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The geologist who standardises the field record

$287,180top of the range in Texas · middle $101,920 / yr
AI is transforming this role

Geologists 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
Bachelor's or Master's degree in Geology
Lower disruption Higher exposure AI is transforming this role
Entry · $59,330 Top of range · $287,180 (Texas) Middle $101,920

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 GeologistReviewed September 2026

We track new AI-tool launches every week and refresh this list — here’s what’s gaining traction for Geologist work right now.

Julius AINEWFree / $20 mo

AI data analyst that runs statistics and charts from plain-language prompts.

How a Geologist 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 Geologist 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 Geologist 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 Geologist uses it: get evidence-backed answers with the studies behind them

SciSpaceFree / paid

AI that explains papers and helps with literature review.

How a Geologist 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 Geologist 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 Geologist 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 Geologist 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 Geologist uses it: draft and reply inside Google Workspace and research without leaving the page

Rocks, a map, and the file for a well

I am a geologist, and the work I recognize is rocks, maps, wells, and field sites. An office morning might be a table of samples, a map that still has a blank where last month's site visit belongs, and a well file someone needs read before a meeting. You are tying what the ground is made of to a decision a company, a public agency, or a client has to make. The decision might be where a resource sits, whether a site matches the story in an old report, or how to describe the subsurface so the next person does not start from zero.

Maps are the shared language. You draft them, you revise them when a new observation disagrees with the old line, and you write the note that says what the line means. A pretty map that outruns the evidence is a professional problem, not a graphics win. Well files are the other shared language in energy, water, and some environmental work. You read what was already recorded, you compare it with the map, and you say where the story is solid and where it is thin. The point of the morning is a clearer picture of the ground, captured so someone else can use it.

The people around that work are engineers, drillers, land staff, regulators, and other geologists. They do not need a lecture. They need a description they can act on: this unit, this depth in the language of the file, this uncertainty. Your value is the habit of separating what you saw from what you infer. I trust the geologist who will write "we do not know yet" on a map. I do not trust the one who fills every blank to look decisive.

Field sites, then the report back at the desk

Some weeks you go to the site. A roadside cut, a mine, a lease, a riverbank, or a project parcel is there so you can see the rock and the lay of the land instead of only the archive. You look, you take notes a colleague can read later, and you come home with something that changes the map or confirms it. I am describing the job, not a field manual. The employer's own practice, and the rules for that land, govern how a visit is conducted. What belongs in a career account is simpler: you were there, you observed, and the office product got better because you went.

Other weeks you never leave the building, and the job is still geology. Historic maps, well records, and reports from earlier visits can fill a month when the question is regional. You reconcile old names for rock units with the names your group uses now. You flag a file that contradicts the map. You prepare a figure for a partner meeting. Field time is not a moral test. Some roles are mostly sites. Some are mostly records. Ask which one the posting is, because a person who wanted boots and got a permanent desk, or the reverse, will be unhappy at the same salary.

The report is where the week cashes out. A useful report says what the rocks are, what the map shows, what the well information adds, and what remains uncertain. It names the site. It separates observation from interpretation in sentences a non-geologist can follow. Clients and regulators remember the report longer than they remember the visit. If your notes only make sense to you, the visit did not finish.

Who puts a geologist on the project

Energy companies, mining firms, environmental consultants, water agencies, state geological surveys, and federal land or science offices all hire this work. The rocks change and the week rhymes. An energy seat leans on wells and subsurface maps. A mining seat leans on ore, waste rock, and the site. An environmental seat leans on how the ground affects a cleanup or a construction parcel. A survey job leans on mapping for the public. Say which of those stories your training supports. A general claim that you "love the outdoors" does not tell me which file you can actually read.

A bachelor's degree in geology is the door. A master's is common when the role is specialized or when you want more independence early. Coursework and a field camp, where your school required one, are part of how you prepare. So is any internship where you touched real maps or real well files. In the interview, bring a story about a map you changed and a site or a file that forced the change. Leave the step-by-step technique at home. I am hiring judgment and clarity, and I already assume your school taught the craft inside its own courses.

