3D Static Geological Model using PETREL

Introduction

The main objective of this course is to provide a comprehensive understanding of static reservoir modelling and reliable reservoir models, which used to predict oil production, investigate various production scenarios and eventually help decision makers to optimize field development. The more data-consistent the model, the sounder the predictions. Thus, the key point is the integration of all available data into reservoir models for field development strategies and how to maximize recoverable hydrocarbon.

Objectives

By the end of this training course, participants will learn to:

• To understand geostatistical methods.
• To apply geostatistical models to evaluate the data.
• To understand the concepts of Kriging and cokriging and how these are used in data analysis.
• To develop a conceptual geological model ahead of a static model building.
• To develop a sound structural model using regional data applied down to the model scale.
• To develop and test a stratigraphic model.
• To be able to develop a facies model and how to test this against analogs.
• To be able to determine petrophysical and property models.
• To know how to generate an accurate 3D static model by integrating all the above.
• How to integrate with the reservoir engineer to match simulation data

Training Methodology

This is an interactive course. There will be open question and answer sessions, regular group exercises and activities, videos, case studies, and presentations on best practices. Participants will have the opportunity to share with the facilitator and other participants what works well and not so well for them, as well as work on issues from their own organizations. 

Who Should Attend?

This course is designed for all Oil Industry Technical Professionals and will cover from fundamental theoretical background to high-level real work information, techniques, and workshops. This training course is suitable for a wide range of professionals but will greatly benefit:

• Geo-modelers, Petrophysicists, Seismic Interpreters, Development Geologists, Reservoir Engineers, Well site geologists, Technical Support Personnel, Team Leaders, and managers.

Course Outline

Data Conditioning and QC.
• Collecting facies and petrophysical data to be read for modeling.
• Cross plots to QC porosity data.
• Comparing porosity and facies.
• Permeability calculations from core and porosity data.
• Facies log generation by different methods (Manually, neural network, FMI, and petrel calculator).
• Adjusting seismic cubes to be upscaled in the model.
• Choosing suitable seismic inversion product to be used as weighting input for data distribution.
Spatial Analysis and Modelling
• Univariate statistics
• Bivariate data description
• Data transformations
• Geostatistical analysis
• Spatial analysis and modeling
• Interpolation
• Variograms
Building the 3D Structural Model
• Generate the Fault framework.
• Fault framework while interpreting.
• Boundary definition and Horizon modeling.
• Horizon filtering attribute.
• Refine and create a zone model.
• Troubleshooting.
• Structural gridding.
• Corner Point Gridding.
• Data preparation.
• Modeling of main faults.
• Pillar gridding.
• Make horizons.
• Truncations.
• Data preparation, including well-log edits and calculations as well as log upscaling for discrete and continuous data
Scaling up Well logs
• Scaling up facies logs.
• Averaging methods and their impact on upscaled facies logs.
• Scaling up petro physical logs
• Averaging methods and their impact to upscaled petrophysical logs.
Building the 3D Property Facies Model.
• Deterministic and stochastic facies modeling (object and pixel modeling).
• Developing a conceptual geological model.
• Data analysis.
• Facies probability function and its importance for facies distribution.
• Facies variogram analysis and how it affects its distribution through the model.
• Sequential Indicator Simulation.
• Object Facies Modeling.
• Truncated Gaussian Simulation with and without trends and use for carbonate reservoirs.
• Using secondary data to populate facies models.
• Developing a stratigraphic model
• The use of analogs in model builds
• How to build an accurate facies model and how to provide geological controls on this.
Building the 3D property Petrophysical Model
• Deterministic and stochastic petrophysical modeling
• Data analysis.
• Sequential Gaussian Simulation.
• Gaussian Random Function Simulation.
• Kriging.
• Using secondary data to populate petrophysical models.
• Porosity and water saturation distribution through the model.
• How to weigh water saturation distribution in the model.
• Permeability distribution in the model.
Uncertainty Analysis, Ranking and Upscaling
• Building the final 3D model
• Uncertainty analysis and risk
• The space of uncertainty and pragmatic decisions
• First, second and third order changes to the model
• Multiple realizations
• Developing risk maps
• Ranking and upscaling – passing the model on.
Hydrocarbon in place calculations
• Monte Carlo Hydrocarbon Calculations based on structure contour maps.
• 3D static model hydrocarbon in place calculations.
• Validation of final in place with Monto Carlo assumptions.
• Reservoir dynamic model reserve estimation.
• Decision tree for best drillable locations and number of wells.