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Herausgeber: John Wiley & Sons
Kategorie: Wissenschaft und neue Technologien
Sprache: Englisch

Beschreibung

Petrophysics is the science of evaluating the rock and fluid properties of oil, gas and water reservoirs through the acquisition of physical samples, electrical, chemical, nuclear and magnetic data acquired by surface logging, downhole coring, and drilling and wireline sondes. The evaluation, analysis and interpretation of this data is as much an art as a science as it requires an understanding of geology, chemistry, physics, electronics, mechanics and drilling technology. The techniques have been developed over the last 100 years primarily by the oil and gas industry, but the principles are equally relevant in coal mining, hydrogeology and environmental science.

This book is firmly aimed at students of geology and petroleum engineering looking for a practical understanding of the background and workflows required to complete a petrophysical study of a well, a reservoir or a field. Petrophysics is log analysis constrained by geology, and if we ignore the rocks we risk making poor investment decisions.

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Leseprobe

Cover

Title Page

Dedication Page

Preface

1 Introduction

1.1 The basics

1.2 The results

1.3 Summary

2 Data Acquisition

2.1 Drilling data

2.2 Coring and core analysis

2.3 Wireline logging

2.4 Well test data

2.5 Borehole environment

2.6 Summary

3 Rock and Fluid Properties

3.1 Controls on rock properties

3.2 Lithology

3.3 Porosity

3.4 Water saturation

3.5 Permeability

3.6 Summary

4 Quality Control of Raw Data

4.1 Validation of log data

4.2 Depth merging

4.3 Tool corrections

4.4 Core analysis data

4.5 Merging core and log data

4.6 Converting measured depth to true vertical depth

4.7 Summary

5 Characteristic Log Responses

5.1 Characteristic shale response

5.2 Matrix characteristics

5.3 Fluid characteristics

5.4 Hydrocarbon corrections

5.5 Shale corrections

5.6 Summary

6 Evaluation of Lithology, Porosity and Water Saturation

6.1 Evaluation of lithology

6.2 Evaluation of porosity

6.3 Evaluation of water resistivity

6.4 Estimation of water saturation

6.5 Summary

7 Petrophysical Workflows

7.1 Data management

7.2 Quick-look interpretation

7.3 Full petrophysical interpretation

8 Beyond Log Analysis

8.1 Pressure measurements, gradients and contacts

8.2 Saturation-height functions

8.3 Electrofacies and facies analysis

8.4 Rock typing

8.5 Integration with seismic

8.6 Production logging

8.7 Geo-steering

8.8 Petrophysics of unconventional reservoirs

9 Carbonate Reservoir Evaluation

9.1 Rock fabric classification

9.2 Petrophysical interpretation

10 Petrophysics for Reservoir Modelling

10.1 Multi-scale modelling

10.2 Petrophysical issues

10.3 Blocking logs

10.4 Geological issues

10.5 Engineering issues

10.6 Volumetrics

10.7 Uncertainty

10.8 Epilog

Appendix 1: Petrophysical Report

PRELIMINARY PETROPHYSICAL EVALUATION

Summary

Objectives

Appendix 2: Data Collection and Management

Available input data

Quality

Database

Data types

Appendix 3: Oilfield Glossary

References

Index

End User License Agreement

List of Tables

Chapter 01

Table 1.1 Comparison of different unit systems of measurement.

Table 1.2 Common abbreviations and three-letter acronyms.

Table 1.3 Permeability ranges for different qualitative descriptions of permeability.

Chapter 02

Table 2.1 Common wireline logging tools and acronyms.

Table 2.2 Logging tool depth of investigation and vertical resolution.

Table 2.3 Standard wireline logs scales, units and ranges.

Table 2.4 Logging tool applications and limitations.

Chapter 03

Table 3.1 Typical GR responses seen in commonly occurring rocks and minerals.

Table 3.2 Sonic velocities and interval transit times for different matrix types.

Table 3.3 Matrix density and photoelectric effect values for common lithologies.

Chapter 05

Table 5.1 Common clay types and their characteristics.

Chapter 06

Table 6.1 Typical values of the main lithological determinant logs.

Table 6.2 Discriminant log ranges of shallow marine facies.

Chapter 08

Table 8.1 Typical pressure gradients and fluid densities.

