Petrel facies modeling

Name: Petrel Geology and Modeling Facies Modeling
Availability: InStock

Build accurate facies models

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Overview

Petrel™ facies modeling is used to populate geocellular grids with discrete property values for geological characterization of the reservoir. It enables both simple and complex workflows—such as seismic-driven modeling in which probabilities can be used in several different ways to help create a realistic representation of the depositional facies or lithologies.

Complex geometries such as this flower structure is represented by a stairstep grid populated with interpolated facies from well data.

Multipoint facies simulation brings together the best of both pixel-base and object-based modeling techniques.

Model lateral variations of environment such as progradation and import an image or a surface to aid in the set-up of facies transitions.

Control the Object Modeling variables to derive your required object size, orientation and dimensions. Combine to develop your facies model.

When new data becomes available, such as new well tops and logs, structure and properties can be updated locally.

A facies model viewed in geological space (geospace), which has been modeled from upscaled well data.

A facies model viewed in depositional space (depospace), which has been modeled from upscaled well data.

Applications

Complex geometries
truncated gaussian with trends
channel object modeling controlled by trends
pixel-based and object-based modeling

Benefits

High-resolution well log data and point attribute data can be upscaled into the geocellular grids. Properties are distributed into the remaining 3D grid volume by using a variety of algorithms. Structural grids can model “depositional” properties more accurately using the depospace concept.

Combining property modeling techniques, truncated gaussian with trends together with channel object modeling controlled by trends.

Features

Deterministic modeling algorithms, such as indicator kriging (pixel-based method for producing facies models based on kriging probabilities)
Interactive editing to draw and intuitively edit facies models, with geological brushes for more realistic depositional environment design
Stochastic modeling algorithms, such as object modeling, sequential indicator simulation, truncated Gaussian simulation, or multipoint statistics
Generation of dynamic QA maps
Ability to save property modeling input parameters as objects to reuse, share, and include in workflows
Modeling input parameters editor for editing, viewing, exchanging, and reporting of all facies modeling parameters inside a flexible, unified, tabular interface

Training

A group sitting in an auditorium watching a presenter speak on a characterization model image

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