Most Canadian operators have three forecasts that matter, and they live in three different spreadsheets. The reservoir engineer runs decline curves in one model. Finance calculates ARO provisions in another. Operations builds maintenance and capital budgets in a third. Each spreadsheet may be right on its own. But nobody can see the connection between falling production revenue and rising abandonment obligations until both numbers land on the same board slide. By then, your options have already narrowed.
Oil and gas forecasting software exists to fix that. Not by adding a fourth tool, but by connecting the three forecasts that already drive every operational and regulatory decision you make.
For Alberta and BC operators, the Licensee Capability Assessment under Directive 088 now evaluates whether operators can meet their closure obligations based on overall financial health. That assessment ties together the same three numbers most operators forecast in isolation. The AER is connecting the dots. Operators who do not connect them internally are building a regulatory position they cannot defend in a review.
The scale of unfunded liability in Alberta turns accurate forecasting into something closer to existential than operational.
Start with the liability gap. The AER has publicly reported multi-billion-dollar estimates for total oil and gas cleanup in Alberta for years. A 2018 internal AER presentation, later reported in the Canadian press, put the real figure several times higher than the public one. The gap between standardized AER liability calculations and real-world cleanup costs is one of the most persistent numbers-do-not-match stories in Canadian energy, and it has not closed.
Mandatory closure spending is also accelerating. Directive 088’s Closure Nomination Program sets rising annual industry spending targets for abandonment, remediation, and reclamation work. Operators who build their closure budgets strictly from standardized AER cost assumptions routinely discover the gap during execution, when the actual abandonment and reclamation cost for a deep or remote well comes in at several times the standardized estimate. If you budgeted for the standardized number, you run out of budget. If you budgeted for reality, you need data that nobody on your team has centralized yet.
The orphan well inventory tells the rest of the story. The Orphan Well Association’s active inventory has grown from a few hundred wells a decade ago to several thousand today. Estimated cleanup costs have climbed into the billion-dollar range, and the industry-funded levy supporting the OWA has grown along with it. Companies that underestimated their liability exposure are the ones that ran out of runway, could not transfer their licences, and eventually became someone else’s cleanup problem. Every one of those orphan wells had an operator who thought their forecast was good enough.
And auditors are asking harder questions. IAS 37 requires organizations to recognize provisions for asset retirement when obligations arise. Auditors now routinely ask how production decline assumptions affect ARO timing, how budget allocations connect to liability estimates, and whether the methodology traces back to source data. Those questions span all three forecasts. Answering them from three disconnected spreadsheets requires weeks of reconciliation before every audit cycle.
Arletta Environmental is an Alberta-based environmental consulting firm with more than 500 active projects and millions of dollars in managed budgets each year. Its project management team handles everything from Phase I assessments to multi-million-dollar remediation programs across a diverse client portfolio.
Before centralizing its data, Arletta’s team was growing, but its project management tools were not keeping up. Spreadsheets were the backbone, but they were starting to show their limits where project complexity and increasing portfolios demanded more.
Project tracking approaches varied across the team. Project managers had the flexibility to organize and track costs on their own, but information was not always standardized across projects or clients. When coverage was needed, additional handoff time was often required to ensure continuity. A significant portion of each PM’s time went to manually compiling costs, reconciling field tickets, and updating spreadsheets instead of the technical work they were hired to do.
Annual budget planning consumed weeks of non-billable time. At the start of each year, creating program budgets for every client, getting approvals, and distributing the approved work to PMs took weeks of effort from ownership and the PM team. It was entirely manual and entirely non-billable.
Ownership had no visibility without asking. Christine Niemiec, President, and Jennifer Carscallen, CEO of Arletta, could not view business operations, a client overview, or deep-dive into any project without putting in a report request to a PM. If a client called on a Friday afternoon, answering with accuracy immediately was not possible.
The shift to centralized cost tracking and project management changed the operating model. Annual budget planning collapsed from weeks to days. Each PM now saves approximately two hours a week on cost tracking and reporting. Ownership can pull any report at any time without asking anyone.
Jennifer Carscallen, CEO of Arletta, described the impact: “Fieldshare has been a game-changer in terms of operations visibility and transparency of cost tracking. It has significantly reduced administrative load, duplication and manual entries. We use it to accurately forecast budgets and as a long-term planning tool.”
That last phrase, “long-term planning tool,” is the forecasting dimension. When budget data, project costs, and client program planning all live in one system, forecasting becomes a byproduct of normal operations. Not a separate exercise anyone has to remember to run.
