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Key statistics

The identity block — every fact is canon, none is generated.

1 of 8

Track

Individual contributor

Family rungs priced

P1 · P2 · P3 · P4 · P5 · P6 · P7

19-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Entry-level petrophysicist who supports analysis of rock and fluid properties to characterize oil and gas reservoirs under guidance from experienced staff. At the Entry-Level Professional (P1) level, the role owns own tasks within a defined component, routine problems with known solutions, and drives own deliverables. None — building the craft.

What this level does

Build foundational hands-on data-acquisition experience in oil and gas exploration and development under close supervision, following defined coring and wireline logging procedures
Perform routine log quality control checks and data management tasks on wireline and LWD datasets using standard workflows
Assist in formation evaluation by loading and depth-matching well logs, core data, and seismic surveys under detailed instruction
Gain field/operational exposure involving frequent travel and communication with rig-site and operations personnel
Learn petrophysical software (Techlog, Geolog, or IP) by executing supervised interpretation steps on legacy well data

Knowledge applied: Applies foundational geology, geophysics, and petrophysics concepts and basic log-QC/data-management procedures under close instruction; learns petrophysical software (Techlog/Geolog/IP) through supervised tasks.
Complexity & problem solving: Handles routine formation-evaluation tasks with standard answers — depth-matching, load-and-QC, following defined coring and logging procedures.
Collaboration & interaction: Stable internal relationships within the subsurface team; communicates with rig-site and operations personnel during field exposure.
Typical experience: 0–1 years; new graduate or intern in geoscience/petrophysics.

Skills at this level

Log analysis, rock physics, and core-log integration: — Interprets wireline and LWD logs, calibrates them against RCAL/SCAL core measurements, and applies rock-physics relationships to derive porosity, saturation, permeability, and net pay for reservoir characterization.
Formation evaluation program design: — Plans and supervises petrophysical data acquisition — coring, wireline and MWD/LWD logging, formation pressure measurements and fluid sampling, production logging, and cement evaluation — and specifies the QC and processing sequence.
Petrophysical software proficiency: — Uses Techlog, Geolog, or Interactive Petrophysics to load, depth-match, QC, and interpret well data and compute reservoir properties; applies modules such as Quanti.Elan for multi-mineral/saturation solving.
Reservoir property uncertainty modeling: — Quantifies and propagates uncertainty in porosity, saturation, and net pay so that reservoir property ranges are correctly reflected in static and dynamic subsurface models.
Core-log data QC and management: — Performs quality control on legacy and new well datasets — depth registration, environmental corrections, tool response checks — and manages data consistency across multidisciplinary subsurface teams.
Multidisciplinary subsurface integration: — Reconciles petrophysical interpretation with geology, geophysics, and reservoir engineering inputs to build a coherent subsurface picture supporting well placement and field development.
Complex/unconventional formation evaluation: — Applies advanced methods to challenging reservoirs — thin beds, low-resistivity pay, complex lithology, and unconventionals — where standard porosity/saturation models require adaptation or novel interpretation.
Petrophysics for asset valuation and due diligence: — Translates log and core interpretation into value drivers and material technical risks for asset valuation, transactions, and strategic decisions across oil and gas and carbon-storage assets under transaction timelines.
Broader geoscience literacy: — Applies working knowledge of basic geology and geophysics to contextualize petrophysical results within depositional and structural frameworks.
Technical communication and stakeholder influence: — Presents interpretation results, uncertainty ranges, and value implications clearly to subsurface teams, executives, partners, and regulators to inform and defend subsurface decisions.
Mentorship and best-practice development: — Coaches junior and peer petrophysicists and establishes interpretation standards and workflows that raise the technical consistency of the team or organization.

Model-authored from 18 retrieved sources, then adversarially reviewed by an independent judge panel and held to a minimum-evidence floor before publication. Distinct from corpus-extracted content, which is labelled as such.

Pay across the ladder

Petrophysics — median with , by . Real canon data.

National-base pricing — this family's function differential is pending review, so dollar levels are not function-adjusted (level-over-level % is unaffected).

Pay figures are modeled estimates from our market equation — level-differentiated, with honest-wide bands. They refresh as new leveling evidence lands; treat per-role dollars as directional.

Demand — is the field growing, or just turning over?

SOC 19-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

-22.9%Geoscientists, Except Hydrologists and Geographers · United States

29,200 → 22,510 jobs

2,000 openings / year, split into:

replacement / exits 1,919

Growth — new jobs (4%)Exits — backfill (96%)

4% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +3.2%
Growth share of hiring: 4%
Exit / retention pressure high: 96%
Openings / year: 2,000

Two quantities, kept apart: observed = employment growth differenced from two BLS OEWS vintages (what already happened); projected = BLS Employment Projections 2024–34, openings decomposed into growth + exits (growth derived from projected employment change). Neither is a pay figure.

Where this role sits — growth vs. pay

level P1 held

Demand axis is projected growth (not raw openings — that just measures churn). A curated, de-duplicated set of recognizable occupations held at this level; this role is highlighted.