Chapter 09

Table 9.1 Bulk volume water at irreducible water saturation as a function of grain size and type of carbonate porosity (Asquith, 1985).

Appendix 1

Table A1.1 Wiley-7 header information.

Table A1.2 Available wireline log data from Wiley-7.

Table A1.3 Final petrophysical interpretation of the Wiley Formation interval in Wiley-7.

Appendix 2

Table A2.1 Common mnemonics.

Table A2.2 Common CPI mnemonics.

Table A2.3 Common core analysis mnemonics.

Table A2.4 Pressure measurement mnemonics.

Table A2.5 SCAL mnemonics.

List of Illustrations

Chapter 01

Figure 1.1 Petrophysical evaluation: schematic showing the primary data sources, products and deliverables of an integrated petrophysical evaluation.

Figure 1.2 Depth measurement: terminology used to describe the stages and geometry of a well path designed to achieve a number of geological objectives.

Figure 1.3 QFL plot: a standard lithology ternary plot based on the proportions of quartz, feldspar and rock fragments in sandstone.

Figure 1.4 Carbonate pore types: classification of carbonate rock into intergranular and vuggy pore types; comparison of alternative classification schemes.

Figure 1.5 Physics of the reservoir: representation of fluid distribution within an oil reservoir based on the relationship between water saturation, capillary pressure and the free water level datum.

Figure 1.6 (a) Porosity: the relationship between volume of pore space and total volume of rock is a function of grain size, sorting and packing at time of deposition. Post-depositional processes such as compaction and diagenesis can alter the original relationship. (b) Water saturation: the proportion of the total reservoir pore volume filled with water: the remaining pore volume is filled with oil or gas, not necessarily hydrocarbon gas. (c) Permeability: the ability of a reservoir to conduct fluids through an interconnected pore network.

Figure 1.7 Capillary pressure (

) and wettability: (a) representation of a liquid-filled capillary tube and the relationship between the buoyancy pressure generated between two immiscible fluids; (b) the difference between wetting and non-wetting liquids as a function of the surface tension and contact angle.

Figure 1.8 Net to gross: terminology used to describe the proportions of an oil or gas reservoir in terms the different interval thicknesses.

Figure 1.9 Volume of HIIP: schematic to show the calculation of the volume of hydrocarbons in place in an oil or gas reservoir; to estimate potential resources it is necessary to apply the appropriate conversion factor from reservoir volume to surface volume, the formation volume factor.

Chapter 02

Figure 2.1 An example of a mudlog showing rate of penetration and drilling parameters in the first column, cuttings percentages and depth in columns 2 and 3, total gas in column 4 and the drilling exponent related to formation pressure in column 5.

Figure 2.2 Schematic diagram of a coring assembly and barrel prior to retrieval.

Figure 2.3 Schematic diagram of a typical set-up for running wireline logs. The logging unit, either a truck or Portakabin offshore, contains the surface control and data recording equipment. Set-up can take a few hours after the drillstring is retrieved.

Figure 2.4 The pressure gradients that are to be expected in the subsurface as a well is drilled. The formation pressure lies generally between the hydrostatic and lithostatic gradients.

Figure 2.5 A representation of the zones of invasion around a vertical borehole and the resulting resistivity profile.

Figure 2.6 The effect of time and permeability on the drilling mud invasion profile.

Figure 2.7 Different geothermal gradients showing increasing temperature with depth, with the zone of typical oilfield temperatures indicated.

Chapter 03

Figure 3.1 The representative elementary volume (REV) and scales of investigation and measurement in heterogeneous and homogeneous media.

Figure 3.2 (a) The impact of grain size, sorting and packing on porosity in typical clastic rocks. (b) Typical visual estimation of degrees of sorting in sandstones.

Figure 3.3 Examples of petrographic thin sections and SEM images: porosity is stained blue.

Figure 3.4 The SP (spontaneous potential) log, the simplest of all electrical measurements made in a borehole.

Figure 3.5 Gamma ray logging measurements of both the normal and spectral gamma tools.

Figure 3.6 Typical gamma ray or SP log profiles and the descriptive terms in use since the 1950s to infer the environment of deposition.

Figure 3.7 Types of porosity seen in thin section and typical porosity ranges found in different potential reservoirs.

