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Workflow: Reservoir Characterization

This page will review individual workflows used for reservoir characterization:


Rock Typing Using SCAL Data: Mercury Injection Capillary Pressure and Relative Permeability Data

The above workflow represent the process through which MICP and other data can be used in order to generate Rock Types.

The workflow includes the following steps:

  • Curve Representation using Intelligent Compression Technology.
    • Reservoir Dependent Technique.
    • Must accurately reproduce the original Capillary Pressure and Relative Permeability Curves.

    ISI's curve representation algorithms reproduces Pc and Relative Permeability curves with accuracy.

  • Rock Typing with State-of-the-Art Classification Algorithms, using Advance AI&DM Techniques (Self Organizing, Reinforced and Supervised Cluster Analysis ).

ISI's workflow provides three different techniques for Rock Typing. You may use any of these techniques (or a combination of them) in order to perform the task. These techniques are:

  1. Self Organizing Cluster Analysis: Let IDEA™ Select the Rock Types.
  2. Reinforced Cluster Analysis: Domain Expert Observes and Influences IDEA™'s Rock Type Selection.
  3. Supervised Cluster Analysis: IDEA™ is trained to reproduce Domain Expert's Rock Type Selections.

Furthermore, ISI's workflow provides two possible Rock Typing Schemes. These schemes are:

  1. Crisp Cluster Analysis: Rock Types do not overlap.
  2. Fuzzy Cluster Analysis: Overlapping Rock Types.

ISI's workflow allows overlapping and non-overlapping Rock Types.

An overview of techniques offered by ISI as Rock Typing workflow.

Overlapping Rock Types in a Porosity-Permeability cross plot. A naturally fractured carbonate reservoir.

Capillary Pressure curves for Rock Type Number 1.

Capillary Pressure curves for Rock Type Number 2.

Capillary Pressure curves for Rock Type Number 3.

Capillary Pressure curves for Rock Type Number 4.

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References:

  • Intelligent Data Evaluation & Analysis; IDEA™


Propagation into Cored Wells: wells with no SCAL data

The above workflow represent the process through which Rock Types are estimated for wells that have core data (porosity and permeability) but not SCAL data.

Using ISI's workflow shown above, all available information such as Depth, Latitude, Longitude, Porosity and Permeability from cored wells are used along with some relevant log data in order to estimating Rock Types.

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References:

  • Intelligent Data Evaluation & Analysis; IDEA™


Propagation into Logged Wells: wells with no Core data

The above workflow represent the process through which core-porosity and core-permeability values are estimated for wells that have log data (Gamma Ray, Density, Sonic, SP, Resistivity ...) but not core data.

Using ISI's workflow shown above, all available information such as Depth, Latitude, Longitude, log data (Gamma Ray, Density, Sonic, SP, Resistivity ...) from logged wells are used along with some relevant geostatistical data in order to estimating Porosity and Permeability.

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References:


Propagation into Full Field: populating grid cells between wells

The above workflow represent the process through which well logs such as Gamma Ray, Density, Sonic, SP and Resistivity are estimated for 3D seismic attributes.

Using ISI's workflow shown above, all available information such as Depth, Latitude, Longitude, and 3D seismic attributes are used along with some relevant geostatistical data in order to estimate well logs for all locations in the reservoir. This workflow lets you log a well, before drilling it.

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References:


A Comprehensive Workflow for Populating the Geo-Cellular Models

The above workflow represent the process through which a geo-cellular model is populated using the best possible data and information gathered from multiple sources. You can see details of each component of the above workflow in the corresponding pages

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References: