L1 ⚛ L1-460 ⊙ Testnet

Reservoir History Matching

Petroleum Engineering · Inverse modeling

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Layer template

⬇ principle.md ⬇ principle.json

Fork L1-460

⬇ L1-460.md ⬇ L1-460.json

Prompt — copy into your LLM

You are helping me submit a MODIFICATION of L1-460 (Reservoir History Matching) to the PWM Protocol — a Principle (L1) artifact.

I will paste a Markdown template (or the current L1-460.md).
1. Rewrite the Markdown so the science is correct and clearly explained for my change.
2. Regenerate the sibling L1-460.json so EVERY field matches the Markdown.
3. Keep the schema in the "File Mapping" footer at the bottom of the MD.
4. Keep the parent reference unchanged unless I ask otherwise.
Rules: the Markdown is the source of truth; use SI units; do NOT invent benchmark scores.
Output each file in its own fenced code block tagged with the filename.

Here is my template:
[PASTE THE .md HERE]

⚙ Forward Model

y = `O.misfit.production` x

world state x (3D permeability field)

→

O · misfit · production `O.misfit.production`

→

observation y (acoustic detector)

Noise: observation gaussian

Solver / auxiliary components (2)

S.ensemble.kalman_filter_reservoir — S · ensemble · kalman filter reservoir operator
O.iter — a fixed-point or gradient iteration on the unknown

Markdown — human-readable source of truth

⚙ auto-generated

⬇ L1-460.md

# ⚛ L1 Principle — Reservoir History Matching **ID:** `L1-460` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Petroleum Engineering — *Inverse modeling* > **🎯 Problem class:** nonlinear inverse · **🧮 Solution space:** 3D permeability field > **📡 Carrier:** acoustic · **🌫 Noise:** observation gaussian > **⚖ Difficulty (δ):** 10 · **⛓ Block:** 41555279 --- ## 🧠 1. Introduction **Reservoir History Matching** is a **nonlinear inverse problem** whose unknown lives in **3D permeability field** space, within the **Inverse modeling** sub-domain of **Petroleum Engineering**. Measurements consist of acoustic pressure waves recorded by transducers via a **reservoir production data matching** sensing mechanism. The forward operator applies, in order: S · ensemble · kalman filter reservoir operator; a fixed-point or gradient iteration on the unknown; O · misfit · production operator. Observations are corrupted by observation gaussian. Existence of the recovered 3D_permeability_field is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 100000.0); structural_uncertainty dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Observation gaussian sets the irreducible data-fidelity floor. ## ⚙ 2. Forward Model Physical chain: **x** → O · misfit · production → **y** (detector). ``` y = `O.misfit.production` x ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `O.misfit.production` | O · misfit · production operator | **🛰 Estimator components** _(used inside the solver, not in the forward equation)_: | Primitive | What it does | |---|---| | `S.ensemble.kalman_filter_reservoir` | S · ensemble · kalman filter reservoir operator | **🛠 Solver components** _(used inside the solver, not in the forward equation)_: | Primitive | What it does | |---|---| | `O.iter` | A fixed-point or gradient iteration on the unknown | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Petroleum Engineering | | Sub domain | Inverse modeling | | Carrier | acoustic | | Problem class | nonlinear_inverse | | Solution space | 3D_permeability_field | | Noise model | observation_gaussian | | Integration axis | production_history | | Difficulty delta | 10 | | L dag | 5 | ## 📡 4. Measurement Model Existence of the recovered 3D_permeability_field is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 100000.0); structural_uncertainty dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Observation gaussian sets the irreducible data-fidelity floor. | Metric | Value | |---|---| | Metric | production_NRMS_match | | Secondary | permeability_uncertainty_reduction | ## 📏 5. Operating Range (Ω) **Center problem class:** `nonlinear_inverse` · **Forward operator:** `reservoir_production_data_matching` **Center point:** | Parameter | Unit | Value | |---|---|---| | N cells | — | 50000 | | N wells | — | 20 | | N ensemble | — | 100 | | Production years | — | 30 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | N cells | — | 1000 – 500000 | | N wells | — | 5 – 100 | | N ensemble | — | 50 – 1000 | | Production years | — | 5 – 60 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 0.10 production_NRMS_match | Metric | Range | |---|---| | Production nrms match | 0.02 – 0.5 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **production_NRMS_match**, with κ = `100000000.0` and δ = `10`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0x7caf924efbe92b76a31b36174184241d0f295450540d95438b24d73f186c47df` - **Chain tx hash:** `0x45cdbbb49e8fdd172d82ab435f6c6311aaf36df7a436e9cde979c6e1d470ba74` - **Chain block:** `41555279` --- ## File Mapping This bundle consists of: `L1-460.md`, `L1-460.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-460.md` | Source of truth — edit this | Human or LLM | | `L1-460.json` | Structured metadata for the registry | LLM regenerates from the sections above | **Prompt for your LLM after editing this Markdown:** > Read the attached Markdown. Regenerate the sibling `.json` so every field matches. > Preserve the schema documented in the rows above. > Output each file in its own fenced code block tagged with the filename. > Output only the JSON object. _This Markdown was auto-synthesized from the catalog row for `L1-460`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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⌥ Hierarchy

