2. INTRODUCTION.................................................................................................................... 3
RISK EVALUATION.............................................................................................................. 3
RISK ASSESSMENT IN E&P PROJECTS APART FROM FACTS. ........... 4
INTEGRATED GEOLOGICAL DATA MANAGEMENT, ANALYSIS &
VISUALIZATION ................................................................................................................... 5
TASK DESCRIPTION ............................................................................................................ 5
PROCESS FLOW – MANAGEMENT OF SCIENCE......................................................... 7
BASIN MODELING AS PART OF INVERSION – OR INVERSION PART OF BASIN MODELING ?....... 9
HYDROCARBON CHARGE ...................................................................................................... 10
BASIN MODELLING ESSENTIAL TO PROSPECT/ PLAY MODEL ANALYSIS.................................. 10
WHAT IF WELL DATA ARE PRESENT? ..................................................................................... 11
WHAT TYPE OF WELL DATA CAN WE USE FOR CALIBRATION?................................................ 12
ARE THERE ANY OTHER GEOCHEMICAL DATA WE CAN USE IN BASIN MODELING? ............ 13
TIMING OF HYDROCARBON GENERATION ............................................................................. 13
TWO DIMENSIONAL BASIN MODELLING................................................................................ 14
MAKING MODELS MATTER............................................................................................ 15
THE 4D BUSINESS OPPORTUNITY................................................................................. 18
4D TECHNOLOGY IS EXPECTED TO IMPROVE RECOVERY OF RESERVOIRS OF ALL TYPES....... 18
4D CREATES ADDED VALUE FORM EXISTING 3D SEISMIC DATA.......................................... 20
Appendix 1: Playmodel overview
Appendix 2: Playmodels and risk overview and associated
G&G studies
3. Introduction
During my 15 + years of experience within the oil and gas industry, several regimes
of risk evaluation have been found to exist within the industry. However a few
elements are found to be co-existent in all companies. Reservoir, trap and
hydrocarbon risk has found to be main elements subject to risking. The different
companies put more effort into reservoir risking vs others more into trap or
hydrocarbon risking. Elliminating these smaller differences, one can find that
understandment of geological processes influence the amount of risk one puts into
either of these three elements. What risk factor is more critical than the other, is like
discussing the egg and the chicken, but one finds that the factors are all dependant
upon each other, but the first geological process to start up, is developement of
reservoir and non-reservoir sections, as well as organic matters. Structuring together
with basin subsidence, then creates potential for hydrocarbon generation and
migration into any potential structural, semi-structural or stratigraphic traps found in a
basin.
Being able to explain to why a well was drilled dry or successfull is a very important
knowledge. Many companies do not have time to dwell over well results for too long,
before they have to go on further into another area or other parts of the basin for the
search of hydrocarbons. The more subtile the trap is, the more work is needed for
understandment of the dynamics around a prospect and its drilled well.
This short note will walk through the main elements in workprocess within a E&P
project an try to point out some of the risk factors involved in these process steps. I
will also try to poiint out where Ødegaards products and services can help aid the
E&P companies need for risk assessment understanding. I have also tried to look
into the factors of non-fact risks within the E&P business.
My main message will be to understand where risks are involved and what products
and services fit into the workflow, and where they can assist in reducing the risks of
E&P business.
RISK EVALUATION
Risk evaluation is always talking about G&G assesments of reservoir, trap and
hydrocarbon, their presence or absence. But an equally important aspect of risk
assessment, is data management and resource availability.
Then yet another factor comes into play, and that is the visualization part of this,
where the data management and resource aspect has to be considered.
Which factor is most important? I would not state any of these as more important
than another, since any of these factors will have varying degree of significance,
depending upon your organization.
Some organizations have good data management, but has no way to visulize the
data, and others the quite opposite way. Yet, others have not resources to perform
any work on the data they have inhouse.
4. There is always a balance between amount of data and resources available to use
them. Part of the clue, is to organize the data in such a way that the data easily can
be transformed into knowledge as soon as possible.
This key word that has struck into the E&P industry as a buzz word, is transform
data into knowledge.
But how to do it, seems to be each companies struggle – and all have their own
solutions to this question.