Where it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$101k

San Francisco-Oakland-Fremont, CA$90k

Washington-Arlington-Alexandria, DC-VA-MD-WV$83k

Boulder, CO$82k

Seattle-Tacoma-Bellevue, WA$82k

Boston-Cambridge-Newton, MA-NH$79k

Lexington Park, MD$77k

Trenton-Princeton, NJ$76k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $60k; the demand-cube initiative will add growth-by-metro.

What changes across the ladder

Level-distinction canon isn't available for the adjacent levels of this profile yet.

Level differentiators

What separates P1 (P1 — Entry-Level Professional) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Own tasks within a defined component
Autonomy: Close supervision; work reviewed frequently
Complexity: Routine problems with known solutions
Impact: Own deliverables
Decision rights: Few independent decisions; escalates the rest
Leadership: None — building the craft

Full level-by-level matrix (side by side across the ladder) lives on the Ladder drill-down — not here.

Promotion

The next rung from P1 is P2.

Performance criteria for this profile render in the assessment kit →

People also watch

Nearest coordinate neighbors — same , same level. Each row's (confident / review / no match) comes from its — computed, not curated.

Profile	Key	Median	Δ structural
VP of Petrophysics	jf_petrophysics::E1	$169,459†	confident0.06
Petrophysics Supervisor	jf_petrophysics::M1	$85,619†	confident0.06
Petrophysics Technician	jf_petrophysics::S1	$37,323†	confident0.06
Petrophysicist	jf_petrophysics::P2	$72,357†	confident0.06

†National-base pricing — this family's function differential is pending review, so the dollar level is not function-adjusted.

Capability cluster

O*NET 19-2042

Core to this role. Click any element with an ⓘ for its O*NET definition. A job-specific capability model (SkillFrame) will sharpen this and add worked examples.

The Job Swatch

P1

jf_petrophysics::P1

Associate Petrophysicist

Petrophysics

The swatch is JobFrame's core primitive: a hueset deterministically by the role's superfunction, the profileKey as its color code, the level ladder, and a content fingerprint. Two swatches that look alike are alike.

Because every role carries computable coordinates, similarity, leveling, and pricing become measurable instead of arguable— the whole point of "Pantone for jobs."

Structural

structural@1

Where it sits— position in the work taxonomy + level (weighted Gower, level > function > focus).

Track: P
Superfunction: industrial_energy_operations
Function: geoscience
Family: petrophysics
Universal level: 1 / 8

Content

content@2

What it's about— a fingerprint over the role's tasks & capabilities.

Two roles can sit far apart structurally yet be close in content — that gap is itself a signal.

3-state matching

How any two swatches compare — a real distance in coordinate space, resolved to a calibrated verdict (never a fake "94% match").

Geology · P1review0.17

Geomatics · P1review0.17

Geophysics · P1review0.17

Geothermal · P1review0.17

Technologist · P1review0.17

Editions — frozen & versioned

structural@1live

Released 2026-06-17

content@2live

Released 2026-07-28

pay@2live

Released 2026-07-02

semantic@1live

Released 2026-07-02

Coordinates belong to a frozen, versioned edition — a coordinate computed today still means the same thing next quarter. Re-fitting issues a new edition, so comparisons are never silently redefined.

How to read this profile

Every number here is traceable — to a named source, a stated method, and an as-of date — and each value is labeled by how we know it: observed from data, computed by a model, projected forward, or governed canon. Nothing is a black box, and nothing is invented to fill a gap.

Where every number comes from

What	Source & method	Edition	State
Median pay + range	JobFrame pay equation (function base × family multiplier × level × focus differential)	pay@2	computed
Pay across the ladder	Same equation applied at each universal level	pay@2	computed
Demand — growth & openings	BLS Employment Projections; openings decomposed into growth + exits	EP 2024–34	projected
Pay by metro	BLS OEWS metropolitan medians	OEWS 2024	observed
Level distinctions	JobFrame universal-level canon (scope · autonomy · complexity · impact · decision rights · leadership)	canon	canon
Capability cluster	O*NET Knowledge / Skills / Abilities	O*NET 19-2042	computed
Coordinates	JobFrame coordinate system — structural (weighted Gower) + content fingerprint	structural@1 · content@2 · pay@2 · semantic@1	computed
Related roles	Nearest neighbors in the structural coordinate space	structural@1	computed

The principles behind the numbers

Ranges, not false precision

Pay is P10 · median · P90, never a single misleading number.

Three honest states, never a fake %

Role matches resolve to confident / review / no-match — a calibrated verdict, not a made-up percentage.

Provenance on every value

Each number carries whether it's observed, computed, projected, or canon — so you always know how much to lean on it.

Gaps shown as gaps

When a figure isn't available at the grain you need, we say so — we don't fabricate a number to fill the cell.

Frozen, versioned editions

Pay and coordinate editions are pinned, so a comparison you make today still means the same thing next quarter.

Privacy by min-N

Any aggregate over people is suppressed below a minimum count, so no individual is identifiable.

Freshness

As of2026-07-30Editioncanon-v2@2.1.0-completeSourcecanon-v2 cell + salary-benchmark (model)