Meana Petro
DR-07IntermediateWave 3AIDomain

Drilling Fluid Design Optimization

In one sentence

Recommends the mud formulation for the next section based on what worked in comparable sections, and what it cost.

The problem

Mud programmes are inherited from the last well and adjusted by habit. The link between a rheology choice and the hole-cleaning or stability outcome is rarely quantified after the fact.

Fluid is one of the three largest line items on a well AFE, and additive spend is where most of the waste sits.

How it works

A case-based model matches the planned section against historical sections by lithology, angle, hole size and temperature, then ranks the fluid systems used by their measured outcome: stability events, hole-cleaning index, dilution volume and total additive cost.

Recommendations are presented as a comparison table with the evidence behind each, not as a single prescriptive answer.

Data required

  • Historical mud reports with full rheology, solids and additive consumption
  • Section outcomes: losses, stability events, stuck events, dilution and discard volumes
  • Offset lithology and temperature profiles
  • Additive pricing from the supply contract

What you get

  • Ranked fluid system options with expected cost and risk for the planned section
  • Additive consumption forecast and a dilution plan
  • Post-section reconciliation of planned versus actual fluid cost

What it cannot do

The model is only as good as the mud reporting discipline in the archive, which in most operators is weak: additive volumes are frequently reported to the nearest sack and dilution is under-recorded. We assess the archive before committing to a confidence level, and in several fields the honest answer has been that the data does not support this capability yet.

Every capability page states a real limitation. If a vendor cannot tell you where their product stops, you are not being told the truth about where it starts.

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