Which one is right? Well, one could measure on amounts of discoveries, amount of
oil and gas resources available, or how it changes by the years… Any way you
measure it – workflow of how you assess an area, before, during and after drilling an
exploration and/ or production well is crucial for the company.
Note, the after aspect of this. Lots of companies makes a final well report, make a
short statement of result, and leave it by that. What went wrong and for what
reasons? These questions are equally important as to where to drill that well. When
one makes a discovery, the companies launches large efforts to find the size of
discovery, and prepare to develop the discovery further.
Utilize the database and make shure your data is up to date, so one can make
strategic decisions for future actions in regions, is very important. Therefor the
accessability of the data, and the flexibility in how you can use, combine and analyze
the data is equally important.
Ideally a shared earth model is the answer. But, then dependant upon who you talk
to, you will get different answers to what should be emphazised in a model like this.
A geoscientist has his views, an engineer has others, and so on. Even within each of
these groups you will find different focuses.
The answer is to integrate all possible parameters, and make shure one understands
the dependability of these parameters, and what methodology one can utilize in order
to understand that parameter, and how it vary.
RISK ASSESSMENT IN E&P PROJECTS APART FROM FACTS.
1. DATA MANAGEMENT
a. Shared Earth model database
b. Tight zones within organization
2. VISUALIZATION CAPABILITY
a. Hardware
b. Software
c. Integration
3. AVAILABLE RESOURCES
a. Amount of people
b. Skill of people
c. Integration of skilled complementary people
5. Integrated Geological Data Management, Analysis &
Visualization
Integration of various toolboxes to solve matters in hand, seems to be the key
element in E&P business.
Inversion has been seen as a special study, which one performs on top of all other
tasks performed.
Inversion has also traditionally been seen as a geophysical domain, hence the
geophysicists has performed the analysis of the data as well. Then the geologists
have used the analysis for support to their geomodels or other models made.
Even the interpreters have not been using the inversion results properly. They
traditionally have been performing the interpretation on ordinary amplitude data or
other amplitude derived attribute data.
I strongly believe that inversion results (impedance, PR, Q, Hilberts etc) should be
made more accesible to the interpreters and geologists.
Therefor a critical workthrough of the value chain within E&P is important in order to
understand where inversion and geophysical well log analysis as well as lithology
cube together with Lithann can be performed.
In addition it is very important to evaluate where other tools can help verify our
producs results, and try to integrate or at least make it possible for the clients to
evaluate the need to performed other studies.
The below list of tasks is not complete by no means, but exemplfies the workflow
items within E&P.
Task Description
Overview of area
o GIS systems or graphic packages to illustrate data as well as results
Data collection and systematization
o Database systems and accesability systems
Point Mapping of data
o Simple GIS system eqvivalents
Multivariate Symbol Maps for overview of data
o As above
Interpretation of leads, play models, prospects and fields
o Various interpretation/ visualization software, seq strat
Geological analysis tools
o Stratigraphic analysis software, fence diagrams, log analysis, seq strat
Contour Maps of data
o Mapping softeware combined with gridding utility and visualization
3-D Surface Diagrams of key data values for E&P work
6. o As above.
Land Grid Utilities / GIS analysis
o As above
Surveying Utilities / Aqusition of seismic data
o Programs for planning surveys, raytracing, modelling tools.
Gridding Tools for mapping of surfaces – play models, prospects
o Mapping software combined with gridding utility and visualization
Solid Modeling – reservoir parameters for input to risk analysis (Monte Carlo)
o Modelling tools such as RMS, Petrel and GeoProbe.
Volumetrics – with probability – Monte Carlo
o Mapping softeware combined with risk analysis and probability tools
Stratigraphic Diagrams – Well log analysis as well as correlation
o Stratigraphic analysis software, fence diagrams
Statistics – Variations within reservoir params as well as volums
o Geomodelling toolboxes with stochastic modelling possibilities
Lineation Analysis – Trend analysis of POR-Depth f.inst.
o Several different tools
Planar Feature Analysis - Fault analysis etc
o Special software for fault seal analysis combined with coherence
Geotechnical – Mechanical destruction/ build up of zones.
o Special software
Geochemistry - Combined with Basin Modelling for HC charge
Conversions – Unit conversions
Geological Tools – Various geological analysis of wells, seismic etc.
o Stratigraphic correlations, analysis, calibrations
Advanced 3-D Visualization – Integration of data in caves etc.
o Mostly inhouse caves with geoprobe, voxelvision, geocap etc etc.