Figure 3.8 The borehole-compensated sonic tool: mode of operation, applications and typical display.

Figure 3.9 The formation density tool: mode of operation, applications and typical display.

Figure 3.10 The compensated neutron porosity tool: mode of operation, applications and typical display.

Figure 3.11 The nuclear magnetic resonance tool: principles of operation and typical display.

Figure 3.12 (a) Capillary pressure curves representing the effect of different pore-size distributions on fluid saturation. (b) The impact of wettability on saturation distribution with height above the free water level.

Figure 3.13 Formation resistivity factor (

): the principle of estimation and experimental determination. Plotting the results of each measurement determines a slope

that relates

to porosity, known as the cementation exponent.

Figure 3.14 The resistivity index relates the proportion of a saturating fluid to the resistivity of a non-conductive fluid.

Figure 3.15 Resistivity log response in sandstone of constant porosity varying with formation water resistivity or hydrocarbon content.

Figure 3.16 Different resistivity tools: laterologs and induction logs; modes of operation, application and typical displays.

Figure 3.17 Experimental method to determine flow of water through a sand pack recreating the original Darcy experiments.

Figure 3.18 Example of a porosity–permeability cross-plot with a single linear

-on-

relationship described. The data distribution suggests that more than one lithofacies may be grouped together: try to partition the data to reflect geology.

Chapter 04

Figure 4.1 Example of an LAS well file header showing the basic well information such as location and tools run. This example is of a composite suite of data for a complete well after well editing.

Figure 4.2 Example of a conventional core analysis data sheet. The Comments column may give clues to the quality of a particular measurement.

Chapter 05

Figure 5.1 Schematic representation of the impact of different clay types on permeability in a clastic reservoir.

Figure 5.2 (a) Different clay types based on the Thomas–Stieber classification; (b) examples of different clays under SEM; pore-lining and grain-coating examples are seen.

Figure 5.3 Histogram of gamma ray response in a well showing a bimodal distribution reflecting the two populations of sandstones and shales. This display can be used to identify the clean sand and shale responses for calculation of shale volume.

Figure 5.4 A neutron–density cross-plot scaled to identify the sandstone, shale and fluid points of interbedded, water-filled sequences.

Chapter 06

Figure 6.1 Simplified lithology determination from gamma, neutron–density and PEF logs.

Figure 6.2 Identifying the point of inflection of a suite of wireline logs to determine bed boundaries.

Figure 6.3 Example of M–N lithology plot, where M represents a normalized relationship of the sonic and bulk density and N represents a normalized relationship between bulk density and neutron porosity. This plot is used to identify different minerals and lithologies.

Figure 6.4 Example of a neutron–density cross-plot and interpretation overlay for the appropriate version and supplier of the tool. The cross-plot is used to estimate porosity for a given lithology.

Figure 6.5 Examples of different types of scatter plots used to establish relevant shale points and tool response to different lithologies. (a) Sonic versus gamma ray scatter plot used to estimate sonic response to sand and shale. (b) Comparison of sand and shale response to sonic and bulk density; presence of coal also picked out. (c) Scatter plot of raw sonic against neutron porosity used to compare variations to lithology response.

Figure 6.6 Log analysis gives total porosity including that associated with clay-bound water. Core analysis may also give total porosity depending on the cleaning and drying methods applied. For volumetric calculations we need effective properties.

Figure 6.7 Example of a cross-plot of deep and shallow reading resistivity tools used to establish the formation water resistivity when the resistivity of the mud filtrate is known. The slope of the line gives

Figure 6.8 Example of a Pickett plot used to establish the value of formation water resistivity when the Archie parameters

and

are known.

Figure 6.9 Process diagram used to calculate water saturation using the Archie equation for clean sands.

Figure 6.10 Model of clay bound water and the distribution of exchangeable cations on a clay surface; the greater the number of exchangeable cations, the greater the CEC and the greater the surface conductance of the clay.

Chapter 07

Figure 7.1 Simple computer-processed interpretation (CPI) of a suite of wireline logs: primary input logs in columns 1–4 and

estimation in column 5 with the distribution of shale, matrix, porosity and BVW in column 6.

Figure 7.2 Cross-plot showing overburden-corrected porosity against formation density from wireline data, used to determine fluid density and matrix or grain density.

