Import (Seismic and Logs)
To master Petrel, you must understand its data structure. Petrel is a —meaning all data sits within a common 3D grid.
Found at the bottom left, this serves as an interactive workflow checklist. It guides you sequentially from data import to simulation. Project Initialization Steps Open Petrel and create a new project: File > New Project . Below is a high-level "story" or workflow for
Generate a to tie your well logs (depth domain) to your seismic data (time domain) using a checkshot survey. Select the Horizon Interpretation tool.
[ OIP = GRV \times N/G \times \Phi \times S_o \times (1/FVF) ]
With the structural framework in place, the user moves to . This is where the static model comes to life. The grid consists of millions of individual cells, or blocks. Initially, these cells are empty. The goal is to populate them with properties such as porosity, permeability, and water saturation. Petrel uses algorithms—most notably "Geostatistics" and specifically Kriging or Sequential Gaussian Simulation (SGS)—to fill these cells. The software takes the hard data from the well logs and extrapolates it outward into the space between wells, using statistical rules to predict where high-quality sand might transition to low-quality shale. This tutorial step requires a balance of mathematics and geological intuition; the computer can calculate statistics, but the geologist must tell the computer the direction in which the ancient rivers or sand dunes were flowing.