The geophysicist known for one method, not for all of them
$287,180top of the range in Texas · middle $101,920 / yr
AI is transforming this role
Geophysicists in the United States earn a median of $101,920 a year. Pay starts near $59,330. Pay reaches $287,180 at the top of the range in Texas, the best-paying state for this work among those with at least 500 people in the job.
Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Geoscientists, Except Hydrologists and Geographers, SOC 19-2042). Last checked 9 September 2026.
Entry level
$59,330
Top of the range · Texas
$287,180
Education
Master's degree in Geophysics
Wages — U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025 (Geoscientists, Except Hydrologists and Geographers). Top of the range is the highest state-level figure among states with at least 500 people in the job. AI-impact rating is PayCrunch's editorial assessment. Updated September 2026.
🆕 New & Trending AI Tools for GeophysicistReviewed September 2026
We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for Geophysicist work right now.
Julius AINEWFree / $20 mo
AI data analyst that runs statistics and charts from plain-language prompts.
How a Geophysicist uses it: analyze datasets and generate figures without writing code
NotebookLMNEWFree / $7.99 mo
Google tool that answers questions grounded only in the documents you give it — with citations.
How a Geophysicist uses it: load your own manuals, policies, or PDFs and ask questions that stay accurate to the source
ElicitFree / $12 mo
AI research assistant that finds and summarizes papers.
How a Geophysicist uses it: run a literature review and extract findings across dozens of papers fast
ConsensusFree / $9 mo
AI search that answers questions from peer-reviewed research.
How a Geophysicist uses it: get evidence-backed answers with the studies behind them
SciSpaceFree / paid
AI that explains papers and helps with literature review.
How a Geophysicist uses it: decode dense papers and trace citations quickly
SciteFree / $20 mo
Shows whether other studies support or contradict a paper's claims (Smart Citations).
How a Geophysicist uses it: check if a finding is actually backed by the wider literature before you cite it
ChatGPTFree / $20 mo
The most-used AI assistant — writing, analysis, research, and images from a plain-language chat.
How a Geophysicist uses it: draft emails and documents, summarize long files, and get instant answers to on-the-job questions
ClaudeFree / $20 mo
AI assistant known for careful writing, long-document analysis, and coding.
How a Geophysicist uses it: analyze big reports or spreadsheets and turn messy notes into clean, finished writing
Google GeminiFree / $20 mo
Google's AI assistant, built into Gmail, Docs, and Search.
How a Geophysicist uses it: draft and reply inside Google Workspace and research without leaving the page
Sound, pull, and a magnetic trace
A geophysicist uses measurements to picture what is underground. Three families of measurement carry most of the career you will hear about. Seismic work uses sound waves that travel through rock and return. Gravity work uses tiny differences in gravitational pull, which hint that rock below is denser or less dense than what sits beside it. Magnetic work uses the magnetic character of rock. Together they are the data geologist reads when the rocks themselves are still buried. The geophysicist builds and interprets that picture. The geologist uses it.
The picture supports real decisions, and the setting changes the stakes. An energy company wants to know where a structure might hold oil or gas. A mining group wants to know where an ore body might sit. An environmental firm wants to know what is under a contaminated site before anyone digs. An engineering firm wants to know whether the ground can carry a road, a dam, or a building. A public agency wants to understand earthquake hazard. The measurements differ in detail. The job is the same kind of honesty: say what the data can support, and say where it goes quiet.
Day to day, the work splits into collecting, processing, and interpreting, and many people spend their careers in one of those rooms. Acquisition programs gather the measurements, often with crews and contractors in the field or offshore. Processing turns raw records into sections, maps, and models a human can read. Interpretation reads those products and writes the conclusions a client, a geologist, or an engineer will use. You might touch all three early and then specialize. A career guide can name those rooms. It should not turn into a field manual for how to lay out a survey, how to set an instrument, or how to run a processing sequence. That teaching belongs with a crew lead and a company's own procedures.
