Build production forecasts from wells that actually belong in the analog set.
Type curves are only as reliable as the wells behind them.
When teams plan a development program, evaluate acreage, book reserves, or underwrite an acquisition, they often rely on offset wells to estimate future production. When the best analogs sit outside the company’s operated position, that analysis depends heavily on public records and third-party datasets.
Those sources can provide useful coverage. They do not always provide the context needed to determine whether two wells are truly comparable.
A well may be assigned to the wrong producing interval. A broad formation label may combine multiple benches. Completion design, spacing, lateral length, development timing, downtime, or nearby activity may materially affect performance. If those differences are not identified, the wrong wells can shape the curve.
BasinIQ helps teams build more defensible production expectations by combining proprietary producing-formation intelligence, normalized public records, well-level production history, completion context, satellite-observed activity, and internal type curve assumptions.
The goal is not simply to add more wells to the analysis.
It is to identify the wells that belong there.
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A Precise Curve Can Still Be Built on the Wrong Wells
Type curves often appear more certain than the underlying data deserves.
The curve may be mathematically sound. The analog population may still contain wells from different benches, different development generations, different spacing regimes, or materially different completion designs.
That creates a difficult problem for reservoir and evaluation teams. They are expected to defend production expectations even when the public data does not clearly show why each well belongs in the analog set.
Common issues include:
- Production data that trails actual well performance
- Producing intervals that are missing, unclear, or misclassified
- Broad formation labels that hide bench-level differences
- Wells with different lateral lengths, completion intensity, spacing, or development timing grouped together
- Parent-child effects or frac interference that distort production
- Downtime or operating constraints treated as reservoir performance
- Outliers that pull the curve higher or lower
- Basin-wide averages applied to a much narrower area of interest
When those issues go unresolved, the type curve may reflect the available dataset rather than the wells the operator actually plans to drill.
The Wrong Analog Set Creates More Than a Forecasting Error
A weak type curve does not stay inside the reservoir model.
It affects acreage value, reserves assumptions, development sequencing, capital allocation, financing discussions, and acquisition underwriting.
An overstated curve can make inventory look more economic than it is. An understated curve can cause a team to undervalue acreage, delay development, or leave opportunity unrecognized.
The greatest risk is often not an obvious mistake. It is a reasonable-looking curve built from wells that should have been excluded, separated, or adjusted.
No technical team should have to defend a forecast without being able to explain:
- Why each analog was selected
- Which producing interval each well represents
- What differences were normalized
- Which wells carry lower confidence
- How nearby activity or operational history affected performance
- What changes when questionable wells are removed
BasinIQ Helps Validate the Wells Behind the Curve
BasinIQ brings the evidence needed for analog selection into one analytical workflow.
Teams can evaluate an area of interest using proprietary producing-formation data, public production records, well-level history, completion information, internal assumptions, and SynMax satellite-derived activity intelligence.
This helps reservoir and evaluation teams distinguish between wells that are geographically close and wells that are actually comparable.
Validate producing formation and bench
Public records may assign wells to broad formations or contain incomplete producing-zone information.
BasinIQ helps refine that context so teams can separate wells by the producing interval most relevant to the planned or evaluated development.
This reduces the risk of combining wells that appear similar in a public database but produce from materially different rock.
Compare development context
Two wells in the same formation may still represent different development concepts.
BasinIQ can help compare variables such as:
- Formation and bench
- Landing zone
- Lateral length
- Spacing
- Stage count
- Proppant and fluid intensity
- Completion generation
- Development timing
- Parent-child relationship
- Nearby drilling and completion activity
These distinctions help teams determine whether performance differences are likely tied to reservoir quality, well design, development sequence, or operating conditions.
Identify wells that distort the forecast
Some wells should not be allowed to drive the curve without further review.
BasinIQ can flag wells affected by:
- Uncertain producing-formation assignments
- Material downtime
- Frac interference
- Parent-child degradation
- Incomplete production history
- Operational constraints
- Unusual completion designs
- Misclassified status
- Production performance far outside the relevant population
These wells may still provide useful information. They should not automatically carry the same weight as higher-confidence analogs.
