Alberta Oilfield Data — Public Records vs. Spreadsheets for Research Workflows

When a Spreadsheet Is the Right Call

Spreadsheets are not obsolete — they are appropriate for clearly bounded tasks. If you are researching a handful of operators, running a one-time analysis, or building a custom model that a platform cannot express, a spreadsheet is the right tool. Many teams use public Alberta records in a spreadsheet for exactly this. The mistake is using spreadsheets for recurring, multi-region monitoring where their limitations compound.

Spreadsheet Formulas That Oilfield Researchers Actually Use

A few formulas carry most ST37 analysis. COUNTIFS groups wells by operator and status. VLOOKUP or XLOOKUP joins ST37 to Petrinex on the licence number. Pivot tables summarize well counts by field centre. Geographic distance can be approximated with a haversine formula on latitude and longitude, or simplified by filtering township ranges. The data sources guide explains which joins are valid.

Where Platforms Pull Ahead: Linking and Monitoring

The decisive advantage of a research platform is not speed alone — it is the connections between datasets and the persistence of monitoring. A platform can show an operator's wells, their status mix, nearby activity, and recent filings in one view, then alert you when any of it changes. That linking is manual and fragile in a spreadsheet. The watchlist guide shows why this matters for catching opportunities early.

Cost of Stale Data

A spreadsheet is a snapshot. The day after you build it, wells change status and operators transfer licences, and your list begins to decay. Teams that rely on spreadsheets often discover their prospect list is weeks out of date exactly when they need it current. Platforms with saved searches close that gap by re-running your criteria against fresh data. The prospect list guide stresses saving criteria so lists can be refreshed.

A Pragmatic Hybrid Recommendation

For most teams, the hybrid model wins: use a platform for search, filtering, linking, and monitoring, then export to a spreadsheet for bespoke analysis, reporting, or CRM staging. This captures platform efficiency while keeping the flexibility spreadsheets offer. The export guide covers how to prepare clean CSV files for that hand-off.

The Starting Point Every Team Faces

Every oilfield service company that wants to do systematic business development faces the same choice: work with raw public data exports in a spreadsheet, or use a research platform built on the same data. Both approaches use the same underlying AER records. The difference is in how much time they take, how reliable the results are, and whether the research is reusable across your team.

This guide compares the two approaches honestly, including where spreadsheets work well and where they create problems. The goal is not to tell you which to use — it is to help you understand the trade-offs so you can make an informed decision for your specific situation.

What Public Data Includes

Alberta publishes extensive oilfield data through the AER and Alberta Open Data. The primary datasets for business research include:

ST37 well records — public Alberta well records with status fields, operator fields, location fields where available, well type, and drilling information.

Regulatory filings — licence applications, suspension notices, abandonment applications, and reclamation certificate filings.

Production data — separate approved sources may provide production context when production trends matter.

Facility and infrastructure data — separate public sources may provide facility or infrastructure context that can complement well records.

These public data sources are free and useful, but each has coverage limits, update schedules, and field definitions that need to be checked. The raw data itself is not the differentiator — what you do with it is.

The Spreadsheet Approach

Working with raw data in a spreadsheet is the most common starting point. Here is what it looks like in practice:

How It Works

Download the ST37 file from the AER or Alberta Open Data. Open it in Excel, Google Sheets, or another spreadsheet tool. Apply filters to narrow the data by location, operator, well status, and other attributes. Sort and group the results to build prospect lists. Save the filtered results in separate tabs or files for each research session.

What Spreadsheets Do Well

Low cost — no subscription fees. You already have the tools.

Familiar interface — most people know how to filter and sort in a spreadsheet.

Flexibility — you can create any column, formula, or layout you want.

Good for small datasets — if you are working with a few hundred records, spreadsheets handle it fine.

Where Spreadsheets Break Down

Large file handling — the ST37 file can contain hundreds of thousands of rows. Spreadsheets slow down, crash, or truncate data at scale.

No data linking — connecting well records to operator profiles, facility data, or regulatory filings requires manual lookups or complex formulas. There is no built-in relationship between datasets.