The tools are computers as much as they are instruments. You will live in data volumes, in maps, and in the argument between a pretty image and a rock fact someone logged in a well or a borehole. Geophysicists who only trust the image, and geologists who only trust the hammer, both miss the point of the partnership. The useful person can sit in that argument without turning it into a contest. Write so a non-specialist on the project can see what you believe and what you are unsure about. The subsurface does not reward false confidence.
The data the geologist uses
Geologists map, sample, and tell the story of the earth from rocks they can see and from clues they cannot. Where the rocks are hidden, your seismic section, your gravity map, or your magnetic map becomes one of those clues. A geologist may take your horizon, your fault interpretation, or your anomaly and fold it into a larger model of the basin, the mine, or the site. They will argue with you. That argument is the work. If the picture cannot stand up to a geologist asking what the rock would actually be, the picture still needs work. The partnership is the point: geophysics supplies a picture, geology supplies the earth-science judgment, and the project needs both.
Clients rarely buy a method. They buy a decision. "Can we lease this block?" "Should the tunnel move?" "Is this anomaly worth a drill hole?" Your job is to connect the measurement to that decision without overclaiming. Seismic can show structure and, in the right setting, something about the material. Gravity and magnetics can show broad contrasts that seismic may not have covered. None of them is a magic view of every layer. Say the limit in the same paragraph as the conclusion. Managers and geologists trust the geophysicist who does that, and they discount the one who delivers a bright map with no caveats.
You will also translate. A processing specialist, an interpreter, a geologist, a driller, and a finance person may all sit in one review. They do not share a vocabulary. The geophysicist who can say what changed in the model, in plain words, keeps the project honest. The one who hides inside jargon creates a meeting where everyone nods and nobody knows what was decided. Practice that translation on purpose. It is a larger part of seniority than a new piece of software.
Study, seasons in the field, and a licence for some public work
The usual preparation is a bachelor's degree in geophysics, in geology with serious geophysics coursework, or in physics with a turn toward the earth. A master's degree is common for interpretation and for many industry seats. A doctorate fits research groups, universities, and some specialist posts in national surveys. The degree shows you can handle the physics and the geology at the same time. It does not, by itself, make you someone a company will leave alone with a basin.
People add field seasons, internships, and a first processing or acquisition job. A summer with a crew teaches the messiness that clean textbook figures hide: weather, access, equipment that fails, and data that arrives incomplete. You do not need to become a career field hand to respect that mess. You do need enough of it that you stop treating a dataset as if it appeared from nowhere. Programming and comfort with large files help in almost every room of this profession. So does the habit of labeling a figure so someone else can reproduce the display from your notes.
Some public and consulting work requires a professional geoscientist or geologist licence from a state board. The board grants it. The licence shows you met that board's education and experience rules to offer geoscience to the public. It proves the jurisdiction's requirements, which differ by place. Many people inside an energy or mining company work under the firm's supervision, where hiring often proceeds without that licence. Consulting firms and public agencies more often ask for it, because their product is advice a stranger will rely on. The National Association of State Boards of Geology is where those boards gather. Check the board where you will practice rather than assuming one rule covers the country.
The professional home for a lot of this community is the Society of Exploration Geophysicists. Membership is voluntary. It does not grant the state licence. It does put journals, meetings, and a network next to your training. Use it to see how working geophysicists talk about seismic, gravity, and magnetic problems. Use the state board, when you need it, for the legal credential. Keeping those two ideas separate will save you from describing a society membership as if it were a licence to stamp public work.
Who hires, and who gets the first project
Employers include energy companies, mining firms, environmental and engineering consultancies, geophysical contractors, government geological surveys, and universities. A posting for a junior geophysicist may mean processing support, interpretation support, or field quality control. Read it. Bring a thesis or a class project you can explain without slides full of decoration, and be ready to say what the data could not tell you. Hiring managers are allergic to certainty that outruns the figure. They are patient with a candidate who marks the uncertain part in ink.