Graphic Utilities – Various presentation packages combined with visualization
o As above
Data Management – Construction and maintanance of raw and refined data
o Openworks, Geoframe and its alike.
Help & Tutorials – Help systems to guide G&G personel in workflow for E&P
work
Import/Export Options – Various programs have import/ export functionality
and limitations. These systems are dynamically changed.
These tasks describe the workflow as G&G experts has to work through a play model
assement into prospect evaluation, and finally into a field evalution. Some tasks are
repetitive, and some tasks interact more with each other than others do.
The main point from this exercise is that the sooner we get into the value chain with
our products and clearly can demonstrate value added for the evaluation teams, the
better.
We clearly has demonstrated the technology, next step is to prove value added in
several steps within the value chain.
Another main hurdle to get over, is to find the break-even in interaction with the client,
offsite, onsite and a mix between the two. It is seen as a clear wish to have our
7. people in the offices of the clients, when it does not make the other team players to
suffer timewise, competence wise etc.
We can certainly help insteps such as data management (wells, seismic, geophysical
analysis etc), but there is also an added potential in visualizing the data, and to lower
the turnaround time for analysis of the data. In this step the integration of data comes
in. The workflow of analysis of data requires a shared earth model, but in 90% + of
the cases, this has not been obtained in any project, wether its exploration nor
production projects.
Therefor we should strive for workflow analysis – and how to optimize the workflow
and put added value on top of this.
It is clearly a matter of having an open environment in our systems, but also making
shure we can interact with major systems working around us (Landmark, Eclipse etc).
Process Flow – Management of Science
To point out the particual step where inversion could play a role, or where we can
interact with other software vendors, it is important to visualize the workflow or
managment system of G&G science. This enables us to find the critical processs
where we should adress our work and software suite. Being supported or suporting
other studies could play an important part when trying to convince the decision
makers in the Science Management. These people as others, need arguments to
why studies should be performed and what it demands of them with respect to
personell amount – skills etc. It also will clarify to our customers in what extent they
are ready to perform studies of the sorts we offer. In what state is their database – do
they have the needed data – have they got the needed overview of the area etc?
The figure below will illustrate the main processes in E&P work, and decision points.
The figure does not explain all work tpoics involved in the processes, but will give a
basis for further discussion and clarification of these processes. The processes are
more or like each other regardless of countries and fiscal regimes, but some
variations will aply where the shelf is more mature with respect to business models
than others.
8. PROCESSES G&G WORK
Data Mining/
regional Study
Play Models
evaluation
Prospect
Evaluation
Drilling
Post Mortem
Drilling
Field Evaluation
No Drilling
Partial
Relinquishment
Relinquish
acreage
Wells
Basin Modelling
Regional studies
Grav Mag, 2D seismic
Mapping – Trap integrity
Horizon mapping, Corr – seis
facies, seq / seis strat, 2D seismic
Attributes – Classifications
Horizons – Constrain prospect
Facies analysis
Geomodel, 3D seismic ?
Report to
authorities
Production and
IOR
Site Survey, Geosteering
Visualization,. Well analysis
Final Well Report
Well planning, seq strat, reservoar
stuies
Field reports, reservoir simulations,
geological models,
Reservoir simulations – revisions
together with geological models,
well analysis, well planning, tests,
production, redetermination
Tail-end
Production
Relinquish
Acreage
Reservoir simulations – revisions
together with geological models,
well analysis, well planning, tests,
production, redetermination, farm-
in/out
Reservoir simulations – revisions
together with geological models,
well analysis, well planning, tests,
production, redetermination, farm-
in/out
9. Exploration phase
If we look closer to the first 3 steps in the flow chart, we are in the Exploration phase
of the E&P business, we also define the 4th step as exploration, but the transition
into production comes more and more evident from this step and further down into
the workflow process diagram.
We will consentrate on the first 3 steps in the next chapter, called Basin Hydrocarbon
Charge risk. In this phase, the companies are faced with a contradiction, one wnats
to find hydrocarbons of significant amounts, but at the same time for as little money
as possible. The $/bbl in exploration cost is less that 5 USD in the major oil
companies, and continue to shrink. Technology together with smarter ways of using
data integration shall help the companies to lower this cost.
