Drowning In Data — The Future of
Reservoir Performance Analysis
(more data, models, analysis, and software — but
will we know any more than we do now?)
T. A. Blasingame, Ph.D.
Department of Petroleum Engineering
Texas A&M University
College Station, TX 77843-3116
(979) 845-2292 — t-blasingame@tamu.edu
The Future of Reservoir Performance Analysis
Slide — 1
Reservoir Performance Analysis: Philosophy
Ignorance is bliss...
Production data exist.
Data quality issues.
Where is the pressure data?
What we want...
"Data on demand"
Wellbore pressure data!
Flowrates for each phase.
What we can live with...
Monthly production data.
Some idea of pressure.
Allocated data (if we have to).
From: Dealing with the Idiots
in Your Life, J. Benton (1993).
Ignorance may be bliss — but,
then again, you're still ignorant!
Blasingame
The Future of Reservoir Performance Analysis
Slide — 2
Reservoir Performance Analysis: Future View
Practically speaking...
"Data on demand" will arrive.
We may even have pressure.
Today's tools can not handle
the task of analysis and interpretation.
"Drowning in Data"
Consider the case of pressure transient testing —
10,000-100,000 data are now
common.
Production databases will be
enormous...
From: SPE 56419 — Athichanagorn, Horne, and Kikani (1999).
May your every wish be
granted...
Ancient Chinese Curse
The Future of Reservoir Performance Analysis
Slide — 3
Reservoir Performance Analysis: Let's Cheat...
Consider a well test example:
Impossible to analyze all of
the data...
Use "windows" to analyze
segments of the data.
Surprise! The results are not
the same from window to
window — but they are
related (see histograms).
Good news: The statistics are
relevant...
Bad news: This is not as consistent as we would like...
From: SPE 56419 — Athichanagorn, Horne, and Kikani (1999).
First gain wealth, then gain
virtue.
Greek Proverb (bad advice)
The Future of Reservoir Performance Analysis
Slide — 4
Reservoir Performance Analysis: What else?
"Van Everdingen-Meyer Method:
"Analysis by simulation" (use
analytical solution to define xaxis plotting function.
Considers all of the data,
needs a complete model to
generate an appropriate
analysis/interpretation.
Theoretically simple, practical.
Pro: Theoretically simple and
practical (can use field data).
Con: Limited by solution model
as well as data quality.
From: SPE 15482 — Whitson
and Sognesand (1988).
A wise man will make more opportunities than he finds.
Francis Bacon (1625)
The Future of Reservoir Performance Analysis
Slide — 5
Reservoir Performance Analysis: What's Next?
Data analysis/interpretation:
Improved acquisition.
Integration of analytical and
numerical tools.
"Event" analysis
"Continuous" data analysis.
Good news: The tools (analytical and numerical) will evolve.
Bad news: The data burden will
be tremendous, perhaps even
overwhelming. Data quality
may still be an issue.
From: School is Hell, M. Groening, (1987).
The heresy of one age becomes
the orthodoxy of the next.
Helen Keller (1903)
The Future of Reservoir Performance Analysis
Slide — 6
Reservoir Performance Analysis: History Lessons
Origin of technology:
Early 1900's — estimate well
deliverability and reserves.
"Reservoir characterization" did
not evolve until 1950's.
Relevance:
Pressure transient testing is a
"high frequency/high resolution" data analysis technique.
Production data analysis remains a "crude data" technique.
Data quantity/quality issues will
always be an issue.
From: Dealing with the Idiots in
Your Life, J. Benton (1993).
Anybody can make history.
Only a great man can write it.
Oscar Wilde (1890)
The Future of Reservoir Performance Analysis
Slide — 7
Reservoir Performance Analysis: History Lessons
From: Manual for the Oil and Gas Industry —
Arnold (1919).
From: Estimation of Underground Oil Reserves
by Oil-Well Production Curves — Cutler (1924).
Production decline analysis:
Over 80 years old!
Objective was economic, not
technical — production extrapolations were even
referenced to the tax year!
Very humble origins —
"whatever worked" plots
seemed to be popular (e.g.,
Cartesian, log-log, and semilog).