The first role is supervised on purpose. You will redo displays. You will have an interpretation returned with hard notes. You will learn the company's naming, the client's preferences, and the difference between a quick look and a product that leaves the building. Show up able to take the note. Geophysicists who defend a first draft as if it were a reputation rarely get the second project. The ones who fix the draft, and who can say what they fixed, become the person a lead wants on the next bid.
Cycles in energy and mining move hiring. A busy year can hire a whole class of juniors. A quiet year can freeze the same seats. Consulting and public-sector work sometimes move on a different clock, tied to infrastructure, water, and hazard projects. If you can be geographically flexible early, you will see more openings. If you cannot, build skill in the methods local employers use, and say so. A gravity and magnetics specialist in a mining region and a seismic interpreter in an energy region are both geophysicists, and they are not applying for the same Tuesday.
From a workstation to the person who leads the program
The path has a technical branch and a leadership branch, and they overlap. You start as a processor or a junior interpreter. You become the geophysicist who owns a prospect, a mine target, or a site model. A team lead reviews other people's work and deals with the client. A chief geophysicist, or a principal in a consultancy, sets method for a group and carries the hard conversations when the data and the business plan disagree. Some people stay individual experts on seismic imaging, on potential-field methods such as gravity and magnetics, or on a particular basin. Expertise without a manager title is a respected end, not a stall.
Field program leadership is another branch. You plan, with contractors, the kind of measurement the project needs, you watch data quality at a career level, and you decide when a program has done enough to interpret. That role fits people who can hold a schedule and a scientific limit in the same week. That role still leaves no room to improvise a survey from memory. Company procedures, a permit, and a lead who has done the work before all stay in the loop. The career skill is judgment about whether the data will answer the geologic problem, not a private recipe for how to collect it.
Later moves include independent consulting, a return to research, or a crossing into management of exploration or engineering groups. Each move asks you to keep the habit that made you useful: the data, the limit of the data, and a conclusion a geologist can use. If you lose that habit in exchange for a bigger title, the title will not protect you in the next review. Projects remember who was careful.
Geoscientist wages, with this work in mind
These figures are Occupational Employment and Wage Statistics for May 2025, for Geoscientists, Except Hydrologists and Geographers. The series also includes geologists and other geoscientists, so the dollars describe a wider group than geophysicists alone. Use them as that published market, then talk about where seismic, gravity, and magnetic work sits inside it. Published pay starts at $59,330. The national middle is $101,920. The gap from entry to the median is $42,590. That gap is the practical distance for a person moving from a supervised junior seat toward a geophysicist who owns an interpretation. A brand-new graduate belongs nearer the entry figure. A master's plus a project you can defend belongs in the conversation toward the middle.
The high end of the published range is $287,180 in Texas, where enough of this work is counted for a high end to be shown. From the national median to that high end is $185,260. Texas also has a median, and it is a different statistic: $145,220. Do not merge them. The high end is the top of a published range. The median is a typical wage. The distance between those two Texas figures is large enough that treating them as one number will end the negotiation before it starts. The long stretch above the median is where scarce senior technical leaders tend to sit. Early offers belong on the entry-to-median gap and on the state median that matches where you will actually work.
State medians, the middles, line up this way. Texas leads at $145,220. Oklahoma is $119,990. Colorado is $114,410. California is $106,500. Washington is $105,020. The lowest median is Pennsylvania at $84,180. The gap between the highest and lowest median is $61,040. The gap from the national median up to the Texas median is $43,300, almost the same size as the climb from entry pay to the national middle. Working in a high-median state can move a typical geoscientist wage about as much as the whole early-career step. Pennsylvania's median sits below the national figure, which matters if that is where the job actually is. None of these medians is the Texas high end of $287,180.
When you negotiate, bring the mandate of the job and three comparisons. Where does the offer sit between $59,330 and $101,920? If the office is in Texas, Oklahoma, Colorado, California, or Washington, how does the offer sit against that state's median, from $145,220 down to $105,020? What will you own in the first two years: processing support, a supervised interpretation, or a program lead? A licence, where the public work requires one, and a project a geologist actually used both support a move toward the median or toward a higher state median. The $287,180 figure is the high end of the published range in Texas, a landmark for the top of that range, not a starting offer. Say so. The same plainness you owe a client about the limit of a seismic section is the plainness that makes a wage conversation believable.
