As the petroleum industry
migrates from its relatively safe havens into more turbulent frontier
environments, significant challenges await decision makers in all disciplines.
The increasingly expensive and uncertain investments, with highly uncertain
risks inherent in revenues and tax regimes, which may never cover the hundreds
of millions and even billions of dollars in costs, raises an ominous cloud over
our industries future profitability.
Uncertainty is a part of every
decision we face in our industry (and in life in general). Ignoring, or hiding
from, uncertainty does not remove it. However, as will be extensively discussed
and illustrated in this course, uncertainty is not necessarily a negative to be
avoided. The challenge for decision-makers is not to eliminate all uncertainties,
but to anticipate - and prepare for the consequences, positive and negative, of
uncertainty. To do that, we must acknowledge uncertainty: uncover it, recognize
it, understand it, and deal with it in an unbiased way. Most courses on
decision-making emphasize that as the likelihood of a project's success is
evaluated, the risks of failure must also be assessed. Very few of these courses
consider the numerous ways we might capitalize upon uncertainty, turning it
into a competitive advantage.
This course will illustrate how to accurately capture
the important uncertainty elements around, for example:
oil-in-place
and reserves;
production
rates;
time to first
oil;
drilling times
and down times; and
economic metrics.
The participant will learn how to calculate the value
of, for example:
taking a core,
drilling another appraisal well, or reprocessing seismic;
constructing a
larger platform for additional wells to capture the upside oil in place
potential;
initiate a
consulting study;
initiate a
research project to enhance, drill-bit technology; and
stimulate a well,
performing workovers, or buying and/or upgrading
modeling and processing software.
We will also show how to calculate the appropriate
balance between:
cost and
benefit;
risk and
return;
value of
acquiring information to reduce uncertainty versus building in flexibility to
manage the impact of uncertainty; and
capital allocation
between infill wells, side-tracks and workovers (or,
in general, different programs).
Other decision-making challenges and questions that
will be discussed include:
how do I
optimize a decision given multiple and sometimes competing objectives;
how can I
recognize a good decision;
what are the
right questions to ask to ensure unbiased estimates that capture the true range
of uncertainties;
how can I
avoid common psychological and behavioral traps in uncertainty
characterization, valuation and decision-making
A broad audience
including petroleum engineers (surface and sub-surface), geoscientists,
managers and decision-makers. Petroleum industry
professionals looking for an introduction to the field. It is primarily
a course to introduce modern decision-science tools to the uninitiated but it
can also be used as a review for the practicing decision-making engineer or
geoscientist.
A defining characteristics of
this course is the upside opportunity aspects of uncertainty. It is in the
intelligence-gathering stage that we as decision-makers seek to overcome
uncertainty. We often hope that more information will at least reduce, if not
eliminate, the discomforting uncertainty. The intent seems logical, and, in
part, it is. Many of us were trained to manage just that way. We learned to
work toward single numbers for all important parameters such as reserves,
production, oil price, etc.. When statistics and
probability gained momentum in the oil & gas industry they were often
viewed as tools and means for reducing and, ideally, eliminating uncertainty.
At the corporate management level we learned that distilling past performance
and future prospects to a set of numbers was crucial. Vague projections and
expressions of doubt were signs of analytic weakness, so, faced with
uncertainty, many of us ask for more facts, believing (with some justification)
that more information will let us pinpoint which of the various options will
succeed. We demanded precise forecasts - and ignored all the uncertainty
embedded in them. We felt justifiably annoyed at colleagues who offered only
loose estimates and wishy-washy "on the one hand,
but on the other hand" or it depends analyses.
Unfortunately, in a world
characterized by increased technical and commercial complexities, and
increasing levels of uncertainties we are dealing not so much with trends as
with surprises. Numerical precision offers only a false sense of certainty.
Even if real certainty were possible (and in our industry, it's not), the cost
of obtaining it is unacceptably high. What do we as
decision-makers do?
This course take the approach that
uncertainty must be reduced as far as it makes sense for any given situation,
then it must be managed. Managing uncertainty doesn't mean accepting vague
projections, making wishy-washy recommendations, or abandoning planning. It
does, however, mean redefining rigor. In the uncertain world of oil & gas
exploration & production, rigor is not found in precise single-point
predictions, but rather in precisely defined uncertainty estimates. It is not
obtained by selecting the one right prediction for the future, but through a
rigorous process that will enable us to anticipate and prepare for multiple
futures.
The course will illustrate how to appropriately characterize uncertainty but will also show how to mitigate the downside risks and capture the upside potential. Indeed, it is the decision-makers most skilled in eliciting, assessing, characterizing, valuing and managing uncertainty who will make the best decision and create competitive advantage.
Decision-making
Process
Objective
hierarchies
Framing
and influence diagrams
Multi-Objective
Decision Making
Review
of basic probability and statistics concepts and techniques
Review
of project economic evaluation
Decision
Criteria
Decision
Trees
Value
of Information
Sensitivity
and Risk Analysis
Scenario
assessments.
Preference
theory
Psychological
and judgmental aspects of decision-making