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L2-460-001 Reservoir History Matching — Nominal + Mismatch Specs

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📋 JSON metadata

{
  "artifact_id": "L1-460",
  "chain_block": 41555279,
  "chain_hash": "0x7caf924efbe92b76a31b36174184241d0f295450540d95438b24d73f186c47df",
  "chain_tx_hash": "0x45cdbbb49e8fdd172d82ab435f6c6311aaf36df7a436e9cde979c6e1d470ba74",
  "domain": "Petroleum Engineering",
  "hardness_fn": {
    "delta": 10,
    "kappa": 100000000.0,
    "metric": "production_NRMS_match",
    "type": "epsilon_fn"
  },
  "initiator_dataset": [
    {
      "ipfs_cid": null,
      "license_hash": null,
      "name": "primary",
      "weight": 1.0
    }
  ],
  "layer": "L1",
  "observable_profile": {
    "metric": "production_NRMS_match",
    "regime": "Existence of the recovered 3D_permeability_field is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by declared priors. Stability is conditionally stable (kappa_eff ~= 100000.0); structural_uncertainty dominates the stability cliff; the remaining mismatch parameters contribute higher-order bias terms. Observation gaussian sets the irreducible data-fidelity floor.",
    "secondary": "permeability_uncertainty_reduction"
  },
  "physics_fingerprint": {
    "L_DAG": 5.0,
    "carrier": "acoustic",
    "difficulty_delta": 10,
    "domain": "Petroleum Engineering",
    "integration_axis": "production_history",
    "noise_model": "observation_gaussian",
    "primitives": [
      "S.ensemble.kalman_filter_reservoir",
      "O.iter",
      "O.misfit.production"
    ],
    "problem_class": "nonlinear_inverse",
    "sensing_mechanism": "reservoir_production_data_matching",
    "solution_space": "3D_permeability_field",
    "sub_domain": "Inverse modeling",
    "title": "Reservoir History Matching"
  },
  "size_tiers": {
    "allowed_forward_operators": [
      "reservoir_production_data_matching"
    ],
    "allowed_omega_dimensions": [
      "N_cells",
      "N_wells",
      "N_ensemble",
      "production_years"
    ],
    "allowed_problem_classes": [
      "nonlinear_inverse"
    ],
    "center_spec": {
      "epsilon_fn_center": "0.10 production_NRMS_match",
      "forward_operator": "reservoir_production_data_matching",
      "input_format": "measurement_only",
      "omega": {
        "N_cells": 50000,
        "N_ensemble": 100,
        "N_wells": 20,
        "production_years": 30
      },
      "problem_class": "nonlinear_inverse"
    },
    "epsilon_bounds": {
      "production_NRMS_match": [
        0.02,
        0.5
      ]
    },
    "omega_bounds": {
      "N_cells": [
        1000,
        500000
      ],
      "N_ensemble": [
        50,
        1000
      ],
      "N_wells": [
        5,
        100
      ],
      "production_years": [
        5,
        60
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Inverse modeling",
  "title": "Reservoir History Matching"
}

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