The top of Geophysicist pay — and how to get there with AI
$287,180what Geophysicist pay reaches in Texas
Highest state-level top-of-range annual wage for Geoscientists, Except Hydrologists and Geographers, among states with at least 500 people in the job. U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025.
And the role it leads to — Data Scientists — reaches $224,920 in California.
$59,330entry$101,920middle$287,180top end
Broad competence across gravity, magnetics and seismic keeps a geophysicist comfortably mid-range; being the person a company flies in for one specific acquisition or inversion problem is what pushes past it.
This is a field where the difficult, valuable questions are narrow. Measuring the Earth's gravity or magnetic fields with gravimeters, magnetometers and torsion balances, estimating probable oil, gas, mineral or groundwater resources from survey results, and identifying earthquake or volcanic risk are not one skill but a dozen, and generalists get paid for the easy end of each. Routine processing keeps getting cheaper to run, which squeezes the generalist further. The corner that does not get squeezed is the one where somebody has to decide whether an anomaly is real, and that judgment only accumulates if you keep working on the same class of problem.
Your playbook, by where you are now
Just startingSample methods deliberately, then choose
Get into the field on acquisition rather than only receiving processed data, because instrument behaviour is where a geophysicist's intuition comes from.
Work through at least three methods in your first years — a potential field method, a seismic programme and a borehole or downhole method — and note which problems you enjoy arguing about.
Learn to code your own processing in Python and keep it under Git, so a result can be reproduced two years later.
Reprocess one public dataset where the published answer is known, and find out where your parameters change the interpretation.
Read the method papers behind the software you use, not just the manual.
What proves it: Reproducible processing of a known dataset, with your parameter choices documented.
Realistic span: the first three or four years
A few years inGo deep on one problem class
Pick the corner: shallow hazard characterisation, mineral exploration inversion, reservoir monitoring, or seismic risk assessment, and turn down work that dilutes it.
Build a case library of every survey you have interpreted in that corner, including the ones where drilling later proved you wrong.
Use GitHub Copilot to speed up the inversion and modelling code you write, then test each change against a synthetic model where you know the true answer.
Publish or present in that specific area, because in narrow work reputation is how clients find you at all.
Take the interpretation calls other people avoid, and write down your reasoning before the result comes back.
What proves it: A documented case library in one method, including the wrong calls and what caused them.
Realistic span: years five through ten
ExperiencedBe the person called when it matters
Take the survey design decisions — line spacing, instrument choice, acquisition parameters — since design errors cannot be processed away afterwards.
Review other people's environmental, historical and technical reports in your area for accuracy, which is quiet work that builds enormous standing.
Keep GeoPLUS Petra or the equivalent interpretation environment for your corner sharp, and hold the data conventions your team works to.
Teach the method, at a university or internally, because explaining an inversion to a sceptic is how you find the gaps in your own reasoning.
Weigh where your method is bought heavily; Texas concentrates subsurface geophysics, and specialists there see the widest range of problems.
What proves it: Being named on survey design and interpretation for work outside your own employer.
Realistic span: eleven years and beyond
The next 90 days
In the next ninety days, decide what your corner is and prove you belong in it with one piece of work. Take a dataset from the method you want to be known for — your own or a public one — and reprocess it end to end, documenting every parameter choice and showing how the interpretation changes when you vary the two that matter most. Write the result up in five pages: the geological question, the acquisition, the processing decisions, the ambiguity you could not remove, and what you would acquire next to settle it. That last section is what marks a specialist. Send it to two people in that corner and ask them to disagree with you. A geophysicist who can defend a narrow interpretation in front of other specialists is on a different pay track from one who processes whatever arrives.
Wage figures: BLS OEWS, May 2025. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.
Every figure is the national median from the U.S. Bureau of Labor Statistics (OEWS) shown on that role’s own page.
Never used AI before? Start here (2 minutes).
