• Class and Course

    Integrated Reservoir Modeling: Interpretation, Evaluation, and Optimization with Petrel

    This five day interactive and practical course will help participants to use geological modeling to produce realistic volumetric estimations for hydrocarbon reservoirs.  It will show how new operational data and revised interpretations, such as a new well or a recently discovered fault, can be identified and incorporated into models at any point in the workflow.

    This course will introduce the procedures and workflow for building a 3D model, regardless of the software available to the modeling team.  In other words, this will be an attempt at a best practice approach to a complex and varied workflow. There will be a particular emphasis on integrating static and dynamic reservoir properties with the geological facies model.  Exercises will be done using industry standard modelling software (Petrel), although it should be emphasized that the purpose of the course is methodology and not software operation.

    Relevant industry case studies and practical applications will be reviewed throughout the course.  Participants will gain an understanding of the key challenges associated with building effective 3D reservoir models from interpretation and design to quality assurance and optimization of results.

    Participants will understand the science and workflows behind building consistent 3D reservoir models including fluid distribution, permeability, compartments and volumetric estimation. They will learn how integrate data from cores and logs and how to upscale this data into geological and flow simulation models that will have a high impact on field development and production scenarios.

    Day 1

    Conceptual Design and Workflow

    • Reservoir envelope: top and base structure
    • Internal framework: correlation scheme
    • Reservoir compartments: fault geometry
    • Reservoir architecture: facies model
    • Petrophysical property distribution
    • Volumetric Assessment

    When planning a reservoir modeling project, the ultimate purpose of the model must be defined.  To this end the geological model should address all of the above points.  On the first day, participants will learn about the retention of relevant fine-scale detail through upscaling.  The process of building a 3D reservoir model will always follow the same general workflow, regardless of the tools available to the modelling team.  Each of the steps will be outlined in the course with an appreciation of the required input data, associated uncertainties, and likely deliverable and its use. The database used for the exercises will be from a real field that includes two different clastic reservoir types with different modeling challenges.

    Day 2

    Reservoir Framework

    • Depth conversion uncertainty
    • Model surface selection and quality control
    • Fault modelling and compartments
    • Stratigraphy and correlation
    • Grid construction

    In volumetric models the greatest uncertainty is usually the gross rock volume at the top structure map and the hydrocarbon contact.  Depth conversion, where well data can be sparse, leads to much of this uncertainty.   Structural models that result in over complexity, much of which cannot be modelled, may drive seismic interpretation.  Participants will learn how to decide what structural elements to include, which can be a source of much debate.  Likewise too much well-to-well correlation can over science a model especially when still in development and drilling surprises are common, so it will be covered on this day as well.

    Day 3

    Reservoir Architecture

    • Depositional models and facies analysis
    • Core-log integration
    • Basic statistics
    • Objects and indicators
    • Seismic conditioning
    • Facies modelling

    Participants will learn about the different clastic and carbonate depositional environments and how to best characterize them for subsequent modelling.  The dependence on statistics will be introduced as a way to demonstrate the different methods of facies modelling available.

    Day 4

    Property Modeling in 3D

    • Basic petrophysics
    • Rock typing
    • More basic statistics
    • Porosity models
    • Saturation models
    • Permeability models

    Running through the course will be the theme of petrophysics, always calibrated to the geology, as a way to distribute reservoir properties.  Participants will be shown simple rock typing methods that are readily applicable to 3D models.  Particular attention will be paid to saturation height methods that accurately distribute fluids through the model.

    Day 5

    Uncertainty and Upscaling

    • Geological model analysis
    • Hydrocarbon volumes initially in place
    • Drainable volumes
    • Simulation grid construction
    • Property upscaling
    • Multiple scenarios, realizations, and ranking

    What makes a good static model will be discussed.  The methods of interrogating and analyzing the results described before addressing the thorny question of upscaling for dynamic simulation will also be covered.

    This course is designed primarily for geologists, geophysicists and reservoir engineers involved in subsurface reservoir characterization and who wish to know how to derive geologically robust framework models and how to populate them with meaningful reservoir properties. Attendees should include Geologists, Geophysicists, Petrophysicists, Reservoir Engineers, Drilling Engineers, and Seismic Interpreters.

    • Modelling Overview
    • Conceptual Design and Workflow
    • Geological Modeling Project Workflow
    • Geophysical Data Interpretation and Integration
    • Reservoir Framework
    • Property Modelling
    • Rock Types and Flow Zones
    • Volumetrics and Uncertainty
    • Upscaling Models for Reservoir Simulation

    Students are expected to have a clear understanding of how to use the Petrel software. It is suggested that a Petrel Fundamentals course has been taken, although this is not mandatory.

    Some understanding of the principles of Geology and Log Analysis.

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