Where public practice requires a professional geologist licence, the state board grants it. The licence is permission to practice for the public in that state and, where the rules say so, to seal certain work. It proves the board accepted your education and the experience it requires, through the process that board uses. Many boards draw on exams associated with the National Association of State Boards of Geology. The board in your state is still the body that grants the licence. Read that board's own description rather than a secondhand list. Jobs that never seal public documents may not ask for the licence on day one. Jobs that do should hear a plan, not a shrug.

Two Texas numbers, two meanings

$287,180 is the high end of the published range in Texas. Typical pay in Texas, the state median, is $145,220. Use the median when you talk about an ordinary offer.

From the junior map to the signature

You start as a staff geologist. Someone else scopes the question. You draft map edits, organize well files, and write sections of the report that a senior person will mark up. The promotion that matters is the one where your draft needs less repair and where people ask you what the site means before they ask the senior. That happens when your writing separates evidence from hope.

Later you own the interpretation. You decide which uncertainty to highlight. You talk to the engineer or the land manager in language they can use. In states that require a seal, this is when the licence stops being theoretical. You sign work the public or a regulator will rely on. Some geologists move into project management and spend more time on scope and clients. Some stay technical and become the person called when the map and the well file disagree. Both paths are real. The technical path dies if you stop reading the rocks. The management path dies if you cannot tell a weak report from a strong one.

Along the way, ask for a mix you can sustain. A year of only well files will make you fast at the archive and rusty at the outcrop. A year of only site visits will make you vivid in the field and slow at the report the client actually pays for. I try to give juniors both, even when a busy drilling schedule wants to swallow them. If your firm cannot offer that mix, look for a short assignment that restores the missing half before the habit sets. The geologist who can sit with a well file in the morning and stand on a site in the afternoon is the one other teams request. Moves between energy, mining, environmental work, and public surveys happen, and they happen more cleanly early than late. The shared skills are maps, careful description, and honest limits. The local knowledge, the rock names, the regulatory habits, does not transfer for free. If you switch, expect a period of being new again. Say that in the interview. Pretending a shale well file and a hard-rock mine are the same document is how trust gets lost in the first month.

The wage series, then the state medians

These figures are Occupational Employment and Wage Statistics for May 2025, published for Geoscientists, Except Hydrologists and Geographers, a series broader than the rock, map, well, and field-site work on this page. Entry pay is $59,330. The national median is $101,920. The gap from entry to the median is $42,590. The high end of the published range in Texas is $287,180, in the places a high end was released because employment was large enough. The gap from the national median to that Texas high end is $185,260. That high end is a range top. It is a different statistic from the Texas median.

Typical pay is the median, and the state medians here sit far from that Texas range top. Texas itself has a median of $145,220, which is $43,300 above the national median and still far below $287,180. Oklahoma's median is $119,990. Colorado's is $114,410. California's is $106,500. Washington's is $105,020. Pennsylvania shows the lowest median in these facts, $84,180. The gap between the Texas median and the Pennsylvania median is $61,040. If someone offers you the Texas range top as if it were a normal Texas salary, they are mixing two statistics. Ordinary talk about Texas starts at $145,220. Talk about the far edge of the published range, and only in Texas, is where $287,180 belongs.

The entry figure of $59,330 and the national median of $101,920 frame the early career. The $42,590 gap between them is the stretch from a junior seat toward the middle of the published picture. The much larger $185,260 gap from the median to the Texas high end is not a ladder most people climb rung by rung. It marks how far the top of the published range sits from typical national pay. Use it as a warning against loose quotes, and use the state medians when you want to know what "typical" means in Texas, Oklahoma, Colorado, California, or Washington.

Keep the two Texas figures apart

When the offer arrives, write the base, then write the national median of $101,920, then write the state median if the state is listed. For a Texas job, write $145,220 on the median line and $287,180 on a separate line labeled as the high end of the published range. Do the same mental split if a recruiter blurs them in a phone call. You can say, calmly, that typical Texas pay in this series is $145,220 and that $287,180 is the high end of the published range in Texas. That sentence is specific enough to reset the conversation.

A new graduate should look at $59,330 and at the $42,590 path toward the median, then at the local median if one exists. An experienced geologist in Oklahoma should look at $119,990 before looking at a Texas range top. An experienced geologist in Pennsylvania should look at $84,180 and at the national median, and should notice the $61,040 state-median gap if a move is truly on the table. None of this requires you to pretend every employer pays the Bureau's figure. It requires you to know which published number you are standing next to.

