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2017-09-RECORDER-Hydraulic Fracturing Data Integration

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FOCUS ARTICLE
Coordinated by Paul Hausmanis / Louis Chabot / Elwyn Galloway
Hydraulic Fracturing Data Integration –
What Should I Be Asking My Engineer and
What Are They Trying to Tell Me?
Jennifer L. Miskimins, Ph.D., P.E
COLOR ADO SCHOOL OF MINES, GOLDEN, CO, USA
between technical disciplines in
Communication the oil and gas industry is always
a challenge. Different defnitions, varied nomenclature, diverse cultures
and backgrounds all make for challenges when working in the multidisciplinary world of petroleum extraction. This paper is an abridged
version of the November 2016 Keynote Luncheon Presentation entitled
“Integrating Data – How Geophysicists and Engineers Can Work
Together to Improve Hydraulic Fracturing” and focuses on the basic
reasons for hydraulic fracturing and what the engineers’ goals generally
are when developing a hydraulic fracturing treatment design. Opportunities for potential areas of data integration between the engineering
and geophysical world are provided, and the paper concludes with
some questions that might help to spur better communication between
these two disciplines.
Introduction
According to the Merriam-Webster dictionary, “communication”
is defned as “the act or process of using words, sounds, signs, or
behaviors to express or exchange information or to express your ideas,
thoughts, feelings, etc., to someone else”. One of the biggest concerns
with multidisciplinary integration in the oil and gas industry is basic
communication. How do different disciplines look at techniques or
applications? How do they approach them? What’s important to each
person involved?
When discussing how geophysicists and engineers can work together
to improve hydraulic fracturing, it is probably best to start with a
discussion of how engineers look at hydraulic fracturing. Hydraulic
fracturing is known as a stimulation technique. In essence, it allows the
well to produce more than it ever could have under natural, non-damaged conditions. By defnition, stimulation means that a well exhibits
a negative skin factor, S. If damaged, the skin factor will be a positive
value. These impacts can be seen when placed into Darcy’s radial fow
equation, Eq. 1, where a positive skin factor drives down the fow rate, Q.
(1)
32
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SEPTEMBER 2 017
Q
k
h
Pi
Pwf
=
=
=
=
=
fow rate
permeability
height
initial reservoir pressure
well pressure
B = formation volume factor
μ = viscosity
re/r w = ratio of drainage radius
to wellbore radius
S = skin factor
Another way to look at a hydraulic fracturing treatment is that a negative
skin factor makes the wellbore radius, rw, “look” bigger to the reservoir,
thus creating a larger exposed surface area and therefore increased fow
rate. This impact can be observed in Eq. 2, where r wa is the “effective
wellbore diameter”.
(2)
This effective wellbore diameter leads to a discussion of “effective
length”. A hydraulic fracture’s length is a point of constant discussion,
however, a major communication issue can be just which “length” is
being discussed – there are actually four. The length of the fracture
contributing to production, as described in Eq. 2, is the “effective
length”. This is the most important of the three, since it is what contributes directly to enhanced production and reserve recovery. The other
three are as follow: “microseismic length” is a measure of the distance
from a wellbore at which microseismic events are detected; “hydraulic”
or “pressurized length” is the distance to which pressure is transmitted
from the treated wellbore during pumping; and “propped length” is
the distance to which proppant is transmitted out into the reservoir.
Although the latter two have an impact on the ultimate effective length,
there is no direct link or percentage calculation. The resultant effective
length is greatly impacted by such things as multi-phase fow, reservoir
permeability and pressure, well spacing, and treatment design. Figure 1
demonstrates these various defnitions of length.
Coupled closely to effective length is fracture conductivity, which is
defned as the permeability of the fracture multiplied times the width
of the fracture. Adequate fracture conductivity given a reservoir’s
producing capacity helps to establish the maximum effective length for
a certain well-reservoir system. These concepts apply to all reservoir
systems, however, the focus of this article will be on unconventional
reservoirs with horizontal wells that are treated with multistage hydraulic
fracturing treatments.
present value is a better way to consider these systems. Overall, it is
impossible to maximize all of the goals, therefore, the engineer must
focus on what is most important to them and their management and
design accordingly.
