neqsim-reservoir-material-balance

neqsim-reservoir-material-balance is a skill for Claude Code, Codex from equinor/neqsim-community-skills. It costs 94 tokens per session (2,253 once invoked), scanned A, original, Apache-2.0.

A reservoir material-balance analysis workflow for estimating oil or gas initially in place from pressure and production history. Material balance is a tank-level screening method, not a detailed spatial reservoir simulation or reserves classification.

In plain words
What is it for?
Use it to estimate GIIP or OOIP, separate pressure compartments, compare drive mechanisms, and assess uncertainty or whether the available data can identify a reliable volume.
Why use it?
It helps compare or reconcile volume estimates and test whether pressure and production data support assumptions about depletion, gas caps, water influx, or compressibility.

Skill for Claude CodeCodex

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

Good fit Use it to estimate GIIP or OOIP, separate pressure compartments, compare drive mechanisms, and assess uncertainty or whether the available data can identify a reliable volume.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/equinor/neqsim-community-skills/neqsim-reservoir-material-balance
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-reservoir-material-balance
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-reservoir-material-balance

README.md
[![agentmods](https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-reservoir-material-balance/github.svg)](https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-reservoir-material-balance)
Your own site
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-reservoir-material-balance"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-reservoir-material-balance/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-reservoir-material-balance

Your own site · 80×15
<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-reservoir-material-balance"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-reservoir-material-balance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,253 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 $0.00094 $0.02253
Opus 5.5 $0.00038 $0.00901
Sonnet 5.5 $0.00019 $0.00451
Haiku 4.5 $0.00009 $0.00225

Measured 5d ago against content hash 9e5604a40d25, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

neqsim-reservoir-material-balance 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.

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-reservoir-material-balance/SKILL.md · 183 lines

How it starts

The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Reservoir Material-Balance Analysis

Use pressure and cumulative production to test an in-place-volume hypothesis. This is a tank-level screening method, not a spatial reservoir simulator or a reserves classification.

When to Use

  • Estimate or reconcile gas initially in place (GIIP), original oil in place (OOIP), or total surface-component inventories from pressure and production history.
  • Compare a prior volumetric estimate with a pressure-production material balance.
  • Test depletion-drive, gas-cap, known-water-influx, or known-compressibility cases.
  • Separate formations or pressure compartments before matching a field total.

For compositional gas-condensate depletion, produced composition, or wellstream forecasts, use neqsim-reservoir-history-match-forecast. Use both workflows only when their fluid and volume bases are explicitly reconciled.

Inputs

  • Dated static/average reservoir pressures, including test type, depth, unit, datum, source and correction provenance.
  • Formation-allocated cumulative production and injection for oil, gas and water on one declared surface-volume basis.
  • Initial and pressure-dependent PVT, initial pressure and temperature, and relevant rock/fluid compressibilities.
  • Supported formation/tank boundaries, pressure communication evidence, and gas-cap/aquifer inputs where applicable.
  • Prior in-place estimates and their date, range, volumetric/PVT basis and allocation assumptions.

Outputs

  • In-place volumes and units by tank and supported model case.
  • Pressure/volume residuals, fit diagnostics and identifiability warnings.
  • Cumulative production, injection, aquifer influx and drive contributions on a consistent basis.
  • Sensitivity range, comparison with the prior estimate, data gaps and discriminating next evidence.

Required Evidence

Before fitting, assemble one time-aligned history per candidate tank:

  • Static or otherwise justified average reservoir pressure with date, wellbore, test type, gauge depth, pressure unit, datum, source, quality and correction method.
  • Cumulative oil, gas and water produced and injected, on one declared surface-volume basis. Keep the formation allocation and its uncertainty; a field total is not automatically a formation history.
  • PVT at initial conditions and at each pressure observation: pressure, Bo, Bg, Bw, Rs and Rv as applicable, with units, standard conditions and separator basis.
  • Initial pressure, temperature, formation/water compressibility and saturation assumptions.
  • Formation and pressure-compartment mapping, well completion intervals, shut-in/stabilization status, and evidence for or against pressure communication.
  • The previous in-place estimate, estimate date, range, and the pore-volume, saturation, PVT and allocation basis used to calculate it.

Read the full file on GitHub · 183 lines

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 · 183 lines · 94 tokens per session scan A 9e5604a40d25

Subscribe to this mod's changes

neqsim-reservoir-material-balance is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed today), licensed Apache-2.0. It adds 94 tokens to every session and 2,253 once invoked, about $0.0004 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.

Related

neqsim-reservoir-material-balance compared with skills from other repositories

neqsim-reservoir-material-balance next to 6 skills from other repositories
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