Halliburton
Well interaction analytics an operator mid-frac can act on at a glance.
Halliburton Project Lead
Pilot data visualizations of intelligent well interaction analytics to improve safety and efficiency.
Design Director. Led a four-person distributed team across San Francisco, Austin, New York and Mexico City, and took the lead IXD/UX seat early in the sprint to hold the schedule.
Employment: frog, a Capgemini Invent company. Deliverables: three interaction models and the integrated model chosen · interaction design and design notes · design system extension · 2D and 3D interface designs · Voice of Customer validation findings. Files modified to preserve confidentiality.
Challenge
Challenge
Halliburton was building a new generation of hydraulic fracturing analytics software and wanted real-time and predictive well interaction analytics — what happens between well bores during a frac — added as a feature. Our team had eight weeks to define, design and test it.
Well interaction is invisible and it moves fast. A pressure breach in one well bore can mean trouble in a neighboring one, and the operator needs to know that a threshold has been crossed, how many wells are affected, and whether to intervene — in a glance, not a reading. Numbers on a dashboard don't do that. The data existed. The open question was whether an operator mid-frac could act on it.
Solution
Four cities, two companies, one feature. The risk isn't disagreement. It's drift.
We started with a rapid immersion into the energy industry: six previous Halliburton engagements to draw on, plus stakeholder interviews and online research. We presented three interaction models. Halliburton chose all three, so we integrated them into a single model and iterated with their team.
A UX designer and a client engineering team can both build from the same screen and still ship two different behaviors, because a static comp doesn't say what happens when the state changes. So I set the interaction direction and wrote the design notes everything was built from: the specific behavior of every indicator in every state, including the states nobody had drawn yet.
The client team worked in the Figma file alongside us, so requirements and design progress were a daily conversation rather than a weekly reveal. Every Friday I ran Voice of Customer validation sessions with current Halliburton customers. What we heard on Friday changed what we prioritized on Monday.
Result
Outcome
The integrated model went into Halliburton's product development. My design notes let the build proceed without rework. An additional engagement was scheduled for the next phase: the 7th frog project with Halliburton.
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