Start inside the interpretation package you already use. Turn on the machine-learning tools in dGB OpendTect (free/open) or your Petrel and Geophysical Insights Paradise workflow and run automated fault and facies detection on a public 3D volume (e.g., the F3 Netherlands or Groningen data). Compare the AI picks to your manual interpretation to learn where it helps and where it hallucinates.
For scripting and learning, use Claude or ChatGPT to write Python with ObsPy, segyio and PyTorch, and keep Perplexity handy for new methods. Practice on open datasets so no licensed data ever touches an external tool.
The one rule, forever: Subsurface interpretations underwrite drilling, injection and hazard decisions with huge safety and financial stakes. AI fault/horizon picks and inversions carry real uncertainty and can be confidently wrong on noisy or unfamiliar data - always tie interpretations back to well ties, physics, and error bars, and never present an ML result as ground truth without validation. Guard proprietary and licensed seismic data; never load it into consumer AI tools.
The plays — exact steps, exact prompts
Do these in order. Each one is copy-paste ready. You do not need to know anything about AI going in.
1
Automate seismic interpretation with ML
Why this pays: Interpreting a 3D survey manually takes weeks; ML fault/horizon/facies detection does the first pass in hours, so you cover more prospects and catch subtle plays competitors miss. More and better prospects mapped is exactly what earns the senior-interpreter, top-of-range seat.
Run automated fault and seismic-facies extraction in OpendTect or Paradise on your volume; use Bluware InteractivAI for interactive deep-learning body tracking, then QC every surface against well ties.
2
Design the attribute-and-ML workflow for your play type.
Copy-paste this prompt
I'm interpreting a 3D seismic volume for [a fluvial reservoir in a passive-margin basin]. List the seismic attributes and an ML workflow (unsupervised facies clustering vs supervised fault detection) that best highlight [channel sand bodies], the typical failure modes of each on noisy data, and the QC checks to confirm the AI picks are real geology, not acquisition footprint.
AI accelerates the first pass; the geological story and every drill-relevant pick are yours to validate against wells and physics.
What you'll haveFull 3D surveys interpreted in a fraction of the time with subtle features surfaced - the productivity that defines a top-of-range interpreter.
2
Deep-learning seismic processing and inversion
Why this pays: Cleaner data and faster inversions mean better images from the same acquisition budget. The geophysicist who can denoise, deblend and run ML-accelerated FWI turns marginal surveys into drillable prospects - directly what an exploration team pays a premium for.
Use deep-learning denoise/deblend and ML-accelerated velocity building; prototype in PyTorch on open data, then apply in your production system (SLB Omega/DELFI or DUG).
2
Build a validated seismic-denoising model.
Copy-paste this prompt
Write a PyTorch training loop for a U-Net that denoises 2D post-stack seismic patches: a synthetic-plus-field training strategy, an appropriate loss for preserving weak reflectors, data augmentation that won't create artifacts, and metrics to prove I haven't removed real signal. Explain how to validate on a blind line.
Denoising can erase faint but real reflectors - always validate against a withheld line and against the raw data before trusting a processed image.
What you'll haveHigher-quality subsurface images from the same data - turning marginal prospects into drillable ones and raising your value to the team.
3
Monitor earthquakes and induced seismicity with deep learning
Why this pays: Monitoring induced seismicity for fracking, geothermal and carbon-storage operators is a growing, well-paid niche. Deep-learning pickers detect an order of magnitude more events than classic methods - the geophysicist who runs that pipeline becomes the operator's essential risk manager.
SeisBench (PhaseNet, EQTransformer)ObsPyGaMMA / PyOcto association
1
Build a detection pipeline with SeisBench models (PhaseNet/EQTransformer) for phase picking, associate with GaMMA, and locate - automating a catalog that used to take an analyst weeks.
2
Design the full monitoring pipeline and alert thresholds.
Copy-paste this prompt
Outline an end-to-end microseismic monitoring pipeline for [a geothermal injection site]: SeisBench model choice and why, how to fine-tune on my local stations, an event-association and location workflow, magnitude-of-completeness estimation, and how to set a traffic-light-protocol alert threshold for the operator.