Scale
Figure 1. (a) The fgure to the left represents a pad with fve horizontal wells
shown in black. The solid red lines demonstrate effective fracture lengths along
the center well, while the blue boxes drawn around those lengths represent the
associated drainage areas. The dashed red lines represent potential propped
or hydraulic lengths. (b) The fgure to the right shows a four-well pad with
microseismic lengths emanating from the 3H well. Both fgures point to the
importance of understanding the effective length of a fracture as it directly
impacts appropriate well spacing. (From Barree et al., 2017.)
Goals of Hydraulic Fracturing
When designing a hydraulic fracturing treatment, there are usually
several goals that are attempted to be accomplished. The importance
or ranking of these goals will vary depending on the specifc objectives
of the company or engineer that is designing the treatment. Along
these same lines, the data that is needed to improve or aid the design
(and the associated cost to acquire them) is also a function of the overall
treatment goals.
In general, maximizing the effective fracture length is a major objective
for most treatments. Quite simply, the longer the effective fracture
length, the larger the drainage area for that well, and the fewer wells
needed for a given area. Coupled with the effective length is the desire
to achieve adequate fracture conductivity for the available reservoir
deliverability. Minimizing the potential damage through gel damage,
crushing, flter cake build-up, etc. to the established conductivity is also
desired. As with the damage to the fracture conductivity, minimization
of damage to the formation itself should be pursued.
In multistage treatments, such as those pumped in most horizontal
shale wells, maximizing the number of zones producing and draining
everything that is connected to the well should be a focus. It is
frequently reported that the number of contributing stages is well below
the number actually pumped in many horizontal wells (<50%), which is
obviously a large waste of resources under such circumstances. Also,
when considering the number of stages and other variables for a given
well, the importance of acceleration or addition of reserves needs to be
understood. Both can be achieved but are not directly related. (Barree
et al. 2015). Pursuit of acceleration, without adding reserves, can destroy
economic value.
Finally, it might be obvious, but still needs to be stated, minimization of
treatment costs is always a desire. However, costs need to be considered under the other goal conditions, and perhaps maximizing net
Like many areas in the oil and gas industry, the scale of various measurements needs to be taken into account when considering hydraulic
fractures. Bedding planes or mechanical property variations on the
order of 1-2 cm can impact fracture growth, especially in the vertical
direction. Such a small scale is obviously below the resolution of many
data-gathering techniques and this fact needs to be considered when
integration of data sources is attempted.
Potential Opportunities for Integration
There are several places that geophysicists and engineers can work
together on data integration for improved hydraulic fracturing, not all
of which can be discussed in the space of this article. Focus is therefore
placed on three of the more obvious and perhaps easiest areas where
integration can be performed, while having a signifcant impact on
treatment design and overall feld development and characterization: 1)
diagnostic fracture injection tests (DFIT’s); 2) fber optic measurements;
and 3) fracture modelling.
DFIT’s
DFIT’s have become popular in unconventional reservoir development
as they provide information about a number of reservoir characteristics
including fracture pressure, closure pressure, process zone stress (the
difference between fracture and closure pressures), leakoff mechanisms
including the presence of natural fractures, reservoir pressure, and
reservoir permeability. This article focuses on the application of these
results and not the actual tests themselves, therefore, for further
information on such, the reader is referred to Barree et al. 2009, Barree
et al. 2014, and Barree and Miskimins, 2016.
DFIT’s are frequently used to help calibrate calculated closure pressure
(minimum in-situ stress) logs. While one DFIT in the zone of interest
can provide information regarding that zone, multiple DFIT’s taken in a
vertical profle can provide critical information about stress changes and
how they may or may not impact height growth. This is the same with
process zone stress values, which can also have a signifcant impact on
fracture containment in the vertical profle.
In addition to calibration of vertical stresses, this type of information
can also be plotted across a play or basin and linked to other data.