It is therefor imperative that we can demonstrate that usage of inversion at this stage
will save the companies money when evaluating the cost pr bbl in exploration, as well
as increasing the discovery rate of exploration wells in the basins they explore for oil
and gas resources.
The most critical element in any explorationis risk of no hydrocarbons present in the
defined trap. No use of trap – if no hydrocarbons migrated up into the trap itself.
Several misses both in the NCS and UK illustrate lack of understanding for
hydrocarbon migration pathways.
Basin Hydrocarbon Charge Risk
There are three risks that must be addressed prior to drilling a well: trap (incl seal), reservoir, and
hydrocarbon charge. These three components must be in-place for an exploration, or production well
to be successful.
Assessing the trap and reservoir risks are routine tasks in all hydrocarbon exploration companies.
Seismic, well, and outcrop data provide an abundance of information that explorationists use to
determine the quality and viability of these two constituents. However reservoir distribution and quality
variations are less examined than trap risks.
Assessing the hydrocarbon charge risk, however, is not a routine in all oil companies. This important
function is usually limited to a few geologists or a special group.The reason for the oversight of such
an important part of the puzzle is two-fold: terminology and an understanding of the science.
Geologists, have all taken courses in structure, stratigraphy, and petrology. These courses qualify
them to make an informed judgment about the trapping configurations and the reservoirs that may be
found in a basin. However, not many have taken courses in organic geochemistry, rock and fluid
dynamics, and thermodynamics. These things are at the core of a hydrocarbon charge risk evaluation.
The terms are unfamiliar and we do not have a good handle on these aspects of geoscience.
The same goes for inversion techniques – this analysis method is judged to be a special study, and
hence not used in normal workflow for assesing reservoir and maybe trap integrity.
Basin Modeling as part of Inversion – or Inversion part of Basin
Modeling ?
Traditionally, basin modelling has been used by the oil and gas industry to study the
physical and thermal histories of basins. The models lead to an estimation of the
timing of hydrocarbon generation and expulsion.
In recent years, however, basin modelling has expanded to include evaluation of
secondary migration and trapping of hydrocarbons within basins. It is therefor
10. important to understand the hydrocarbon dynamics in a basin, not only how
hydrocarbons form and expulse, but also how the basin developed – structural wise.
This is a very important task, and since inversion products can help enhance the
resolution and increase the S/N ratio, it should enable better understanding of the
hydrocabon dynamics in a basin and hence give more clear cut answers to the
prospectivity in areas. Since impedance data give the explorer surfaces, the carrier
beds could be better defined and therfor give more correct answers to the migration
mapthways and trap development through space and time. Therefor it should be
used impedance data to perform horizon mapping, to better give a distribution of
lithology properties that should be input to the thermodynamic model, and to give
support for hydrocarbon migration,
Hydrocarbon Charge
Simply, and most usefully, hydrocarbon charge is the filling, with hydrocarbon fluids,
of traps (prospects) within a basin.
Whereas trapping configurations and reservoir characteristics of a prospect may be
very local in scale, the hydrocarbon charge of a prospect may involve a significant
portion of the basin. All hydrocarbons that migrate to a prospect, in physical and
temporal space, make up the hydrocarbon charge of that prospect. A prospect may
be gas charged, oil charged, under-charged, or the area may have no hydrocarbon
charge.
Here our inversion products ranging from traditional impedance data to more
advanced AVO inversion and of course combined with stratigraphic coherence
analysis. Some migration pathways are as known prohibited or increased through
fault systems.
Basin Modelling essential to prospect/ play model analysis
Here is a very simple scenario. A geologist and geophysicist look at a seismic line in
a frontier basin and see an undrilled structure. This of course also apply to more
mature basins where one wants to exploit the remining more subtle prospectivity. The
only difference is calibration potential and uncertainties. G&G Experts are able to
map its areal extent and establish an area of closure. No faulting is evident. The risk
of trap failure is low. The seismic data gives them some information about the
lithology and thickness of the potential reservoir sections. The risk of reservoir failure
is moderate. Through a simple volume calculation they determine that the structure
can hold a commercial quantity of hydrocarbons. Should a well be drilled? A
comprehensive evaluation of the hydrocarbon charge risk using basin modelling
could possibly give the answer.