A missed or mislocated event has real safety and regulatory consequences - validate the ML catalog against a hand-picked subset and report detection uncertainty.
What you'll haveAn automated, high-sensitivity seismic catalog - the monitoring capability that makes you indispensable to energy-transition operators.
4
Hunt the energy transition with ML prospectivity
Why this pays: Critical-mineral and carbon-storage exploration is where the new money is - AI-driven mineral hunters have raised billions. A geophysicist who fuses geophysical, geochemical and remote-sensing data into ML prospectivity maps is positioned for the highest-growth, role at the top of the ranges.
Google Earth Enginescikit-learn / XGBoostQGIS + OpendTect
1
Stack geophysical (gravity, magnetics, EM), geological and satellite layers in Google Earth Engine/QGIS and train a scikit-learn/XGBoost prospectivity model on known deposits or storage analogues.
2
Set up a leakage-free prospectivity model.
Copy-paste this prompt
I'm building a mineral-prospectivity model for [copper porphyry] over [a permissive belt]. Recommend the geophysical and remote-sensing feature layers to include, how to handle severe class imbalance (few known deposits), how to avoid spatial data leakage in cross-validation, and how to communicate prospectivity as calibrated probability with uncertainty to exploration managers.
Spatial autocorrelation makes ML look better than it is - use spatially-blocked cross-validation and report honest uncertainty, or you'll send a drill rig to the wrong place.
What you'll haveData-driven prospectivity maps for the energy transition - the high-growth work that commands top-of-range compensation.
5
Multiply your code output and own the ML workflow
Why this pays: Geophysics runs on code - SEG-Y wrangling, inversion scripts, plotting. An AI pair-programmer multiplies that, and the geophysicist who builds the team's reusable ML tooling becomes the technical lead, the role that pays top-of-range.
ClaudeGitHub Copilotsegyio + ObsPy
1
Keep Claude/Copilot in your editor to write segyio/ObsPy processing, refactor legacy code, and build shared notebooks the team reuses.
2
Automate a robust attribute extraction from SEG-Y.
Copy-paste this prompt
Write Python with segyio to load a 3D post-stack SEG-Y, extract an [RMS amplitude attribute] in a window around a picked horizon stored in [an ASCII file], export the attribute map as a GeoTIFF, and handle common SEG-Y header pitfalls (byte locations, coordinate scalars). Comment the header assumptions.
SEG-Y headers are notoriously inconsistent - verify trace coordinates and sample intervals on real data before trusting any automated extraction.
What you'll haveA tenfold jump in tooling output and a reusable ML stack you own - the technical-lead position behind pay at the top of the range.
Your 12-month sequence to the top of the range
How the plays above stack into a path from median pay toward the $287,180 tier.
Month 1
Turn on ML fault/facies detection in OpendTect on an open 3D volume and QC it against your manual picks.
Months 2-3
Prototype a deep-learning denoise or a SeisBench detection pipeline on public data.
Months 3-6
Apply one ML workflow to a real project (interpretation, processing, or monitoring) end-to-end.
Months 6-9
Build an energy-transition prospectivity map or a CCS/geothermal monitoring capability.
Months 9-12
Package your tooling for the team and take ownership of the ML workflow - the technical-lead track.
Gear for this job
As an Amazon Associate, PayCrunch earns from qualifying purchases. Links to books and tools are for the job on this page; we only recommend what we’d use in the work.
Same live O’Reilly 3rd already on data-scientist / python-developer / market-research-analyst / physicist. This leftover page says Learn to code your own processing in Python and keep it under Git; start-here names write Python with ObsPy, segyio and PyTorch; the prompt is Write Python with segyio to load a 3D post-stack SEG-Y. Not CompTIA Data+ and not leftover Ross Exam P (that is actuary). Confirm 109810403X. Live page HTTP 200, no PC_GEAR / amazon.com/dp / tag=paycrunch-20 at 2026-09-17 4:44 PM PT.