Reason is the greatest enemy of
faith. (abridged)
Martin Luther (1569)
The Future of Reservoir Performance Analysis
Slide — 8
Reservoir Performance Analysis: History Lessons
a. The "engineer's solu- b. The "gee it works" plot c. The "scratch your head"
— I wonder if there is
plot ... interesting, but ...
tion" (i.e., the log-log
some theory ... (yes).
how does it work?
plot) (did not stand
the test of time plot).
(Only) ants and savages put
strangers to death.
From: Estimation of Underground Oil Reserves
Bertrand Russell (1950)
by Oil-Well Production Curves — Cutler (1924).
The Future of Reservoir Performance Analysis
Slide — 9
Reservoir Performance Analysis: History Lessons
From: SPE-Transactions — Arps (1944).
From: SPE 04629 — Fetkovich (1973).
"Arps" decline analysis:
Introduction of exponential
and hyperbolic families of
"decline curves" (Arps, 1944)
Introduction of log-log "type
curve" for the "Arps" family
of "decline curves" (Fetkovich, 1973).
Empirical ... but seems to
work as a general tool. Is
this more coincidence or
theory?
... hope is the worst of all evils,
as it prolongs man's torments.
Nietzsche (1878)
The Future of Reservoir Performance Analysis Slide — 10
Reservoir Performance Analysis: History Lessons
From: SPE 04629 — Fetkovich (1973).
From: SPE 04629 — Fetkovich (1973).
"Analytical" rate decline curves:
Data from van Everdingen
and Hurst (1949), replotted as
a rate decline plot (Fetkovich,
1973).
This looks promising — but
this is going to be one really
big "type curve."
What can we do? Try to collapse all of the trends to a
single trend during boundary-domination flow (Fetkovich, 1973).
Growth is the only evidence of
life...
John Henry Newman (1864)
The Future of Reservoir Performance Analysis Slide — 11
Reservoir Performance Analysis: History Lessons
From: SPE 04629 — Fetkovich (1973).
From: SPE 04629 — Fetkovich (1973).
Composite Transient Type Curve:
Collapses the transient flow
trends into "stems" related to
reservoir size and skin factor
(Fetkovich, 1973).
Composite Total Type Curve:
Addition of the "Arps" empirical
trends for "boundary-dominated
flow behavior (Fetkovich, 1973)."
Assumptions:
Constant bottomhole pressure.
"Liquid" flow (not gas).
You have to study a great deal to
know a little.
Montesquieu (d. 1755)
The Future of Reservoir Performance Analysis Slide — 12
Reservoir Performance Analysis: History Lessons
From: SPE 12917 — Carter (1985).
From: SPE 25909 — Palacio, et al (1993).
Gas — Carter Type Curve:
Correlation of gas well
performance for varying
levels of pressure drawdown
(Carter, 1985).
Gas — Fetkovich-McCray-Carter
Type Curve:
Addition of new the "McCray"
plotting functions (Palacio, et
al, 1993).
Assumptions:
Production at constant bottomhole pressure.
Man has to suffer. When he has
no afflictions, he invents some.
Jose Marti (1883)
The Future of Reservoir Performance Analysis Slide — 13
Reservoir Performance Analysis: History Lessons
From: SPE 28688 — Doublet, et al (1994).
From: SPE 25909 — Palacio, et al (1993).
Fetkovich Derivative Type Curve:
Good concept, but just try to
take the derivative of production data...
Fetkovich-McCray Type Curve:
Concept is to generate "integral" functions for data analysis, much better performance
than simply using rate.
Still Need:
Variable pressure/rate methods.
Other models — fractured
wells, horizontal wells, etc...
The ant is wise, but he does not
know enough to take a vacation.
Clarence Day (1920)
The Future of Reservoir Performance Analysis Slide — 14
Reservoir Performance Analysis: History Lessons
From: SPE 25909 — Palacio, et al (1993).
From: SPE 28688 — Doublet, et al (1994).
UNFRACTURED Well Case
Variable Rate/Pressure Approach:
Use "material balance time" (xaxis) and "pressure drop normalized rate" (y-axis) functions.
Good news:
New concept provides unique
behavior during boundarydominated flow regime.
Not-So-Good-News:
Wellbore pressure data are
critical.