Ask about the week in the same breath as the base. Field rotation, well-file responsibility, overtime on a drilling schedule, and whether you are expected to seal work all change the job. A salary near the Texas median with a sustainable rotation can beat a louder number tied to a schedule you will leave. If the base is near entry and the posting says you will sign reports, point at the $42,590 gap and at the licence expectation together. The degree, the map-and-well record, the state licence where the work needs a seal, and these published figures are what you bring to the table. Leave the field manual out of the negotiation. Bring the numbers with their labels intact.

The top of Geologist pay — and how to get there with AI

$287,180what Geologist 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

Every geology group has practices that live only in the heads of two or three people, and the geologist who writes those down, gets them adopted and keeps them current is the one who ends up at the top of this range.

Consider how much of this occupation is judgment applied to a record: classifying soils, minerals, rocks and fossils; preparing geological maps, cross-sections and reports on mineral extraction or land use; reviewing environmental, historical and technical reports for accuracy. When two loggers describe the same core differently, the whole dataset weakens and nobody notices until a report is challenged. Writing standards used to be a job people avoided because drafting takes days. It no longer does — a model will turn a transcribed conversation with your best logger into a first-draft procedure by the afternoon. The scarce part was never the prose. It was the person willing to decide what the right practice is and defend it.

Your playbook, by where you are now

Just startingLearn the conventions well enough to question them

  1. Log core or map units alongside the most experienced person in the group and write down every call where your description differed from theirs.
  2. Ask why each convention exists — the grain size cut-offs, the colour terms, the sampling interval — and record the answers, because half of them turn out to be habit.
  3. Get your field data into EarthSoft EQuIS Geology or the group's database from the start rather than transcribing notebooks months later.
  4. Learn ESRI ArcGIS software well enough to produce your own map and cross-section without booking a specialist's time.
  5. Keep a personal log of the errors caught in review, and what caused each one.

What proves it: A field notebook and database record another geologist can use without ringing you.

Realistic span: the first three years of field work

A few years inTurn practice into a document people follow

  1. Write the logging and sampling procedure for one programme: what gets described, in what order, with what vocabulary, and what triggers a resample.
  2. Interview the two people whose judgment everyone trusts, transcribe with Otter.ai, and have Claude turn the transcript into a draft procedure you then argue over with them line by line.
  3. Standardise the map and cross-section output so every deliverable shares scale conventions, symbology and metadata, using BOSS Didger for legacy material that has to be brought in.
  4. Put the procedures and the scripts under Git so a change is a dated decision rather than a new file on a shared drive.
  5. Build the review checklist you wish had existed the last time a technical report came back with errors in it.

What proves it: A written field and reporting procedure that a second crew used without you present.

Realistic span: years four through eight

ExperiencedOwn the quality system, not just the science

  1. Take responsibility for how survey, drilling and testing programmes are planned across projects, so sampling design stops being reinvented each time.
  2. Set the standard for how resource and hazard conclusions are documented — including how identified risks such as mudslides, earthquakes or eruptions are worded for a non-specialist reader.
  3. Train new geologists on the standard in their first month, and audit against it rather than assuming.
  4. Move the group's database and analysis toward something a data scientist could work with, since that is where this occupation's next step is priced.
  5. Consider where the work is thickest and best paid; Texas concentrates a great deal of subsurface geology.

What proves it: A documented standard your organisation audits its own work against.

Realistic span: nine years and onward

The next 90 days

Choose the single task in your group with the most variation between people — usually core or sample description — and spend ninety days writing the standard for it. Start by having three colleagues independently describe the same material and comparing the results; the disagreements are your table of contents. Then sit with whoever is best at it, record the conversation, and write a procedure that includes the vocabulary, the decision rules, the photographs of borderline cases, and the two mistakes newcomers always make. Circulate it as a draft and invite people to attack it, because a standard nobody argued about is a standard nobody follows. What you will have at the end is the thing every geological organisation needs and almost none has written down.

Wage figures: BLS OEWS, May 2025. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.

