People Analytics Toolbox

Ask about this role

grounded in this role's JobFrame record + structure

Download this job's description (markdown) → derived live from this record.

Key statistics

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

7 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

The foremost individual-contributor authority on petrophysical science, setting technical direction for rock and fluid property analysis across the entire organization. At the Staff / Distinguished Professional (P7) level, the role owns cross-organization / enterprise technical strategy, industry-level, highly ambiguous problems, and drives enterprise-wide. Sets technical direction org-wide; develops principals.

What this level does

Set long-term petrophysical technical direction for the company and shape industry practice, anticipating emerging challenges in unconventional and carbon-storage characterization
Solve precedent-free formation evaluation problems with broad business and industry consequences, pioneering interpretation techniques that raise the ceiling for the discipline
Advise executives, boards, and regulators on subsurface resource, risk, and value across the full portfolio
Publish, patent, or otherwise advance formation evaluation methodology, establishing standards adopted beyond the organization
Provide high-level mentorship to senior and principal petrophysicists, building company-wide subsurface capability without necessarily holding direct reports

Knowledge applied: Advances the discipline — pioneers formation-evaluation methodology through publication, patents, or new interpretation techniques adopted beyond the organization.
Complexity & problem solving: Solves precedent-free problems with company-wide and industry consequences; anticipates emerging challenges and defines long-term technical roadmaps.
Collaboration & interaction: Networks with executives, boards, regulators, and industry leaders; persuades senior stakeholders on strategic subsurface priorities.
Typical experience: 20+ years or equivalent recognition; often PhD with significant industry contributions.

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 P7 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$376k

San Francisco-Oakland-Fremont, CA$337k

Washington-Arlington-Alexandria, DC-VA-MD-WV$312k

Boulder, CO$308k

Seattle-Tacoma-Bellevue, WA$308k

Boston-Cambridge-Newton, MA-NH$294k

Lexington Park, MD$287k

Trenton-Princeton, NJ$285k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $226k; 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 P7 (P7 — Staff / Distinguished Professional) from the levels around it — this level only. Every word is real canon for this profile.

Scope: Cross-organization / enterprise technical strategy
Autonomy: Operates autonomously at the enterprise level
Complexity: Industry-level, highly ambiguous problems
Impact: Enterprise-wide
Decision rights: Final technical authority across multiple domains
Leadership: Sets technical direction org-wide; develops principals

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

Promotion

P7is the top of this family's ladder — progression from here is a lattice move (see adjacent roles below), not a rung.

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
Principal Petrophysicist	jf_petrophysics::P6	$188,314†	confident0.06
Senior Director of Petrophysics	jf_petrophysics::M6	$241,631†	confident0.12
Expert Petrophysicist	jf_petrophysics::P5	$138,423†	review0.13
Distinguished Geologist	jf_geology::P7	$231,230†	review0.17

†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

P7

jf_petrophysics::P7

Distinguished 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: 7 / 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 · P7review0.17

Geomatics · P7review0.17

Geophysics · P7review0.17

Geothermal · P7review0.17

Technologist · P7review0.17

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)