Thinkers prepare the revolution,
bandits carry it out.
Mariano Azuela (1918)
The Future of Reservoir Performance Analysis Slide — 15
Reservoir Performance Analysis: History Lessons
FRACTURED Well Cases
Infinite-conductivity vertical
fracture case
Finite-conductivity vertical
fracture case(s).
From: SPE 35205 — Doublet, et al (1996).
From: Current Work — Pratikno (2002).
From: Current Work — Pratikno (2002).
A good garden may have some
weeds.
Thomas Fuller (1732)
The Future of Reservoir Performance Analysis Slide — 16
Reservoir Performance Analysis: History Lessons
Horizontal Well Cases — "Infiniteconductivity" horizontal well
case(s).
From: SPE 29572 — Shih, et al (1995).
From: SPE 29572 — Shih, et al (1995).
From: SPE 29572 — Shih, et al (1995).
The art of pleasing is the art of
deceiving.
Vauvenargues (1747)
The Future of Reservoir Performance Analysis Slide — 17
Reservoir Performance Analysis: History Lessons
Decline Type Curve Analysis:
"Break-glass-in-case-of-fire" cases
From: SPE 30774 — Doublet, et al (1995).
From: Unpublished — Marhaendrajana (2002)
(multiwell analysis — do not use).
From: SPE 30774 — Doublet, et al (1995).
It is a very rare thing for a man of
talent to succeed by his talent.
Joseph Roux (1886)
The Future of Reservoir Performance Analysis Slide — 18
Reservoir Performance Analysis: History Lessons
MULTIWELL Analysis
Multiwell case can be "recast" into
single well case using cumulative
production for entire field.
Homogeneous reservoir example shows
that all cases (9 wells) align — same
behavior observed for heterogeneous
reservoir cases.
From: SPE 71517 — Marhaendrajana (2001).
From: SPE 71517 — Marhaendrajana (2001).
From: SPE 71517 — Marhaendrajana (2001).
The great enemy of truth ... is
not the lie — but the myth.
John F. Kennedy (1962)
The Future of Reservoir Performance Analysis Slide — 19
Reservoir Performance Analysis: History Lessons
Agarwal, et al Methodology:
Basically the same as Blasingame, et al
work.
More like pressure transient test analysis/interpretation.
From: SPE 57916 — Agarwal, et al (1998).
From: SPE 57916 — Agarwal, et al (1998).
All animals are equal, but some
animals are more equal than others.
From: SPE 57916 — Agarwal, et al (1998).
George Orwell (1945)
The Future of Reservoir Performance Analysis Slide — 20
Reservoir Performance Analysis: Tools
Production Analysis Tools:
"Old" decline curve analysis.
Decline type curve analysis.
EUR analysis
Numerical simulation.
On the horizon — integrated data
acquisition, analysis, and control.
Issues:
What tools do we really want?
What tools do we really need?
Numerical modelling — savior
or villain?
Data acquisition is the key.
From: Love is Hell, M. Groening, (1984).
Experience is a hard teacher
because she gives the test first...
Vernon Law (1960)
The Future of Reservoir Performance Analysis Slide — 21
Reservoir Performance Analysis: Reality Check
Production data analyses and
pressure transient analyses
"see" the reservoir as a volumeaveraged set of properties.
New solutions/models will also
have this view of the reservoir.
It's only time-pressure-rate data,
don't expect a miracle...
The challenge of future work is
to represent the behavior of the
reservoir while also providing
an understanding of the scale of
reservoir features.
From: Simulator Parameter Assignment
and the Problem of Scaling in Reservoir
Engineering — Halderson (1986).
Never explain. Your friends do not need it
and your enemies will not believe you...
Elbert Hubbard (1927)
The Future of Reservoir Performance Analysis Slide — 22
Drowning In Data — The Future of
Reservoir Performance Analysis
(more data, models, analysis, and software — but
will we know any more than we do now?)
End of Presentation
T. A. Blasingame, Ph.D.
Department of Petroleum Engineering
Texas A&M University
College Station, TX 77843-3116
(979) 845-2292 — t-blasingame@tamu.edu
The Future of Reservoir Performance Analysis Slide — 23