ShiftLedger.

Matthew worked as a stimulation technician on a crew that alternated shifts with another. After one handover, a costly mistake surfaced on the following shift: a miscalculation, and steps in the protocol that were not followed, in his account. The company had no way to show who had done what and when. Both technicians were written up.

He was disciplined for something that was not his. That stayed with him. The point was never to shift blame onto someone else. It was that a clear record protects everyone: the person who did the work right, the person who needs help doing it better, and the company that has to know what actually happened.

A problem he found, and built the fix for

Matthew did not stop at being frustrated. He treated the gap as a problem to solve: what record would have settled this in minutes? He worked out what a crew actually needs at each handover, then built ShiftLedger around it. That is how he approaches most things: find where work breaks down, name the cause, and build the simplest thing that fixes it for the next person.

Built by someone who has worked the whole job

Matthew has worked in the oilfield since 2010. That experience covers fracturing, cementing, acidizing, coil tubing and chemical stimulation; pump, blender, sand and bulk equipment; data acquisition and chemical inventory; well-stage pricing and job tickets; safety training and crew leadership; and coordination with drilling teams, customers and vendors. He also holds a Bachelor of Business Administration in Finance from Sam Houston State University, so he looks at each workflow in terms of cost, documentation and billing as well as operations.

What the record would have shown

• Who recorded what, and when. Every entry carries the person, the time and, for anything entered on someone’s behalf, a reason.
• What was handed over. The stage record has to be acknowledged before the stage starts, and the close-out packet states what was acknowledged and what was flagged.
• What changed afterward. Corrections never overwrite; the original stays, with who changed it and why.
• Where the gaps were. Missing time, uncovered shifts and open follow-ups surface early, before they become a disagreement.

Beyond one crew

Companies also need a fair, consistent way to see productivity and accountability across crews, locations and departments. A shared record lets supervisors, finance, safety and operations answer the same questions from the same facts. A record cannot decide what went wrong, and it does not replace judgment or a proper investigation. It makes sure the investigation starts from what happened.

This account is Matthew’s own, told in general terms. It names no employer or coworker, and none of it is a statement about any specific person’s conduct.

• Accountability: job, crew, employee and equipment references; separate recording, performing and review roles; due dates and assigned follow-ups.
• Evidence: sample source references and retained reading corrections. Missing data remains visible rather than silently becoming zero.
• Location context: fixed fictional planned-site coordinates linked to well, rig reference, frac spread and equipment. These are not live personnel or equipment positions.
• Trends: a separate 14-day fixture shows both improving and regressing measures, with dates, sample counts, denominators and exclusions.
• Documents: draft shift and management reports, plus JSON, history CSV and GeoJSON exports.

The UI uses HTML, CSS and JavaScript. Reconciliation and management calculations run on the server. A separate sample API serves the fictional preview without exposing calculation source.

The current snapshot passed 61 automated checks, including calculation edge cases, report aggregation, input validation, source exposure, protected-route access, and preview boundaries. Browser checks covered opening the preview, editing a reading, job filtering, inspecting personnel/source details, and the pump service-to-review workflow with a newer record requiring review.

Stage console (added)

A second, fully on-site simulation covers data-van style duties with fictional data: parameters recorded and acknowledged by a simulated Performance Center before a stage can start (with store-and-forward when the link is down), threshold alerts, vendor delivery risk against the stage schedule, and a root-cause evidence checklist with named owners. Open the stage console. It is not connected to equipment.

Crew time (added)

Supervisors schedule crews to locations, crew submit their own time (or clock in and out), and a supervisor can enter missed time with a recorded reason. Corrections never overwrite: the original stays in the record. Each audience gets its own view. Open crew time. It records hours only, not pay.

What this project demonstrates

Domain knowledge translated into a working product: the right fields, meaningful ownership, visible exceptions, and information that supports a decision. Matthew’s contribution centers on understanding the work and the problems worth solving.