The top of Geologist pay — and how to get there with AI

$287,180what Geologist 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

Every geology group has practices that live only in the heads of two or three people, and the geologist who writes those down, gets them adopted and keeps them current is the one who ends up at the top of this range.

Consider how much of this occupation is judgment applied to a record: classifying soils, minerals, rocks and fossils; preparing geological maps, cross-sections and reports on mineral extraction or land use; reviewing environmental, historical and technical reports for accuracy. When two loggers describe the same core differently, the whole dataset weakens and nobody notices until a report is challenged. Writing standards used to be a job people avoided because drafting takes days. It no longer does — a model will turn a transcribed conversation with your best logger into a first-draft procedure by the afternoon. The scarce part was never the prose. It was the person willing to decide what the right practice is and defend it.

Your playbook, by where you are now

Just startingLearn the conventions well enough to question them

  1. Log core or map units alongside the most experienced person in the group and write down every call where your description differed from theirs.
  2. Ask why each convention exists — the grain size cut-offs, the colour terms, the sampling interval — and record the answers, because half of them turn out to be habit.
  3. Get your field data into EarthSoft EQuIS Geology or the group's database from the start rather than transcribing notebooks months later.
  4. Learn ESRI ArcGIS software well enough to produce your own map and cross-section without booking a specialist's time.
  5. Keep a personal log of the errors caught in review, and what caused each one.

What proves it: A field notebook and database record another geologist can use without ringing you.

Realistic span: the first three years of field work

A few years inTurn practice into a document people follow

  1. Write the logging and sampling procedure for one programme: what gets described, in what order, with what vocabulary, and what triggers a resample.
  2. Interview the two people whose judgment everyone trusts, transcribe with Otter.ai, and have Claude turn the transcript into a draft procedure you then argue over with them line by line.
  3. Standardise the map and cross-section output so every deliverable shares scale conventions, symbology and metadata, using BOSS Didger for legacy material that has to be brought in.
  4. Put the procedures and the scripts under Git so a change is a dated decision rather than a new file on a shared drive.
  5. Build the review checklist you wish had existed the last time a technical report came back with errors in it.

What proves it: A written field and reporting procedure that a second crew used without you present.

Realistic span: years four through eight

ExperiencedOwn the quality system, not just the science

  1. Take responsibility for how survey, drilling and testing programmes are planned across projects, so sampling design stops being reinvented each time.
  2. Set the standard for how resource and hazard conclusions are documented — including how identified risks such as mudslides, earthquakes or eruptions are worded for a non-specialist reader.
  3. Train new geologists on the standard in their first month, and audit against it rather than assuming.
  4. Move the group's database and analysis toward something a data scientist could work with, since that is where this occupation's next step is priced.
  5. Consider where the work is thickest and best paid; Texas concentrates a great deal of subsurface geology.

What proves it: A documented standard your organisation audits its own work against.

Realistic span: nine years and onward

The next 90 days

Choose the single task in your group with the most variation between people — usually core or sample description — and spend ninety days writing the standard for it. Start by having three colleagues independently describe the same material and comparing the results; the disagreements are your table of contents. Then sit with whoever is best at it, record the conversation, and write a procedure that includes the vocabulary, the decision rules, the photographs of borderline cases, and the two mistakes newcomers always make. Circulate it as a draft and invite people to attack it, because a standard nobody argued about is a standard nobody follows. What you will have at the end is the thing every geological organisation needs and almost none has written down.

Wage figures: BLS OEWS, May 2025. The playbook is PayCrunch editorial guidance, not a guarantee of pay or placement.

Careers related to Geologist

Similar pay, same field

Where this can lead

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 with Google Earth Engine. It's free for research and the fastest way to bring machine learning to geology — pull decades of satellite, radar, and multispectral data and run alteration or lineament mapping over your area of interest right in the browser. Pair it with ChatGPT or Claude as a coding copilot to write the Earth Engine and Python even if you've never programmed.

For everything else, the free learning stack is QGIS for GIS, Python (with a copilot) for well-log and geochemical work, and NotebookLM to synthesize government surveys and the literature. Keep proprietary client and survey data out of public tools.