Next steps for a Geophysicist
Some links below are affiliate or partner links. PayCrunch may earn a commission if you enroll or subscribe through them, at no extra cost to you. Wage figures on this page still come from the Bureau of Labor Statistics, not from these programs.
Geophysicist work is specific enough that a stamped 'check out these courses' block would be noise. BLS files this work as Geoscientists, Except Hydrologists and Geographers (SOC 19-2042). O*NET Job Zone 5 is typical: graduate or professional school, so the honest next credential is a graduate-level or professional certificate — not a random catalog dump.
The occupation's listed knowledge areas include Geography and Chemistry; the links search those subjects, not a generic 'career courses' list.
Geophysicists in this dataset list Autodesk AutoCAD among the tools in use, so a program that names that stack is a better fit than a survey course.
FlexJobs screens remote, hybrid, freelance, and flexible listings so you are not wading through unverified ads. This is a job-board search for Geophysicist work, not a claim that they list a counted SOC 19-2042 inventory.
Write a Geophysicist resume, or one aimed at Data Scientists, instead of a blank template. Resume Now is a resume builder; we are not claiming a counted template set for this SOC.
A Geophysicist resume that names the actual tasks on this page, or the step-up title Data Scientists, beats a blank template when you apply.
What Geophysicists earn by state
These are the Bureau of Labor Statistics’ own figures for Geoscientists, Except Hydrologists and Geographers, state by state — not a cost-of-living adjustment applied to the national number. Only states employing at least 500 people in the occupation are shown, because a state median drawn from a handful of workers is noise rather than a signal.
Texas
$145,220
highest of them · +42% vs the national median
Pennsylvania
$84,180
lowest of the 11 states that qualify · -17% vs the national median
The same job pays $61,040 more a year at the median in Texas than in Pennsylvania — 73% higher. That gap is what the Bureau measured, before any question of what it costs to live in either place. Texas also carries the top of this job’s range, $287,180 — the figure quoted at the head of this page.
Source: U.S. Bureau of Labor Statistics, Occupational Employment and Wage Statistics, May 2025, SOC 19-2042. 11 states clear the 500-employee reporting floor for this occupation; those below it are left out rather than shown with a wide error band.
Free data. Use any of it.
PayCrunch publishes verified, BLS-sourced salary + AI-playbook data on 1,000+ professions — free, no signup.
No. AI automates picking, processing and detection, but it can't own the geological interpretation, the drill or injection decision, or the uncertainty - and it is confidently wrong on unfamiliar data. Interpreters who wield AI dominate on throughput; those who only hand-pick fall behind.
Is my proprietary seismic safe in these tools?
Only in licensed, on-premise or enterprise systems with the right agreements. Never load client or licensed seismic into consumer AI tools. Build and practice ML skills on open datasets like F3 Netherlands or Groningen.
Do I need to be a machine-learning expert and coder?
For the top of the range, increasingly yes - but LLM pair-programmers dramatically lower the bar. You supply the geophysics and the QC judgment; AI writes much of the code. Learning to direct and validate ML is more important than being able to derive it from scratch.
Which is the highest-value AI skill right now?
For oil and gas, ML seismic interpretation and FWI. For the growth market, energy-transition work - critical-mineral prospectivity, CCS characterization, and induced-seismicity monitoring - where demand and pay are rising fastest.
How does this raise my pay?
It moves you toward exploration and energy-transition roles where a correct subsurface call is worth millions, and toward technical-lead positions where you own the team's ML workflow - both routes to top-of-range compensation.
Methodology & sources
Salary (median, 10th, top of the range) — U.S. Bureau of Labor Statistics, OEWS.
By state — the Bureau of Labor Statistics’ own state medians, limited to states employing at least 500 people in the occupation. No cost-of-living arithmetic is applied to a wage anywhere on this page.
The plays — PayCrunch's own step-by-step guidance using publicly available AI tools. Tool names/URLs are real and current as of August 2026; prompts written to work as-is. Verify any professional output before relying on it.