How the Workflow Works
1. Define the target
Select the area of interest, planned well, development program, or asset under evaluation. Provide the current type curve and any approved internal assumptions.
2. Validate the analog population
BasinIQ evaluates the candidate wells using producing-formation confidence, production history, completion context, spacing, development timing, and nearby field activity.
3. Rebuild the production view
Your team receives a refined analog set, confidence flags, excluded or adjusted wells, and a clearer view of how the type curve changes when only relevant wells are included.
BasinIQ does not replace reservoir judgment. It gives reservoir teams a stronger evidentiary basis for applying it.
Questions Your Team Can Ask
BasinIQ can help answer questions such as:
- Are the wells behind this type curve actually comparable?
- Which wells in this area are producing from the same formation or bench?
- Which public-data classifications are too broad for this analysis?
- Are any wells misclassified or missing reliable producing-zone information?
- Which wells should be excluded, separated, or given less weight?
- Are production differences tied to rock quality, spacing, completion design, or development timing?
- Has nearby drilling or completion activity affected any of the analog wells?
- Which wells are outperforming or underperforming the current curve?
- What happens to the curve when lower-confidence wells are removed?
- Which assumptions are most likely overstating or understating expected production?
- How does the curve change when the analog set is limited to comparable lateral lengths and completion designs?
- Can BasinIQ create an AOI-specific type curve with confidence flags and supporting evidence?
The point is to show why the curve should be trusted.
From Broad Offset Data to Relevant Offset Intelligence
Public and subscription datasets often organize wells for broad coverage. Type curve development requires a narrower standard.
The best analog set may need to distinguish between wells that share a county or formation name but differ materially in:
- Bench
- Reservoir quality
- Completion generation
- Spacing
- Development sequence
- Operating history
- Offset activity
BasinIQ helps teams evaluate those differences before they are averaged into a production expectation.
This is especially important in areas where public producing-formation data is incomplete or inconsistent. A more specific understanding of the producing interval can materially change which wells belong in the population and what the resulting curve suggests.
Why Satellite-Observed Activity Matters
Reported production does not always explain what happened around a well.
Nearby completion activity, parent-child development, frac interference, delayed turn-in-line timing, or extended downtime can affect the production history used in a type curve.
SynMax satellite intelligence adds field context that may not yet appear clearly in reported records. It can help teams understand when nearby activity occurred and whether that timing may have influenced the performance of an analog well.
That context does not automatically disqualify a well. It gives the evaluator a reason to review, adjust, or interpret it differently.
What Better Type Curves Support
For reservoir teams, better analog selection means production expectations that are easier to explain and defend.
For planning teams, it means development schedules and capital plans grounded in more relevant well behavior.
For reserves teams, it means clearer support for the assumptions behind booked volumes.
For A&D and private equity teams, it means stronger underwriting and fewer surprises after closing.
For executives and finance teams, it means capital decisions based on a clearer view of the range of likely outcomes.
The result is a forecast with a visible chain of evidence.
Built for Teams That Depend on Production Expectations
BasinIQ supports:
- Reservoir engineering
- Development planning
- A&D and corporate development
- Production engineering
- Asset teams
- Finance
- Reserves teams
- Executive leadership
- Private equity
- Asset evaluators
Know What Is Driving the Curve
BasinIQ helps teams move from broad offset assumptions to AOI-specific production intelligence.
It connects producing-formation context, public records, production history, completion design, nearby activity, and internal assumptions so teams can identify useful analogs, remove misleading ones, and understand what changes the forecast.
Before a type curve drives the next drilling plan, reserves case, or acquisition model, make sure the wells behind it deserve to be there.
Build the curve around comparable wells—not convenient ones.
Request a Type Curve Review
Not ready for a review? See a Sample Type Curve Analysis to view an example analog set with formation confidence, exclusion criteria, and supporting evidence.