Here is how. The only data available to the basin modeller in the above scenario are
the seismic data. From these data we are able to construct a 'guess' about the
geologic development of the basin (evidence of erosions, age of sediments, tectonic
history, etc.). This conceptual model is applied to the data. We may also determine,
using seismic stratigraphy, which seismic intervals represent periods of geologic time
favorable for the development of a source rock. We add these 'potential source rocks'
to our conceptual model. We make use of modern analogs to add a thermal history to
the conceptual model. We submit the conceptual model to a computer program (any
Basin modelling tool box) that mathematically reconstructs the geologic history of the
basin applying common physical laws to the basin as it develops. The results (a
mathematical model) tell us about the thermal maturity of the basin Figure 1, if our
11. 'potential source rock' generated and expelled hydrocarbons, when it generated and
expelled hydrocarbons, and the type of hydrocarbons generated and expelled.
Most Basin Modelling is done without doing a proper structural development model,
as well as not consider properly at which levels the hydrocarbons can migrate along.
Both these factors can be determined through inversion.
Figure 1.
So, returning to our scenario, the basin modelling results may tell us that the basin is
thermally immature and any 'potential source rock' has not generated hydrocarbons.
They may tell us that the basin is thermally mature and a potential source rock
generated and expelled hydrocarbons . . . millions of years before the trap was formed.
They may tell us that the early charge, generally oil, occurred prior to the structuring
event, however, the structure was in place to receive a late gas charge. Regardless of the
results, we have one more piece of the puzzle to use in the overall risk assessment.
Therefor the basin modelling will act as a supportive tool to our inversion tools, if our
AVO results calculates the hydrocarbons, it can be verified or counter striked by the
Basin modelling.
What if well data are present?
In the previous scenario, no well data were available. The conceptual geologic model
built for our basin is just one possible model out of many. For example, ages may be
incorrect, the amount of eroded section may be wrong, and so on. The model results,
in the previous case, come from creating best and worst case scenarios. Basin
modelling is at its peak when well data are present, as well as inversion work is.
Why? Because now we can compare mathematical results to real data taken from
the well. For example, we can compare calculated temperature vs. depth to
measured bottom-hole temperatures Figure 2. The same goes for inversion, as we
can calibrate towards density and velocities in wells.
12. Figure 2.
If the two do not compare favorably, then we know our conceptual geologic model
does not adequately represent the real world. In this case, we rethink, and rebuild,
our conceptual model and compare the new mathematical results with the measured
well data. Depending on the amount of measured data available from the well, the
process of comparison-rethink-rebuild may occur several times during the course of
an evaluation. This optimization of the mathematical model is called calibration and it
is the most important aspect of basin modelling. When we have constructed a
conceptual geologic model yielding mathematical results that compare favorably with
many independent groups of measured well data, then our conceptual model is an
accurate representation of the real basin. We can then use this model as a template
for looking at other areas of the basin where wells are not present and maintain a
relatively high degree of accuracy. As more wells are drilled in the basin, new data
become available, more calibration can occur, and the conceptual model is further
refined.
What type of well data can we use for calibration?
Well data used for calibration in basin modelling can be classified into three
categories: Physical, Thermal, and Geochemical. Physical data include porosity,
permeability, pore pressure, mud weights, etc. Thermal data include temperature
data from BHT's, DST's, RFT's and the like. Geochemical data include pyrolysis
(Rock-Eval) data, maturity data (Ro, TAI, SCI, etc.), and biomarker ratios. As seen it
is not much overlap in data usage between basin modelling and inversion studies.
The only data we can use, is porosity data for calibration towards inversion models.
But the studies can be complimentary to each other, as they approach the basin in
two different ways, but can confirm each other.
13. Are There Any Other Geochemical Data we Can Use in Basin
Modeling?
