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About this book

This book gives practical advice and ready to use tips on the design and construction of subsurface reservoir models. The design elements cover rock architecture, petrophysical property modelling, multi-scale data integration, upscaling and uncertainty analysis. Philip Ringrose and Mark Bentley share their experience, gained from over a hundred reservoir modelling studies in 25 countries covering clastic, carbonate and fractured reservoir types, and for a range of fluid systems – oil, gas and CO2, production and injection, and effects of different mobility ratios. The intimate relationship between geology and fluid flow is explored throughout, showing how the impact of fluid type, displacement mechanism and the subtleties of single- and multi-phase flow combine to influence reservoir model design.

The second edition updates the existing sections and adds sections on the following topics:

· A new chapter on modelling for CO2 storage

· A new chapter on modelling workflows

· An extended chapter on fractured reservoir modelling

· An extended chapter on multi-scale modelling

· An extended chapter on the quantification of uncertainty

· A revised section on the future of modelling based on recently published papers by the authors

The main audience for this book is the community of applied geoscientists and engineers involved in understanding fluid flow in the subsurface: whether for the extraction of oil or gas or the injection of CO2 or the subsurface storage of energy in general. We will always need to understand how fluids move in the subsurface and we will always require skills to model these quantitatively. The second edition of this reference book therefore aims to highlight the modelling skills developed for the current energy industry which will also be required for the energy transition of the future. The book is aimed at technical-professional practitioners in the energy industry and is also suitable for a range of Master’s level courses in reservoir characterisation, modelling and engineering.

• Provides practical advice and guidelines for users of 3D reservoir modelling packages

• Gives advice on reservoir model design for the growing world-wide activity in subsurface reservoir modelling

• Covers rock modelling, property modelling, upscaling, fluid flow and uncertainty handling

• Encompasses clastic, carbonate and fractured reservoirs

• Applies to multi-fluid cases and applications: hydrocarbons and CO2, production and storage; rewritten for use in the Energy Transition.

Table of Contents


1. Model Purpose

Should we aspire to build detailed full-field reservoir models with a view to using those models to answer business questions?
In this chapter it is suggested the answer to the above question is ‘not necessarily’. Instead we argue the case for building for fit-for-purpose models, which may or may not be detailed and may or may not be full-field.
This choice triggers the question: ‘what is our purpose?’ The answer to this question determines the model design.
Philip Ringrose, Mark Bentley

2. The Rock Model

If you can sketch it, you can model it
Many static model practitioners embark on exercises of ‘geological modelling’, attempting to create a digital version of the geology as seen at outcrop. In practice this is futile. Even relatively high resolution models such as that for the Urgonian Shuiba analogue shown in below are clearly unlike the outcrop and close inspection of the outcrop would reveal a huge amount of missing detail.
Fortunately all the detail is rarely, if ever, required and we are saved the daunting task of capturing it all. We are in the business of building model representations: cellular proxies which capture the essence of the underlying complexity, extracting only the detail which is necessary to address commercial questions such as forecasts of resource volumes or fluid flow rates over time. We are building reservoir models rather than geological models and our focus is therefore on achieving a reasonable representation.
Mark Bentley, Philip Ringrose

3. The Property Model

Now let’s say you have a beautiful fit-for-purpose rock model of your reservoir – let’s open the box and find out what’s inside? All too often the properties used within the geo-model are woefully inadequate. What we need are appropriately-scaled property estimates based on statistical analysis of the available data – not just random guesses!
The aim of this chapter is too ensure the properties of your model are also fit-for-purpose and not, like Pandora’s box, full of “all the evils of mankind.”
Eros warned her not to open the box once Persephone’s beauty was inside[…] but as she opened the box Psyche fell unconscious upon the ground. (from The Golden Ass by Apuleius)
Philip Ringrose, Mark Bentley

4. Upscaling Flow Properties

To ‘upscale flow properties’ means to estimate large-scale flow behaviour from smaller-scale measurements. Typically, we start with a few measurements of rock samples (length scale ~3 cm) and some records of flow rates and pressures in well tests (~100’s m). Our challenge is to estimate how the whole reservoir will flow (~1 km).
Flow properties of rocks vary enormously over a wide range of length scales, and estimating upscaled flow properties can be quite a challenge. Unfortunately, many reservoir modellers choose to overlook this problem and blindly hope that a few measurements will correctly represent the whole reservoir.
The aim of this chapter is to help make intelligent estimates of large-scale flow properties and to avoid stupid pitfalls. In the words of Albert Einstein:
Two things are infinite: the universe and human stupidity; and I’m not sure about the universe.
Philip Ringrose, Mark Bentley