Figure 7.3 Porosity–permeability cross-plot of core data partitioned by rock types. Although a single straight-line relationship is shown, each rock type may have its own predictive relationship.

Figure 7.4 Net-to-gross calculation using

, porosity and

as potential cut-offs to distinguish net reservoir, net sand and net pay.

Chapter 08

Figure 8.1 Different formation pressure gradients with increasing depth.

Figure 8.2 Schematic diagram of a well formation pressure-testing tool.

Figure 8.3 Change in formation pressure as a function of depth and reservoir fluid.

Figure 8.4 Conversion of laboratory capillary pressure data to reservoir conditions.

Figure 8.5 Relationship between capillary pressure, height and permeability, demonstrating the impact of rock type on water saturation.

Figure 8.6 A deterministic distribution of lithological components and interpretation of results using the Petra algorithm in TerraStation.

Figure 8.7 Process diagram to establish a well-to-seismic correlation.

Figure 8.8 Components of source rocks and non-source rocks and the four types of porosity found in shale rocks.

Figure 8.9 Typical log responses to different source rocks.

Figure 8.10 Graph of TOC against Δlog

to estimate levels of maturity (LOMs) of shale source rocks.

Chapter 09

Figure 9.1 Carbonate rock type classification based on Lucia (1999). The example shown is from a non-vuggy dolomitic limestone and important displacement pressure boundaries are be established at 20 and 100 μm pore-throat sizes that define three separate permeability fields.

Chapter 10

Figure 10.1 Scales of measurement from core data, through log, seismic and well test, to demonstrate the approximately 13 orders of magnitude difference between the different sources.

Figure 10.2 Porosity distribution: mapped, interpolated and stochastically distributed showing the increasing heterogeneity in the property.

Figure 10.3 Facies-constrained porosity distribution. (a) The interpolated porosity model honours the well data but results in a smooth distribution between the wells; (b, c) a simple threefold scheme of channel, overbank and floodplain facies allows the porosity seen in the wells to be distributed meaningfully, capturing the rapid changes laterally in the model.

Figure 10.4 Volumes and uncertainty: the percentage change in STOIIP dependent on different petrophysical parameters. The greatest difference comes from the measurement of GRV, due in part to the uncertainty in depth conversion.

Appendix 1

Figure A1.1 Composite log over the Wiley Formation interval in Wiley-7.

Figure A1.2 Gamma ray histogram plot for Wiley Formation interval in Wiley-7.

Figure A1.3 CPI of Wiley Formation interval in Wiley-7.

Guide

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Petrophysics:A Practical Guide

Steve Cannon

Registered OfficeJohn Wiley & Sons, Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK

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Library of Congress Cataloging-in-Publication Data

Cannon, Steve, 1955–Petrophysics : a practical guide / by Steve Cannon. pages cm Includes bibliographical references and index.

ISBN 978-1-118-74674-5 (hardback) – ISBN 978-1-118-74673-8 (paper)1. Petroleum–Geology. 2. Physical geology. 3. Geophysics. I. Title. TN870.5.C328 2015 553.2′8–dc23

2015022538

A catalogue record for this book is available from the British Library.

Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books.

Cover image: An arbitrary cross section through a three dimensional porosity model of a reservoir built in Petrel (Schlumberger™) © Steve Cannon

Dedication

For Janet, as ever

Preface

This book has been written for those studying petroleum geology or engineering, for whom the role of the petrophysicist can become a lucrative and satisfying career. The handbook will be equally useful to students and practioners of environmental science and hydrogeology, where the understanding of groundwater flow is an important part of their technical remit. There is a comprehensive reference list included in the handbook that will cover some of the historic developments in petrophysics over the last 70 years; the book could bear the subtitle ‘from Archie to anisotropy’ and still include all the basic ideas captured in its pages. The handbook is subtitled ‘a practical guide’, and that is what I have set out to try and do: look at the pitfalls and obstructions encountered in any reservoir evaluation study and suggest alternative solutions and works-around.

It has also been developed in response to the needs of many younger colleagues who have not yet had the opportunities and experiences of an older generation of petroleum geologists and engineers. Most experienced petrophysicists in the industry have developed their own routines and preferred solutions to specific interpretation problems, and some of these different ideas will be reviewed for specific types of reservoir and the fluids they contain. Specialist petrophysicists and log analysts steeped in the details of wireline tool physics can sometimes lose the essential requirement of an interpretation, which is to provide usable input for some other static or dynamic model of a hydrocarbon reservoir.