In recent years, new techniques have emerged that tell us something about how and
when various types of kerogens convert to hydrocarbons. The branch of science that
deals with this is called kinetics. Each kerogen has a unique combination of activation
energy levels at which it 'transforms' into hydrocarbons. It serves our purpose to think
of the varying energy levels as changes in temperature. As the temperature
increases, the energy level increases. Generally, Type I kerogens have a very narrow
energy range in which they transform, whereas, Type III kerogens have a much
broader range. The importance of kinetics to basin modelling is two-fold. We can
better model timing of hydrocarbon generation and we can begin to investigate types
and volumes of hydrocarbons generated. In this step, there is not much inversion can
contribute with, apart form telling how light the hydrocarbons could be (oil,
condensate or gas).
Timing of Hydrocarbon Generation
Historically, basin modellers used thermal maturity based on vitrinite reflectance to
estimate the timing of oil and gas generation. We have all heard the statement that a
rock is in the 'oil window' or 'gas window'. However, two problems exist here. First,
although vitrinite reflectance is a measurable quantity, the relationship between
vitrinite reflectance data and oil and gas generation zones is basically empirical and
may not be the same in every basin. In fact, 'oil window' and 'gas window' can be
somewhat misleading because a source rock can have a vitrinite reflectance value
that puts it in the 'oil window' , however it will not be generating oil. Vitrinite
reflectance data are a one way street. The vitrinite reflectance of a rock can never
decrease. An analogy would be our own chronological age. We begin as children
('immature'), continue through adulthood ('mature'), and wind up in old age
('overmature'). The problem is we can take something that is overmature and put it in
an immature surrounding and it is still overmature. To continue with the analogy; we
walk into a kindergarten class room and realize the setting is for children. If a 90 year
old man is sitting in the class, do the surroundings make him chronologically
younger? No, he is still 90. In a like fashion, a source rock with a reflectance of .9 Ro
(in the oil window), but at the surface, still has a reflectance of .9 Ro. However, it is
not actively generating hydrocarbons.
The second problem in using vitrinite reflectance data to estimate timing of
hydrocarbon generation is that it is independent of rock or kerogen type. It is strictly a
time-temperature index. A prodelta shale with a Type III kerogen can have the same
maturity (oil window/gas window) as a basin floor shale with a Type II kerogen. Does
this mean they are both producing hydrocarbons? No!
Kinetics allows us to deal with these two problems to better model the timing of
generation of hydrocarbons. First, kinetic properties of kerogens can be measured in
a laboratory and, unlike vitrinite reflectance data, tell us the distribution of activation
energies at which the kerogens transform to hydrocarbons. Second, the distribution
of activation energies are unique to each kerogen. Therefore, two kerogens may
behave differently at the same energy level. We return to our earlier analogy of the
90 year old man to demonstrate. The 90 year old man is now joined by a second 90
year old man. The first 90 year old man is weak and stares through feeble eyes as
the second 90 year old man jogs into the room. The second man runs around the
room several times, does 50 one-armed push-ups, then jogs out. Both men are the
14. same maturity (90 years), but the second man can do more at that maturity than can
the first man. The Type III kerogen in the prodelta shale and the Type II kerogen in
the basinal shale are at the same maturity, however the Type II kerogen may have
completed its transformation to hydrocarbons while the Type III kerogen is only
partially complete.
Basin modellers build a specific kerogen, or kerogens, into the conceptual model. We
then use the measured kinetic parameters for the kerogens to model the
transformation history of each individual source rock. This is a more accurate
methodology for the estimation of the timing of hydrocarbon generation than using
maturity.
Type and Volume of Hydrocarbons
Kinetics, coupled with other geochemical measurements, provides the ability to
predict the type and volume of hydrocarbons generated. Geochemists have known
for some time that different types of kerogens produce different types of
hydrocarbons. Generally, a Type I kerogen is a prolific oil producer while a Type III
kerogen produces less oil and more gas. Also, generally, the API gravity of a
hydrocarbon fluid increases from early generation to late generation. This is because
the earliest fluids generated tend to be the heaviest compounds (C15+) and
subsequent generative products become lighter until we end with the lightest,
methane. Whereas kinetics data can give us the information about the energy level
needed to transform the kerogen into oil and gas, or, into the different components
(C15+, C6-C15, C2-C5, and C1), Rock-Eval data tells us about the generative
potential of this kerogen. The final piece of geochemical data needed to complete the
evaluation is total organic carbon (TOC). This tells us how rich, in organic material, is
the rock. Simply put, Rock-Eval and TOC data tell us how much we are going to get;
kinetics tells us how we are going to get it. These data, along with density information
of hydrocarbon fluids, allow the basin modeller to predict the type and volume of
hydrocarbons available in different parts of a basin at any time of its development.