The one rule, forever: AI outputs are exploration hypotheses, not conclusions — a licensed geologist must verify with field and lab data and personally stamp any report affecting public safety, resource reserves, or investment (JORC/NI 43-101). Never upload proprietary client or survey data to a public model without a data agreement, always confirm projections and datums on AI-written code, and never let a model's prospectivity score substitute for ground-truthing.
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
Build mineral-prospectivity maps with machine learning
Why this pays: Exploration targeting is where geology pays best — find the deposit and you're indispensable. ML prospectivity mapping over open geoscience data is the single highest-leverage skill for the mining and exploration premium.
Google Earth EnginePython (scikit-learn)QGIS
1
In Google Earth Engine, assemble the predictor stack — geology, geophysics, geochemistry, remote-sensing alteration — for your area of interest.
2
Train a prospectivity model with your copilot writing the code.
Copy-paste this prompt
I'm building a mineral prospectivity model for [porphyry copper] in [region]. My predictor layers are: [list — e.g., ASTER alteration indices, magnetics, fault density, geochemistry]. Write the Python/scikit-learn workflow to stack them, train a Random Forest against known occurrences, handle class imbalance, do spatial cross-validation, and output a prospectivity raster plus feature importance. Comment each step so I can adjust it.
Ground-truth every high-scoring target — the model ranks hypotheses, it doesn't find deposits. Use non-proprietary data in public tools.
What you'll haveA ranked target list that focuses drilling — the discoveries and expertise behind top-of-range exploration pay.
2
Model the subsurface faster in 3D
Why this pays: Fast, defensible 3D geological models are billable, high-value deliverables. Speed and quality here directly raise consulting rates and project throughput.
Leapfrog GeoPetrelPython
1
Use Leapfrog Geo's implicit modeling to build and re-run the model as new drill data arrives, and automate the data prep in Python.
2
QA/QC the drillhole database before every import so the model isn't built on bad data.
Copy-paste this prompt
Write a Python script to QA/QC drillhole data before import to Leapfrog: check for overlapping or gapped intervals, missing downhole surveys, out-of-range assay values, duplicate sample IDs, and collar/survey mismatches. Output a report listing each issue by hole ID with a suggested fix.
AI cleans and flags; you make the geological interpretation. Keep client drill data in approved systems, not public tools.
What you'll haveReliable models delivered faster — more projects and higher rates in consulting.
3
Automate core and well-log interpretation
Why this pays: Logging core and interpreting wireline is slow, billable time. Automating the routine passes frees you for the interpretation clients actually pay premium rates for.
Python (lasio)ChatGPTPetrel
1
Use Python to load LAS files and auto-flag lithology and net-pay zones for your review, instead of scrolling logs by hand.
2
Have your copilot write the petrophysics workflow you can adjust.
Copy-paste this prompt
Write Python using lasio to load these well logs [gamma ray, resistivity, neutron, density], calculate Vshale, porosity, and water saturation using [Archie with my parameters], flag potential net-pay intervals by cutoff, and plot a composite log track. Comment each step so I can change the cutoffs and parameters for my basin.
You interpret and sign off; the script only does the arithmetic. Verify petrophysical parameters against local knowledge.
What you'll haveRoutine interpretation done in a fraction of the time — capacity for the high-value analysis clients pay most for.
4
Turn field and lab data into reports and proposals fast
Why this pays: Consulting income is gated by how fast you turn data into deliverables and win the next job. AI drafting on top of your data compresses both.
NotebookLMClaudeChatGPT
1
Load government surveys, prior reports, and your field notes into NotebookLM and query it for a cited context synthesis.
2
Draft the technical sections from your own data, keeping every conclusion yours.
Copy-paste this prompt
Draft the geology and results sections of a [Phase I environmental site assessment / exploration] report from these field observations and lab results: [paste non-confidential summary]. Use professional, defensible language, state data gaps and uncertainties explicitly, structure it per [standard], and flag anything that needs a licensed geologist's judgment.
You own every conclusion and the stamp. Verify each AI-summarized reference against the source — models invent citations.
What you'll haveFaster, sharper deliverables and proposals — more billable throughput and more won bids.
5
Add a remote-sensing geohazard service line
Why this pays: Geohazard and monitoring work — landslides, subsidence, groundwater — is a growing, well-paid consulting niche, and it's fundamentally a remote-sensing and ML problem.
Google Earth EngineSNAP (Sentinel-1)Python
1
Use Google Earth Engine or InSAR to detect ground deformation and change over time across a site or region.
2
Design the monitoring workflow before you run it.
Copy-paste this prompt
Outline a Google Earth Engine workflow to monitor [land subsidence / slope movement] over [area] using [Sentinel-1 InSAR / optical change detection]: data selection, preprocessing, the deformation or change calculation, how to threshold real signal from noise, and how to visualize results for a client report. Note the limitations of the method.
Field-verify anomalies before reporting — remote sensing flags where to look, not what's happening underground.
What you'll haveA modern hazard-monitoring service line — differentiated, higher-margin consulting work.
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
Do a Google Earth Engine tutorial and run an alteration or change map over an area you already know, with ChatGPT as your coding copilot.
Months 2-3
Automate one slow task — core logging, LAS interpretation, or drillhole QA — with AI-written Python.
Months 3-6
Build a real prospectivity or geohazard model on open data as a portfolio and pilot project.
Months 6-12
Fold AI drafting into your reports and proposals, and pursue or maintain PG licensure — the credential behind top pay.
Year 2
Position as the data-science-fluent geologist on exploration or consulting projects — the differentiator that commands the $287,180 tier.
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.