Figure 2 shows a small feld where DFIT data results corresponded to 3D
seismic information, whereas Figure 3 shows DFIT values associated with
structural complexity across an entire basin. Other DFIT results, such as
pore pressure and permeability can also similarly be plotted in vertical
and plan views.
Continued on Page 34
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FOCUS ARTICLE
Continued from Page 33
Figure 3. Potocki (2012) showed a strong relationship between tectonic complexity and process zone stress
(which he referred to as “net fracture pressure” or NFP) results from DFIT’s.
Figure 2. Four sections in a structurally complex feld.
The contour lines show the fracture gradients in psi/
ft. The impact of the large thrust fault to the west on
these gradients can be seen. 3D seismic was taken
across the feld and indicated a horsetail splay fault
system in the orange area. This structure coincides with
higher gradients and the presence of natural fractures
indicated from the DFIT’s. (From Miskimins, 2000.)
Fiber Optics
A relatively new area for integration is the use
of fber optics including distributed acoustic
and temperature sensing (DAS/DTS). This type
of data is providing detailed, dynamic information on what is occurring downhole during
multistage fracturing treatments, as well as
during post-treatment production. Figure
4 shows an example of perforation cluster
response to diverter drops during a treatment
stage, as well as behaviour during the rest
of the treatment. This type of data is also
providing information on leaking bridge plugs,
inter-stage communication, and zones/clusters
turning on and off during production.
Fracture Modeling
Modelling of hydraulic fractures is another
area where engineers, geophysicists, and
geologists can work together to improve
our understanding of fracture behaviour.
Helping to construct an accurate depiction
of the geologic setting, in both a vertical and
lateral setting can greatly improve the results
and credibility of fracture models. Figure 5
shows an example of such an improvement
in a stacked, fuvial system and the signifcant impacts it can have on the model results
when a detailed geologic system is incorporated. Especially for systems that have known
34
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SEPTEMBER 2 017
Figure 4. Treatment data for one stage (Stage 4) of a multistage fracturing treatment. The bottom fgure shows
the pump curve where two diversion stages were pumped (the black line is the rate and the diverters were
dropped when the rate was slowed). The DTS data is in the center, and the DAS data is shown at the top. In
the DAS data, the “hotter” colours of yellow and red show acoustic activity, while the “cooler” colours of blue
should little or no activity. In the DTS data, the “cooler” colours of blue and purple show where cooldown of the
wellbore is occurring, while the “hotter” colours in red show where the temperature hasn’t been affected. The
perforation sets are shown at the left by the green triangles. Both the DAS and DTS data show cluster activity
changing during the treatment. (From Wheaton et al. 2016.)
geologic changes in a lateral direction, whether structural or stratigraphic, this will result in an
improvement over a “layered cake” approach.
Another modelling area that needs to be addressed from a variety of perspectives is the stress
feld orientation and the fracture profle in relation to it. The present-day stress feld has a clear
impact on drainage pattern and fracture-well alignment. Additionally, the stress feld can have a
large infuence on overall treatment effciency, breakdown pressures, and the extent of longitudinal versus transverse fracture growth. Any insights into both large and small scale stress
behaviours can be helpful on a variety of levels.
References
Barree, R.D., Barree, V.L. and Craig, D.P., 2009, Holistic
Fracture Diagnostics: Consistent Interpretation
of Prefrac Injection Tests Using Multiple Analysis
Methods, SPE Production & Operations, 24, 396-406.
Barree, R.D., Miskimins, J.L. and Gilbert, J.V., 2014,
Diagnostic Fracture Injection Tests: Common
Mistakes, Misfres, and Misdiagnoses, SPE Production
& Operations, 30, 84-98.
Barree, R.D., Cox, S.A., Miskimins, J.L., Gilbert, J.V.
and Conway, M.W., 2015, Economic Optimization
of Horizontal-Well Completions in Unconventional
Reservoirs, SPE Production & Operations, 30, 293-311.
