American Oil and Gas Reporter - November 2017 - 52

ponents, which when assembled together,
offer a robust set of integration, protocol
and storage options.
Data Integration
Integration platforms give companies
the flexibility to change the format and
destination of any piece of data at any
time. Many companies struggle initially
with uncertainty about where all the data
will be stored, and this hesitation results
in the failure to collect enough data to
make analysis meaningful. Analytics platforms address this problem by enabling
connectivity between disparate data
sources, making it unnecessary to choose
one (and only one) database technology
like building a single enterprise data
warehouse. This approach is simply not
required anymore.
Data acquisition, storage and integration
are links along the energy information
value chain. Data models define the relationships between many structured and/or
unstructured data elements. It is important
to understand that data models can, and
should, change as new discoveries are
made. Yet, they do have to start with a
project and a reason to justify their creation. Adequate documentation around
the model and the metadata around each
data element should be at the core of any
new project. Models should be built
around each area of the business through
a process of:
* Defining the project;
* Collecting the data;
* Analyzing and evaluating the data;
* Building a model; and
* Deploying the model.
Today, most companies can gain
tremendous benefits from connecting data

silos, providing visibility into the basic
relationships that are already known to
exist, such as vendor and cost. It is not
surprising that technology leaders over
the last decade dominate in machine
learning and artificial intelligence platforms. IoT and the potential value created
by the petabytes of data streaming from
billions of these devices is why these
leaders are advancing the platforms and
tools to eliminate the barriers to entry
into this cutting-edge field.
Unified Value Chain
The ability to automate, integrate, collaborate and optimize operations through
a single unified value chain that integrates
innovative solutions based on an open
standards-based platform is the key to
empowering oil and gas companies to
conquer complex business challenges
across the entire value chain, from land
acquisition to the back-office.
From the beginning of the land acquisition phase in a new basin, companies
must efficiently document, catalog, prioritize and value their leaseholds and
mineral rights. As market conditions
change, exploratory wells are tested and
field development begins, creating "data
silos" that are difficult to overcome in
many corporate software ecosystems.
With disparate and disconnected systems, market volatility masks the problem
when prices increase and leaves executives
scrambling for answers when prices rapidly decline. There are many analytical
and data services available that utilize
public and internal sources of data to
provide visibility to land availability and
drilling activity.
Once the assets have been acquired

Finding, drilling, completing
and producing oil and gas
wells is capital intensive. Big
data and analytics are being
leveraged as building blocks
for enterprisewide upstream
and midstream activities. By
integrating data from all areas
of oil and gas operations with
IoT and cloud computing-and
bringing them together in new
ways with analytics, big data
and machine learning-these
technological
components
form the basis of a connected
energy intelligence business
model.

52 THE AMERICAN OIL & GAS REPORTER

and field development begins, a real-time
field development engine continually can
evaluate and refine reserves, revalue assets,
and even alter development plans as conditions are met and milestones achieved.
In the world of IoT, data streams are already available that provide each department with the real-time data it needs, but
rarely provide value to any other organization unit.
During the land acquisition phase in a
newly discovered basin, there is often an
emotional component to land deals, and
time is typically the only means of placing
true value on each deal. Through artificial
intelligence technologies such as cognitive
and natural language interpretation, all
emotion can be removed by applying an
objective score. Scoring can be done by
gathering inputs, scanning the lease with
a mobile device, and processing the
content of each page gathered.
When commodity prices drop rapidly,
companies that make better and faster
decisions will be positioned to widen the
gap between them and the rest of the
market, especially when capital budgets
get cut. With the scoring system in place,
connecting the dots to identify assets
with the lowest objective score should
be the first data sent to the data room.
Data produces information that can be
used to provide the acquisition and development roadmap given current and
expected market conditions.
Drilling And Completions
Finding, drilling and completing oil
and gas wells is extremely capital intensive.
As companies strive to improve production
output and extend the life of their assets,
it is not surprising that big data and analytics already are being leveraged to optimize these core activities.
Data models use hundreds, sometimes
even thousands, of controllable inputs:
drilling location, depth, fracture stages,
lateral length, proppant type and amount,
pump pressures and rates, etc. The drilling
process no longer consists of a toolpusher capturing drilling depth on a paper
sheet. Data streaming is the "new normal,"
where fiber optics are used to sample
hundreds of sensors every few seconds
and gather rates, pressures, weight, torque,
molecular composition of gas captured,
etc. It is now common for a drilling engineer in Houston to remotely monitor
drilling activity in Pennsylvania.
Companies that continue to push for
improvements are building their field
development plans and designing their
drill sites and completions long in advance, often using predictive analytics.
If the wrong decision is made while the
bit is in the ground, additional costs and

American Oil and Gas Reporter - November 2017

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