Arletta shows the planning side clearly. For operators managing actual well assets, the same dynamic plays out across the three forecasting pillars, and the consequences are worse when the numbers do not line up.
ARO estimates drift from reality. ARO forecasting software needs current field data to produce a defensible number. When liability estimates sit in a finance spreadsheet that refreshes quarterly while field conditions change weekly, the ARO figure is always stale. A well that developed new contamination six months ago is still carried at its pre-contamination abandonment estimate. That gap between spreadsheet and field is exactly where audit findings and budget shortfalls show up.
Production decline affects everything downstream. A well’s decline curve determines when it approaches economic limits, which determines when abandonment becomes a planning priority, which determines when the ARO provision needs to be funded. When decline curves live in a reservoir tool and ARO provisions live in a finance model, the connection between “this well is declining faster than expected” and “we need to accelerate closure budget for this asset” has to be made manually, by someone, every quarter. At scale, nobody does this in real time. Usually nobody does it at all.
Budget allocation becomes guesswork. Operators allocate capital across production optimization, facility maintenance, regulatory compliance, and abandonment. A well approaching economic limits might look like a maintenance candidate based on production data alone. Overlay the ARO estimate and you see that abandonment costs are lower now than they will be in three years as the site deteriorates, and the decision flips. Without integrated visibility, that tradeoff is invisible until the commitment has already been made.
Summit Earth, an environmental consulting firm operating across Canada, the USA, and Australia, ran into the budget visibility problem directly. Without centralized cost tracking, projects frequently blew past budgets with little warning, and the damage to the client relationship was done before anyone could get ahead of it. After centralizing their project and cost data, Summit Earth saw a 50% drop in how often projects went over budget. Their VP of Operations said the difference was not better estimating. It was seeing the variance at 60% of budget instead of discovering it at 110%. The firm also cut five hours a week off invoicing alone.
Long Run Exploration found the same pattern with reclamation planning. After replacing their legacy software with centralized project management, their annual reclamation planning now takes half the time it used to.
The operators who have moved past disconnected spreadsheets did not buy a forecasting tool. They centralized their asset data so that forecasting became possible.
Arletta’s annual planning collapsed from weeks to days because approved work now flows directly into the system where costs are tracked. PMs see their assignments the moment budgets are approved. Ownership can pull any report at any time. The annual planning exercise stopped being a data assembly project and became a strategic discussion about priorities, because the data was already there when the meeting started.
Summit Earth catches budget variances before they become overruns because approved budgets connect directly to ongoing spend tracked in the field. That 50% reduction in overrun frequency did not come from better estimating. It came from seeing the variance at 60% of budget instead of 110%.
Long Run’s reclamation planning runs at half the time because well data, site conditions, and cost history live in the same place where planning happens. When a field crew identifies new contamination, the environmental restoration tracking data updates the remediation cost estimate, which flows directly into the planning timeline. No manual bridging between systems. No lag between what the field knows and what the forecast reflects.
Audit preparation becomes a non-event across all three forecasts. When every cost entry, every field observation, and every assumption is automatically documented with a timestamp and a user, the audit trail generates itself. The documentation side of oil and gas industry challenges gets solved as a byproduct of connected data, not as a separate pre-audit scramble.
The regulatory direction is clear. The AER’s holistic licensee assessment evaluates operational capability alongside financial health. Operators whose documentation runs on manual reconciliation between disconnected spreadsheets tell a very different story to a reviewer than operators whose field data flows directly into a forecasting model.
For operators still running spreadsheet-based tracking across ARO, production, and budgets, the compounding risk grows with every well. The liability gap between AER-assessed costs and actual costs is not closing. The $750 million closure spending target is not going down. The orphan well inventory is not shrinking.
Arletta went from weeks to days on annual planning. Summit Earth cut budget overruns by 50%. Long Run halved their reclamation planning timeline. These are not theoretical projections. They are measured results from operators who stopped forecasting in isolation.
The question is not whether disconnected forecasting will create a problem. For most operators managing more than a few dozen wells, it already has. The question is whether you find the gap during your own planning, or whether an auditor finds it for you.
Want your ARO, production, and budget forecasts running off the same source of truth? Book a Fieldshare demo. We will walk your team through how Arletta, Summit Earth, and Long Run collapsed weeks of annual planning into days and caught budget overruns before they hit the client.