Figure 5. In both fgures, the lithology is represented as follows: yellow – sandstone, gray – shale, dark grey –
coal, and red – shaly sand. The wellbore and perforation intervals are indicated by the black tick marks. The fnal
proppant concentration in lb/ft 2 is shown in green (full scale at the bottom of the fgure). The left fgure shows
the fnal fracture proppant concentration results when a layer-cake model (properties only extrapolated from
well log data) is applied. The right fgure shows the difference in fracture growth when the model incorporates
a full lithology model with lateral terminations of the various sand bodies. (From Cuba et al. 2013.)
Conclusions
This article (and associated presentation) is not intended to be a comprehensive discussion of data
integration between disciplines, but rather, it hopes to spur conversations between individuals to
improve the effciency and economic value of hydraulic fracturing. With that in mind, a few fnal
questions are provided to help instigate these dialogs and perhaps facilitate that communication.
What should I be asking my engineer?
•
How do you defne “stimulated reservoir volume?” Is it the “effective stimulated volume” or
something else?
•
Can I provide you with some help from a structural standpoint for your model? Fracture
swarms? Fault locations?
•
Can your model handle structural components? Are they important to the fracture behaviour?
If so, should we be looking at a way to handle them?
•
Can I help you defne sedimentary bodies? Terminations of such? Their mechanical properties?
Barree, R.D. and Miskimins, J.L., 2016, Physical
Explanation of Non-Linear Derivatives In Diagnostic
Fracture Injection Test Analysis: Presented at the SPE
Hydraulic Fracturing Technology Conference, The
Woodlands, Texas..
Barree, R.D., Miskimins, J.L. and Svatek, K.J., 2017,
Reservoir and Completion Considerations for the
Refracturing of Horizontal Wells: Presented at the SPE
Hydraulic Fracturing Technology Conference, The
Woodlands, Texas.
Cuba, P.H., Miskimins, J.L., Anderson, D.S. and Carr,
M.M., 2013, Impacts of Diverse Fluvial Depositional
Environments on Hydraulic Fracture Growth in Tight
Gas Reservoirs, SPE Production & Operations, 28, 8-25.
Miskimins, J.L., 2000, Characterization of PresentDay Stress States Near Faults, North LaBarge Field,
Sublette County, Wyoming, MSc. Thesis, Colorado
School of Mines, Golden, Colorado.
Potocki, D., 2012, Understanding Induced Fracture
Complexity in Different Geological Settings Using
DFIT Net Fracture Pressure: Presented at the SPE
Canadian Unconventional Resources Conference,
Calgary, Alberta, Canada.
Wheaton, B., Haustveit, K., Deeg, W., Miskimins, J.
and Barree, R., 2016, A Case Study of Completion
Effectiveness in the Eagle Ford Shale Using
DAS/DTS Observations and Hydraulic Fracture
Modeling: Presented at the SPE Hydraulic Fracturing
Technology Conference, The Woodlands, Texas.
What is my engineer trying to tell me?
About the Author
•
In unconventional reservoirs, longer term production data is usually needed before I can
calculate drainage area.
•
I really, really, really need to understand the 3D pore pressure distribution – can you help
me with that?
•
•
Initial completions can be ineffcient; can you help me determine gaps (4D, fber)?
Dr. Jennifer L. Miskimins
holds B.S., M.S., and
Ph.D. degrees in
Petroleum Engineering.
Presently, she is an
Associate Professor at
the Colorado School of Mines (CSM) in the
Petroleum Engineering Department. She is
a member of SPE, RMAG, and AAPG, was
an SPE Distinguished Lecturer for 2010-2011
and 2013-2014, and currently serves on the
SPE Board of Directors as the Completions
Technical Director.
A “successful” fracturing treatment is not always an economically optimized fracturing treatment.
Hopefully, these thoughts will help improve your completions and spur some lively discussions!
Acknowledgements
The author would like to thank the editors of this special journal edition for the opportunity to
contribute to it. Also, thanks to the DoodleTrain organizing committee for the initial opportunity
to present these thoughts during their annual luncheon.
SEPTEMBER 2 017
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