Carpenter / Keane The Geoscience Handbook: AGI Data Sheets, 5th

AGI 5th (2016), ISBN 978-0-91331-247-6. Field/lab data sheets ASBOG lists on the candidate-resources page. Leftover is ASBOG FG 140 / 4 hr and PG 110 / 4 hr, pass 70. Confirm the 5th, not the leftover 4th 0922152756. Not the free ASBOG handbook PDF. Not NCEES FE, FS, or PE. HTTP 200 on /dp/0913312479.

Next steps for a Geologist

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.

Geologist 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.

Geologists 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.

Geology programs on Coursera for Geologist work

Coursera search for geology — a graduate-level or professional certificate that lines up with science, not a generic professional-development aisle.

Geology courses on edX

edX search for geology, aimed at science (SOC 19-2042). Same field as the Coursera link, different university catalog.

Screened remote and flexible Geologist listings on FlexJobs

FlexJobs screens remote, hybrid, freelance, and flexible listings so you are not wading through unverified ads. This is a job-board search for Geologist work, not a claim that they list a counted SOC 19-2042 inventory.

Build a Geologist resume on Resume Now

Write a Geologist 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.

Build a Geologist resume on Zety

A Geologist resume that names the actual tasks on this page, or the step-up title Data Scientists, beats a blank template when you apply.

What Geologists 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.
Texas$145,220Oklahoma$119,990Colorado$114,410California$106,500Washington$105,020Nevada$99,890North Carolina$95,260Florida$95,140

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.

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Frequently asked
Will AI replace geologists?
No. AI ranks targets and crunches data, but someone with field and lab judgment has to ground-truth it, and a licensed geologist must stamp any report affecting safety, reserves, or investment. AI raises the value of that judgment by removing the grunt work. The geologists who fall behind are the ones who won't touch the data-science tools.
I'm not a programmer — can I really use these tools?
Yes, and that's the biggest change. With ChatGPT or Claude as a coding copilot, a geologist who understands the science can write Earth Engine and Python workflows by describing what they want. Start with one tutorial; the copilot handles syntax while you supply the geology.
Is it safe to put client or survey data into AI tools?
Not into public models without a data agreement — proprietary geophysics, assays, and client data are confidential and commercially sensitive. Use open government data in public tools and keep client data in approved, contracted systems. Never let convenience breach an NDA.
How does AI move a geologist toward the top of the pay band?
The top band is exploration targeting, specialized modeling, and consulting. AI lets you rank targets on open data, model the subsurface and interpret logs faster, and turn data into billable reports quickly — more discoveries, more throughput, higher rates, and the PG-plus-data-science profile clients pay most for.
Which should I learn first — GIS, Python, or a modeling package?
Google Earth Engine, because it's free, browser-based, and gives you satellite ML immediately with a copilot writing the code. Add QGIS for general GIS and Python for log and geochemistry work next. Learn a paid package like Leapfrog or Petrel when a specific job requires it.
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.

Sources