I will quote one anecdote that may help explain what I mean. When learning how to use a new piece of log analysis software, I was afforded the opportunity by a colleague working for an oil company to test the software on a complete suite of wireline logs supported by core and sedimentological data, including XRD and SEM analysis. I had every tool then known to mankind available to employ on the usual problem of establishing porosity and water saturation in a well. I ran the log analysis software; the state-of-the-art software that used elemental analysis combined with a stochastic interpretation to generate the required results. My simple first-pass results were adequate, but no better than the previous deterministic solution I had generated. I was able to call upon the assistance of an expert log analyst in the service company with 20 years of experience in this field. I showed him the input data, the logs, the core analysis, XRD, etc., and my initial results; he felt that we could do better. After a couple of initial runs he said, ‘I think I will relax the neutron a little’, and my sandstone reservoir became a limestone; my comment was, ‘it’s a good job we have the core data; at least we know it is supposed to be sandstone!’. This was a life-changing event! I learnt that it is not enough to quality control the input data, you must quality control the output and make sure the results are sensible; often less experienced users of software solutions do not appreciate what the results should look like.

Until the 1980s, there were very few petrophysicists outside the oil company research laboratory: there were log analysts, core analysts, geologists and petroleum engineers, all of whom dabbled in the interpretation of wireline and core data. Log analysts had generally worked as field engineers with one of the many service companies, often being graduates in physics and electronics and thus well grounded in tool physics and data acquisition. It was with the development of computer-processed interpretations that log analysis became a tool of the many: often geologists with the basic knowledge to run the software but not always the experience to recognize bad data, the classic garbage-in, garbage-out syndrome.

There are also many oilfield service companies that provide wireline and/or LWD services from acquisition, through processing to interpretation. The biggest international companies are Baker Hughes, Halliburton, Schlumberger and Weatherford, and all provide services used in the evaluation of reservoirs; there are many other smaller and local companies that provide similar services. Throughout the book I have tried not to be biased towards one company or another; however, this is not always easy as some products or tools become associated with one or other company – my apologies should I appear to favour one organization over another, this is unintentional.

In writing this practical guide, I have started with the basic data acquisition and quality control of log and core data before moving into the actual interpretation workflow. Before starting an interpretation, however, it is crucial to establish a consistent database, and I give some suggestions on how this may be done, albeit this stage is often software dependent. The interpretation workflow follows a widely accepted series of steps from shale volume estimation, through porosity determination and finishes with the evaluation of water saturation. At each step I have presented a number of methods or techniques that may be selected depending on the available input data; these are not the only solutions, only the most common or simplest, so readers are invited to develop their own solutions for their own reservoirs. I have also tried to cover some of the more specialist log interpretation methods and their applications in reservoir characterization, especially how petrophysics links seismic data through a geological model to the dynamic world of reservoir simulation.

There are many people who have helped and guided me through my career, many no longer with us, so to them all I say, ‘thank you’. I especially want to thank Roman Bobolecki, Andy Brickell, John Doveton, Jeff Hook, Mike Lovell, Dick Woodhouse and Paul Worthington, all proper petrophysicists! Finally, my thanks go to Andy Jagger and Nigel Collins of Terrasciences, who have supported me in many ways over the last 25 years, not least in providing a copy of T-Log for my use while writing this book.

Steve Cannon

1Introduction

What is petrophysics? Petrophysics, as understood in the oil and gas industry, is the characterization and interaction of the rock and fluid properties of reservoirs and non-reservoirs:

determining the nature of an interconnected network of pore spaces –

porosity

;

the distribution of oil, water and gas in the pore spaces –

water saturation

; and

the potential for the fluids to flow through the network –

permeability

Petrophysical interpretation is fundamental to the much of the work on the subsurface carried out by geologists, geophysicists and reservoir engineers and drillers. To characterize the subsurface successfully requires physical samples, electrical, chemical, nuclear and magnetic measurements made through surface logging, coring and drilling and wireline tools (sondes). Terms such as ‘formation evaluation’ and ‘log analysis’ are often used to capture specific parts of the petrophysical workflow, but should not be seen as synonyms. ‘Rock physics’, which sounds as though it might be similar, is usually reserved for the study of the seismic properties of a reservoir; similar concepts apply but at larger scale.