Two Dimensional Basin Modelling
One-dimensional basin modelling is most useful in providing information about the
timing of hydrocarbon generation and the type of products that are generated. Two-
dimensional basin modelling is most useful in providing information about the
petroleum system. The ability to model a series of cross-sections in a basin allows,
for the first time, some insight into how hydrocarbon fluids migrate and are trapped.
Input data are similar between the two model types. However, two-dimensional
modelling requires incorporation of lateral changes in rock, source rock, and thermal
properties. Lateral changes in these properties mean that each point along the cross-
section undergoes a different burial and thermal history. Porosity of a formation in
one area might be reduced due to normal compaction. The same formation a few
kilometers away might have a lower permeability which does not allow the pore fluids
to escape rapidly. This maintains porosity. Changing depths and thermal properties
mean the source rock will generate and expel hydrocarbons at different times. All
these factors control when and where hydrocarbons move.
Two dimensional basin modelling also introduces a new calibrant; the present
distribution of hydrocarbons in the basin. Each of the critical components, source
rock, migration paths, reservoirs, seals, and traps have undergone a geologic history
that yields the petroleum distribution we see today. When we explore, we see a
snapshot of a dynamic petroleum system. Some of the hydrocarbons we identify from
well data as "shows" may be in the process of migrating to another part of the basin.
15. We caught them in transit. Even trapped hydrocarbons are only temporarily stalled.
Structural trap failure, seal failure, and reservoir destruction have been well
documented. We are lucky when we find a situation where all the components in this
dynamic system are, for the present, in place. The results of a two dimensional
modelling exercise should show hydrocarbons in traps and reservoirs where they are
known to exist. If not, then some aspect of the geologic model is incorrect. The
solution is, like one-dimensional modelling, to rethink and rebuild our geologic model.
In this way we will develop risk parameters for the basin; not only for hydrocarbon
charge, but also for reservoirs, seals, and traps.
Making Models Matter
Like all other businesses, exploration is now subject to greater accountability with the
requirement for performance measurement and quality assurance. Increasingly, E&P
experts are being asked by non-technical people to explain in plain language what
they do, why they do it that way, and how they can measure their effectiveness.
Managers and investors require assurance that the exploration programs in which
they have a direct interest are being carried out at least as effectively as those of
their competitors.
What do these issues have to do with the scientific process of exploration, with
designing and implementing R&D for the exploration industry, and, in particular, with
the development of exploration models? Even the most "pragmatic" of explorers use
geological models to justify their decisions as to exploration methodology and
"prospectivity", and to argue that their approach is more effective (i.e., lower risk)
than others. In addition, the marketing of exploration projects and companies
invariably involves at least implicit use of models to justify expenditure, support
money raising, or simply to present results.
In addition, we are currently going through one of the most significant changes in
E&P industry in its history. Billions of dollars of equity funding have been raised,
largely by junior companies, for exploration over the last three to four years. This is
risk capital, and yet E&P company experts are very poor at communicating the
technical aspects of exploration risk among themselves, let alone to non-technical
interested parties.
For the first time in decades, it is arguable that the majority of worldwide exploration
and indeed discoveries, especially at the more grass roots levels, is being achieved
by juniors rather than majors. So called 'juniors' have annual exploration budgets in
the tens of millions of dollars, and they are very sophisticated and technically aware.
In parallel with that change, we are seeing very rapid growth in the services sector to
the E&P industry.
As a result, the customer base for both the R&D community and the geoscience
profession at large is changing dramatically. The rather cosy relationship that has
existed for the past 20 to 30 years between the research community and the larger
companies, is no longer adequate to service the industry as a whole. Similarly,
publication in traditional academic journals is not meeting the modern exploration
community's needs for communication of R&D results.
However, industry view is that most of the current models for forming hydrocarbon
plays are not optimally used to exploration, and have failed as communication aids to
the less technical people who are increasingly among industry stakeholders. The all
16. too widespread practice of oversimplifying industry models and practices when faced
with a non-technical audience (eg, boards of directors, investors), rather than finding
out better ways of communicating them is counterproductive.