5. Model-Based Uncertainty Handling

The preceding chapters have highlighted a number of ways in which a reservoir model can go right or wrong. In terms of the potential impact on a commercial decision, however, nothing compares with the mishandling of uncertainty. An incorrect saturation model, for example, can easily give a volumetric error of 10% or 20%. A flawed geological concept could have a higher impact still. Mishandling of uncertainty, however, can easily result in the whole modelling and simulation effort becoming worthless.
The cause of this may be the misuse of software or misleading data, but the prime reason is more personal: our behaviour and our design choices. Our aim is to stimulate a model design strategy that can overcome data limitations and personal bias and give us a useful way of quantifying model forecast uncertainty.
Mark Bentley, Philip Ringrose

6. Reservoir Model Types

Every reservoir is in some way unique. There are nevertheless generic issues pertinent to certain reservoir types and, in terms of model design, there are issues which inevitably require attention.
We don’t aim to cover all possible reservoir types but we do hope to indicate trains of thought which we have found fruitful in modelling studies. Along the way, we can elicit distinctions between models for clastic and carbonate reservoirs and some courses of action to take if the reservoir turns out to be fractured (which all reservoirs are).
If all reservoirs were just tanks of sand, this task would be trivial. In practice, geology and fluid dynamics combine in complex and intriguing but ultimately understandable ways. Adapting a line from Leo Tolstoy’s Anna Karenina:
Homogeneous reservoirs are all alike; every heterogeneous reservoir is heterogeneous in its own way.
We have chosen to group siliciclastic reservoirs by common depositional settings, namely: aeolian, fluvial, tidal-deltaic, shallow-marine and deep-marine. We then go on to consider carbonate and fractured reservoirs as ‘types’.
In practice, many carbonate reservoir systems contain siliciclastic units, and both sandstone and carbonate reservoirs may be significantly influenced by the presence of faults and joints. The main issue is to identify the key characteristics of the reservoir under consideration as a starting point for the reservoir model design which will be unique to that reservoir.
Mark Bentley, Philip Ringrose

7. Models for Storage

Same rocks – different fluids
What happens if the objective of your model changes dramatically – can the same rock model be applied to multiple dynamic objectives? We have developed the argument that the importance of different scales and types of heterogeneity depends on the flow processes – geomodels for gas depletion are quite different from geomodels purposed for water or gas injection. What about completely different objectives, such as permanent storage of CO2 or seasonal storage of air or hydrogen?
Here we develop the question of how to align the reservoir model design to different objectives, focussing especially on the energy transition for which storage and management of subsurface fluid resources will be as important as fluid extraction. We will focus on the case of CO2 storage, but also draw insights relevant to the seasonal storage of gas, air and hydrogen.
Philip Ringrose, Mark Bentley

8. Modelling Workflows

It ain’t what you do, it’s the way that you do it
There is a tendency in the reservoir modelling community to build detailed, full-field models and the bigger the computer, the bigger the model. Although individual models now run very quickly, the turn-around times for reservoir studies have not necessarily changed over recent decades, despite the huge increases in computing power and the increased sophistication of modelling and simulation software. Often these models are not fit-for-purpose, and the decision at hand could have been made via more efficient routes. We tend, in this sense, to work at a level of maximum inefficiency.
The reason is workflow. In this section we therefore look at alternative workflows which take us away from the ‘default’ of a single detailed full-field model.
Philip Ringrose, Mark Bentley

9. Epilogue – Modelling for the Energy Transition

We will never cease to be interested in how fluids flow in the subsurface.
The same reservoir and simulation technologies which have been developed and honed in the pursuit of oil and gas resources will continue to be required in the future, for a declining production of hydrocarbons, continuing interest in geothermal energy, increasing disposal of CO2 and storage of energy itself. This is in addition to the long-standing needs to manage water, understand earthquakes and predict hydrothermal systems and even volcanic plumbing. All of these require a technical understanding of fluid flow in the subsurface and draw on the skills discussed in this text, and more. Hence we have emphasised in this second edition the use of modelling technologies for carbon storage, an issue of immediate urgency to meet the challenge of managing climate change. Perilous as it is to predict the future, and at the risk of dating this book as soon as it is written, it is worth closing with comments on possible ways ahead. In this last chapter we summarise our current position, draw together some of the developments which may become standard tools in the future and close with a thought on the purpose of modelling itself: understanding.
Philip Ringrose, Mark Bentley


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