The evaluation, analysis and interpretation of these petrophysical data is as much an art as a science, as it requires an understanding of geology, chemistry, physics, electronics, mechanics and drilling technology. At its simplest, petrophysics determines the porosity and water saturation of a reservoir, then estimates the permeability of the rock and the mobility of the fluids in place. The interpretation is dependent on the lithology of the rocks being evaluated, as sandstone, limestone, shale and any other potential hydrocarbon-bearing rocks all have differing characteristics. The acquisition and interpretation techniques applied in formation evaluation have been developed over the last century primarily by the oil and gas industry, but the principles are equally relevant in coal mining, hydrogeology and environmental science. The type of data acquired is generic and can be used in a number of different analytical ways; indeed, as computing power and microelectronics have developed over the last 30 years, more high-resolution data can be collected and used for ever more detailed interpretation. However, measurements can be influenced by a number of variables, including the borehole environment; borehole diameter, temperature, pressure and drilling fluid, all affect the quality and type of data acquired. The reservoir rocks and the fluids therein can further affect the data quality and interpretation – a virtuous or viscous circle depending on how you look at it.

This book can be divided into two sections: first data acquisition and second interpretations, applications and workflow. This introductory chapter reviews the basics of petrophysics, including the confusing topics of measurement units, reservoir lithology, basic measurements and how the results may be used and the value of information and data management.

Chapter 2

reviews data acquisition in some detail, from drilling data to core analysis and wireline logs. I have not tried to give a detailed description of wireline tool technology, because I am not a physicist or electronics engineer; I refer you to the appropriate manufacturers’ publications. In an

appendix I

have tried to collect basic tool information, but I would direct you to the third edition of The Geological Interpretation of Well Logs (Rider and Kennedy, 2011) for a full description and discussion of the range of logging tools available.

Chapter 3

discusses rock and fluid properties and what controls porosity, water saturation and permeability in the reservoir. Each property is defined and described and how the measurements are made, with a discussion of uncertainty.

Chapter 4

is focused on data quality control, especially the validation of log data and the integration with core data.

Chapter 5

looks at the characteristic response of different logs to reservoir rocks and fluids and how the data may be used in log analysis. The response to shales and matrix and fluid properties are fundamental.

Chapter 6

is about the evaluation of porosity and formation water resistivity and estimation of water saturation.

Chapter 7

looks at different petrophysical workflows, starting with data management and then quick-look single-well analyses, followed by multi-well studies. This part of the process is supported by worked examples.

Chapter 8

is called ‘beyond log analysis’ and looks at permeability estimation, cut-offs and zone averages, saturation height relationships, pressure measurements and fluid contacts. There is also a discussion of lithology prediction, facies analysis and rock typing and also integration with seismic data.

Chapter 9

looks at carbonate reservoir characterization.

Chapter 10

describes the role of petrophysics in reservoir modelling, with a particular emphasis on property modelling in three dimensions.

One outcome of a petrophysical analysis forms the basis of the estimation of fluids in place, upon which, together with the gross rock volume of a reservoir, major investment decisions are made by oil and gas companies: the quality of the interpretation will change with time as new wells and new data are collected, so there is a need for consistency in approach at all times. One aspect that should never be forgotten is that most of the measurements that are made are a proxy for the real property that we are trying evaluate: porosity is never actually measured but interpreted from a density or neutron log; water saturation is interpreted from a resistivity measurement, dependent on the analyst knowing some fundamental properties of the formation fluid. A petrophysicist therefore has to be a general scientist with a strong numerical bias to be able to cut through the complex analytical methods and uncertainties inherent in the process of evaluating a reservoir; above all, a petrophysicist must be imaginative and thorough in their analysis and be flexible in their attitude to an interpretation that will change over time through either additional data or greater insight.

Beyond volumetric estimation, petrophysics is at the core of many other subsurface disciplines: the geophysicist relies on correctly edited and calibrated logs for depth conversion and rock property analysis, likewise the geologist for well correlation, reservoir modelling and fluid contact estimation, and the engineers for well completions and pressure prediction and as input for dynamic simulation. How you approach a petrophysical data set will often depend on the objective of the study: a single-well log analysis without core data requires a very different workflow to that adopted for a full-field petrophysical review.