The principal deficiency in such models is that they do not incorporate a sufficiently
detailed and precise understanding of the critical geological processes that were
responsible for localising the play.
As a result, the models lack the essential predictive capability to become
genuinely effective exploration tools.
In this context, we briefly examine the ways in which we develop and use exploration
models. We are particularly concerned with the following questions.
Are the models that industry use sufficiently explicit and useable to be able to support
the decision-making process in a practical way?
Can they provide real input into the evaluation of exploration risk and the analysis of
the cost versus the value of information?
Do the models enable geoscientific information to be linked in a practical way to an
exploration methodology?
The petroleum exploration industry has developed semi-quantitative risk
evaluation procedures that link their scientific models directly to the assessment of
prospectivity, ranking of targets, and determination of appropriate exploration
expenditure levels.
We will briefly examine an example of the application of such risk evaluation
techniques to hydrocarbon exploration, and demonstrate the linkage between the
development and application of an effective play model, the generation and ranking
of targets, the design of appropriate exploration programs, and ongoing evaluation of
the effectiveness of those programs.
How then do we "make models matter"?
We recommend that playmodel/exploration models be developed, applied and
continuously revised according to the following principles.
The models should be based on a thorough understanding of the dominant
geological processes involved in the formation of the playtype type being sought.
The emphasis should be on process rather than just product.
The exploration team should develop/refine and 'own' the model(s) relevant to its
needs and to the particular geological setting of the exploration area. Generic models
taken 'off-the-shelf' are rarely suitable. Models developed by the research community
should therefore encourage this process.
The models should be linked to the whole process of exploration, including the
acquisition and assessment of information, a clear decision-making strategy,
the development and implementation of risk-management procedures, and the
formulation, budgeting and ongoing evaluation of the exploration program.
Models must be translated into a map form that is relatable to the geology of the
exploration area. Integrated geological, geophysical and geochemical databases can
then be compared to the model maps to produce 'probability' maps, enabling
exploration dollars to be focused on the areas with the lowest technical risk.
17. Realistic geological process models for most deposit types are complex. They
usually incorporate several physical and chemical processes with complex
interdependencies. They should therefore incorporate at least some of the' fuzzy'
logic associated with chaotic processes.
In other words, we need to develop, apply and continuously revise industries
exploration models within the business framework, and not just see them as an
intellectual or 'academic' exercise that is somehow divorced from the 'real business'
of exploration. Explorers should be able to measure the effectiveness and efficiency
of exploration programs against the models, and make sensible business decisions
on that basis.
18. The 4D Business Opportunity
4D Technology – What is it?
Massive amount of data available to ”mine”
Software process = The Technology
Market hurdles to overcome.
4D Technology is Expected to Improve Recovery of reservoirs of all
types.
19. 4D Increase Property Asset Value *
Average 20-30% recovery improvement when bright spots present.
How?
o Delays shutin and retirement costs
o Increase recovery & potentially proven reserves.
o Optimize new well placement.
o Plan work-overs and infill targets
o Identify underproduced reserves
o Optimize capital expenditures & increase time-value of money
o Better locate injector position and rate of injection volumes
o Reduce amount of dry holes or bad performers in fields.
o Preempt operational problems
* Source Amoco and Exxon Mobil
4D Grows the Seismic Market – regional and globally. The trend is technology driven
as well as data driven.
Data quality and quantity – more fields have several vintages of data
Technology enables calbration of vintages of seismic despite aquisition and
processing differences between the different vintages.
20. 4D Creates Added Value form Existing 3D Seismic Data
10.000 ++ blocks worldwide of multiple 3D surveys exists for immediate 4D
use
21. New Wells are being drilled to recover reserves.
This example is from EI330 block offshore Gulf of Mexico.
Active & Planned 4D projects.
This overview is outdated – but will serve as a guide to the areas and fields where 4D
has already begun its entry as a workflow.
22. 4D technical hurdles to Overcome.
Despite the fact that several fields experience a large recovery when utlizing 4D
workflow in fields, there are several factors prohibiting the use of 4D technology and
workflow.
