Jordan Reiser

Top 5 Oil Client

AI ENABLED OIL OPERATIONS SCENARIO BUILDER​

Problem Overview

I conceived and designed a tool for oil engineering operations experts that rely on: user defined inputs, machine learning, and algorithmic processes (to produce optimal drilling conditions), fracking, and production schedule options over 50-year time periods.  Each scenario considers key economic factors and is displayed automatically through a combination of outputs such as drilling sequence schedules, predictive economic and oil production forecasts, event labeled maps, and impact forecasts for connected networked facilities. The engineer is able to review, select, modify, and collaborate on their preferred sequence scenario to promote and share with key executive decision makers resulting in a dramatic reduction in approval time.

Prototype can be shown upon request.

Solution Method

Facility Spend Savings
$ 0 M
every 30 years
Worker Time
$ 0 K
saved / year
UX and Development Efficiencies
0 %
time savings due to UX agile integration

The story

Research Discovery

Engineers had been leveraging outdated, legacy scheduling planning and operational methods for oil production. After educating myself on nuances of this company and the industry at large, I conducted in depth stakeholder interviews and documented comprehensive system and interface requirements.

Define & Design

This stage was approached through story driven, product development. Once I had an understanding of the needs and had identified personas, I created a narrative flow by using a feature story map. The map was then used to breakdown jobs into component parts in order to transform them into user stories which were handed off to the development team.

Design Prototype & Build

Using a dual track, agile approach, UX and development collaborated on a number of design tasks. I used a rapid prototyping tool entitled UX Pin to create a slick and reality-based experience so that developers and stakeholders could better understand what was to be built, a component at a time. Pictured here is the sequencer component.

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Additional design assets can be produced upon request.