Petrophysics is not just log analysis – it is log analysis within a geological context or framework, supported by adequate calibration data, including sedimentology, core analysis and dynamic data from pressure measurements and well tests (Figure 1.1). Logs do not measure porosity, permeability or water saturation; they make measurements of acoustic velocity, electrical conductivity and various nuclear relationships between the rock and the fluids to allow computer programs to process and interpret the results. The petrophysicist role is to validate and organize the input data and to understand and calibrate the results. A little harsh, you may say, but how many petrophysicists do the job without using log analysis software and how many integrate the analysis with the geological interpretation?

Figure 1.1 Petrophysical evaluation: schematic showing the primary data sources, products and deliverables of an integrated petrophysical evaluation.

1.1 The basics

It is worthwhile looking at the context in which the rest of the book lies before diving into the detail. Although not attempting to be a primer in geology, physics or chemistry, we will touch on these disciplines as we progress, so I will try to set the scene and leave the reader to dig deeper into interesting subject matter from the references. However, it is worth considering that both of our primary sources of data, wireline/LWD (logging while drilling) and core data, present challenges in terms of sampling, data quality and integration. Log measurements, although made in situ, are invariably indirect; we seldom measure an actual property of the rock, only one inferred from its response to physical input: core measurements are broadly speaking direct but they are ex situ. It is not my intention to describe in any detail the tool physics behind logging measurements, as there are many other books that cover this vital part of the technology; rather, this handbook is designed for the user of these data to evaluate the potential commercial value of a hydrocarbon reservoir.

All the log measurements that are made come from one or more penetrations of a reservoir made by a drill bit usually between 6 and 12½ inches in diameter, attached to a drill-string often several thousands of feet or metres long; we use this penetration to infer reservoir properties tens to thousands of metres away from the borehole (Figure 1.2). The borehole environment at depth is hostile; it can be hot enough to bake the sensitive electronics in the tools or be at pressures that result in the drilling mud being forced into the borehole wall (invasion) such that all the tool measures is a man-made fluid consisting of minerals and chemicals, which renders the results invalid or at best questionable. Even core measurements are made on material that has undergone physical change since it was cut; without careful handling, the change in confining pressure from reservoir to laboratory conditions will affect the pore volume and in-place fluids and even then measurement corrections are normally required to calibrate the results. Drillers, who generally do not like coring because of slow progress, have been heard to say that the only thing you know about a core once it has been cut is ‘where it has come from, possibly’!

Figure 1.2 Depth measurement: terminology used to describe the stages and geometry of a well path designed to achieve a number of geological objectives.

1.1.1 Units and abbreviations

The oil and gas industry can seem very confusing to the modern scientist brought up in the world of Système International (SI) units, because in general the industry uses either a mixed metric and ‘imperial’ unit system or ‘field units’ as the norm (Table 1.1).

Table 1.1 Comparison of different unit systems of measurement.

Measurement

SI units

Metric/imperial units

Field units

Abbreviation

Length/distance

Metre (m)

Metre/foot

m/ft

Mass

Kilogram (kg)

Kilogram/pound

Pound

kg/lb

Time

Second (s)

Second

Temperature

Kelvin (K)

Centigrade

Fahrenheit

°C/°F

Amount of substance

Mole (mol)

Mole

Parts per million

mol/ppm

Pressure

–

Pascal/bar

Pounds per square inch

Pa/bar

Volume

–

Cubic metre/barrel

Barrel

/bbl

Area

–

Hectare/acre

Acre

ha/ac

The industry is also the home of more abbreviations and TLAs (three-letter acronyms) than probably any other, apart from the medical professions. There is a ‘complete’ glossary as an appendix; however, those given in Table 1.2 are some of the more pertinent for use in petrophysics.

Table 1.2 Common abbreviations and three-letter acronyms.

Abbreviation

Meaning

Application

API

American Institute of Petroleum

Measure of gamma-ray activity; oil density

Archie exponent of tortuosity

Used in calculation of FRF and

BHA

Bottom hole assembly

Drill-string from bit to top of drill collars