Our platform enables your team to execute a series of
workflows covering several disciplines for large volumes
of data—such as a facility maintenance initiative—all in
a single interface.
Powered by deep learning for computer vision and natural language understanding, our machine learning models are able to understand and extract context from your unstructured data. This enables you to combine it with your structured data to generate a comprehensive view of your digital and physical assets.
You decide whether your project requires a particular module, a workflow capsule (several modules linked together), or an entire System of Intelligence. Stack capability as your goals and process require.
Deploying IIOT infrastructure,
RCM software, and other initiatives for your facilities?
You might be missing a critical element. When a
processed vibration signal predicts a compressor might fail,
you’ll need to know where that compressor is located,
what other equipment is connected to it,
and what spare parts were needed in the past.
That information provides the necessary context for intelligent decision making, and it may be locked in scanned engineering drawings, purchase orders, and maintenance reports. The Facility Maintence SOI creates that essential context through a package of natural language understanding and computer vision technologies to classify engineering drawings, retrieve instrument tag data from P&IDs, fingerprint all of your documents, and more.
Most long-standing O&G companies
have many shelved, bypassed and near field
opportunities hidden in document, log, seismic and
production data repositories. Uncovering them, however,
typically requires lengthy processing of old typewritten
documents, multidisciplinary analysis, root cause analysis,
and so forth. For each discovered opportunity, it’s
necessary to run a screen from then to now to check
if it was subsequently exploited. Attempting to do
all of this in a predominantly manual workflow may
require many tedious man-years of work.
Machine-based Exploitation (MBX) uses a mix of machine learning technologies to systematically work through this plethora of analytical steps in a fraction of the time it would take a large team of human experts. All uncovered opportunities are classified as Fast, Intermediate or Slow Hydrocarbon (FISH) depending on their accessibility. MBX allows you to quickly add hundreds or thousands of barrels to your production in a fraction of the time required by conventional methods.