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neqsim-well-design-study

neqsim-well-design-study is a skill for Claude Code, Codex from equinor/neqsim-community-skills. It costs 117 tokens per session (4,518 once invoked), scanned A, original, Apache-2.0.

A screening workflow for designing and documenting oil, gas, gas-condensate, water-injection, or gas-injection wells. It checks pressure limits, casing and tubing choices, drilling loads, time and cost ranges, barriers, and supporting evidence.

In plain words
What is it for?
Use it to compare casing programmes, check kick tolerance and drilling feasibility, review offset-well evidence, screen torque, drag and equivalent circulating density, and prepare a well-plan report.
Why use it?
It helps expose design conflicts and uncertainty before a detailed well-design tool or specialist review. It makes clear that the result is a concept-stage study, not final or safety-critical design.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 4repo today A scan 117 tokens original Apache-2.0

Good fit Use it to compare casing programmes, check kick tolerance and drilling feasibility, review offset-well evidence, screen torque, drag and equivalent circulating density, and prepare a well-plan report.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/equinor/neqsim-community-skills/neqsim-well-design-study
View source ↗ equinor/neqsim-community-skills equinor.github.io
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add equinor/neqsim-community-skills --skill neqsim-well-design-study
Clone the repo
git clone --depth 1 https://github.com/equinor/neqsim-community-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for neqsim-well-design-study

README.md
[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-well-design-study/github.svg)](https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-well-design-study)
Your own site
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-well-design-study"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-well-design-study/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for neqsim-well-design-study

Your own site · 80×15
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-well-design-study"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-well-design-study.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 117 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,518 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00117 $0.04518
Opus 5.5 $0.00047 $0.01807
Sonnet 5.5 $0.00023 $0.00904
Haiku 4.5 $0.00012 $0.00452

Measured 5d ago against content hash 0cb212dc11ea, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

neqsim-well-design-study scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

The scan reads SKILL.md. This mod also ships 20 executable files (examples/example_study.py, examples/example_wellplan.py, src/well_design_study/__init__.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/subsurface/neqsim-well-design-study/SKILL.md · 159 lines

How it starts

The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Well Design Study

A reusable, offset-well-aware workflow for a screening well design study and its report. It turns a pressure basis, a planned (or proposed) casing programme and offset-well evidence into a checked design: window and seats, casing strings, completion screening, drilling feasibility, time and cost range, a standards register and a validation list. Detailed design stays in the operator's well-design and casing-design software; this skill frames the concept, checks a design that already exists in those tools, and prepares the evidence and the report.

When to Use

  • Exploration, appraisal or development well at concept or pre-FEED stage needs a casing programme, kick-tolerance check, time and cost range or a design report.
  • A planned programme (for example a "dry case" and a "discovery case" design) must be sanity-checked against offset-well strength tests and mud weights.
  • A reservoir fluid and well deliverability model needs a tubing, wellhead and barrier basis (see neqsim-subsea-and-wells, neqsim-near-well-and-injectivity).
  • Do not use it for final design, rig selection, safety-critical or regulatory work, relief-well or HPHT qualification.

Inputs

  1. Reference: RKB elevation (air gap), water depth, TD (MD, TVD), vertical or deviated path, target and fluids.
  2. Pressure basis: pore (low/base/high) and fracture (low/base/high) EMW curves against TVD. Build them from the prospect estimate (reservoir pressure, depth, regional trend) and calibrate to offset wells (calibration_points, envelope).
  3. Planned programme: sections with hole size, casing OD, top and shoe TVD/MD, mud weight, top of cement, grades to try.
  4. Kick basis: kick intensity (sg), influx density (sg), required kick tolerance (m3).
  5. Offset evidence tables (CSV in one folder, filled from public regulator data and well reports or by hand): offset_casing_lot.csv, offset_mud_weight.csv, offset_pressure_temp.csv, offset_time_depth.csv, offset_problems.csv, offset_documents.csv.
  6. Completion basis (producer): shut-in wellhead pressure from the NeqSim fluid and reservoir pressure, tubing candidates, rates, packer fluid, maximum temperature.

Read the full file on GitHub · 159 lines

Files

What ships with it

22 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 159 lines · 117 tokens per session scan A 0cb212dc11ea

Subscribe to this mod's changes

neqsim-well-design-study is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed today), licensed Apache-2.0. It adds 117 tokens to every session and 4,518 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-11-01.

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