Manual refresh — when the data updates, you must re-download, re-import, and re-filter. There is no automatic way to detect what changed since your last review.

No saved searches — filter criteria are applied manually each time. There is no way to save a search and quickly return to the same research scope when new data is available.

Team collaboration friction — spreadsheets are difficult to share and update simultaneously. Research often lives on one person's machine, making it inaccessible to the team.

No audit trail — when you add notes to a spreadsheet, there is no history of what changed, who changed it, or when.

Context is lost — a filtered list of operators tells you who they are but not what you already know about them. Research context lives outside the data.

The Research Platform Approach

A research platform like FracturingHub takes the same underlying AER data and organizes it into a purpose-built workspace. Here is how the approach differs:

How It Works

Log into the platform, search by location, operator, well status, or other available attributes, review operator views with linked public well records, save searches and operators to watchlists, add notes and tags to records, and export filtered results as CSV for CRM import or outreach.

What Research Platforms Do Well

Speed — search thousands of records in seconds without building filters manually.

Data organization — public well and operator records are organized into searchable views so researchers can reduce manual cross-referencing.

Saved searches with alerts — define your criteria once and receive updates when new data matches.

Team access — multiple team members can search, review, and add notes from the same workspace.

Audit trail — notes, tags, and status changes are tracked over time.

Research stays with the data — notes and context are attached to specific operators and wells, not lost in separate files.

Where Research Platforms Have Trade-offs

Subscription cost — you are paying for the platform, not just the data. For small teams or occasional research, this may not justify the cost.

Less customization — you work within the platform's interface and cannot modify the data structure or formulas.

Learning curve — new users need time to learn the platform's features and workflow.

Dependency on the platform — if the platform has issues or changes its features, your workflow is affected.

Cost Comparison

The true cost of each approach is not just the subscription fee — it is the time your team spends on research:

Spreadsheet cost — no direct cost, but a significant time investment. A typical research session may take one to three hours to download, filter, sort, and cross-reference data. Over a month, that adds up to ten or more hours per team member dedicated to data manipulation instead of outreach.

Platform cost — a monthly subscription fee, with the trade-off that repeated research sessions may become faster and easier to document.

The break-even point depends on how frequently your team does research and how many hours you currently spend on data manipulation. For teams doing weekly research across multiple regions, the time savings typically justify the platform cost within the first month.

When Spreadsheets Are Enough

Spreadsheets work well when: you are researching a small number of operators or wells, your research is infrequent or one-time, you have a single person doing the research and do not need to share it, and you are comfortable with the manual workflow.

When You Need a Platform

A research platform makes sense when: your team does regular weekly or biweekly research, you are tracking multiple regions or operator groups, you need to share research across team members, you want to monitor for changes without manually re-running searches, and the time you spend on data manipulation is time taken away from outreach.

A Hybrid Approach

Many teams use both approaches in combination. A research platform handles the heavy lifting — searching, filtering, data linking, and monitoring — while spreadsheets are used for specific analyses, reporting, or CRM preparation. This hybrid approach captures the efficiency of the platform while maintaining the flexibility of spreadsheets for tasks where they excel.

Best Practices for Either Approach

Define your criteria before you search — whether you use a spreadsheet or a platform, knowing what you are looking for first prevents wasted effort.

Save your research — in a spreadsheet, save filtered tabs and note what each filter was. In a platform, save searches and add notes. Research that is not saved must be repeated.

Verify before outreach — in either approach, confirm key assumptions against current data before contacting an operator.

Review and update regularly — data changes. Set a cadence to refresh your research regardless of your tool.

Quick Checklist

Assess how frequently your team does oilfield research

Calculate how many hours per week your team spends on data manipulation

Determine whether your research needs to be shared across team members

Decide whether saved searches and monitoring would improve your workflow

Evaluate whether a platform subscription is justified by the time savings

If using spreadsheets, establish a consistent save and naming convention

Regardless of tool, always define criteria before searching and save research after