Images
Videos
2D/3D/4D
Seismic
Downhole
Camera
monitoring
fluid flow
Microseismic
Well Logs,
Mud Logs,
Offset Logs
Time-based
image
sequences of
acoustic and
EM fracture
monitoring
Sounds
Numbers
Completion
Procedures
Distributed
Acousting
Sensing
(DAS) - fiber
optic sensors
Texts
Completion
Results
Core Analysis
Production
Data
Past and Present
Notes from
Drilling
Engineering
Artificial Lift
Data
Figure 1: Examples of shale data sets.
that are already at work in the oil patch.
Leading the charge is prescriptive analytics, which can “prescribe” optimum recipes for drilling, completing and producing
wells to maximize an asset’s value at every point during its operational lifetime.
The premise of prescriptive analytics is to
take in all data – Figure 1 shows examples of shale data sets – and use the data
to predict and prescribe how to make better wells using information from the past
wells and subsurface characteristics of
undrilled acreage.
While today’s sophisticated operators and energy services companies are
adept at analyzing each of these data
a na l y t i c s
sets separately, prescriptive analytics
technology is unique in that it processes
these structured and unstructured data
sets together, and does so continually.
Since reservoir conditions are anything
but static, the machine learns from new
streams of data and updates its “prescriptions” when the data sets signal the need
for a recalibration. This adaptive environment compresses learning curves, enabling better decisions faster, with less
risk – and much less capital.
Questions worth answering
Let’s “begin with the end in mind” –
as the late Dr. Steven Covey used to say
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