interpretation, Oil & Gas Glossary

In geophysics and petroleum geology, interpretation is the disciplined process of analyzing acquired data to build reasonable, testable models of the subsurface and to predict the properties, structures, and fluid content of rock formations that no one can directly observe. The dominant form is seismic interpretation, in which a geophysicist studies the reflection patterns recorded by a seismic survey to map geological boundaries, faults, folds, stratigraphic pinch-outs, and potential hydrocarbon traps. Reflection data arrive as travel times measured in milliseconds, and one of the interpreter's first tasks is to convert those times into true vertical depth using a velocity model, so that a structure measured at 1,800 milliseconds two-way time can be tied to a target at roughly 2,400 m (about 7,870 ft). Interpretation is never performed in isolation. It integrates well logs, core descriptions, biostratigraphy, pressure data, and production history, and it leans heavily on seismic data quality, the resolution of the wavelet, and the accuracy of velocity control. In the Western Canadian Sedimentary Basin, interpretation underpins almost every drilling decision: picking the top of the Leduc reef, tracking the erosional edge of the Cardium sandstone at Pembina, mapping the structural closure on a Nisku pinnacle, or correlating the Montney from a vertical pilot hole into a kilometre-long horizontal lateral. Modern interpretation is increasingly quantitative. Geophysicists extract seismic attributes such as amplitude, instantaneous frequency, coherence, and curvature, then calibrate them against rock-physics models to predict porosity, lithology, and pore fluid. Amplitude-versus-offset analysis can flag a possible gas-charged Duvernay interval, while inversion converts reflectivity into acoustic impedance that maps directly to reservoir quality. Because every interpretation is a hypothesis rather than a fact, interpreters explicitly track uncertainty, build multiple equally valid scenarios, and rank prospects by the probability that the model is correct. The economic stakes are large: a single deep WCSB exploration well can cost CAD 8 to 20 million, so a misinterpreted fault or a velocity error that places a target 40 m off depth can turn a planned producer into an expensive dry hole. Sound interpretation is therefore both a technical craft and a risk-management exercise, blending pattern recognition, physics, statistics, and hard-won regional geological knowledge.

Key Takeaways

Models, Not Measurements: Interpretation produces a reasoned model of the subsurface, not a direct observation. Seismic reflections record acoustic impedance contrasts in two-way travel time, and the interpreter must convert milliseconds to depth, tie the data to well control, and account for the fact that several geologically different models can fit the same data equally well.
Time-to-Depth Conversion Is Critical: A reflector at 1,800 ms two-way time may correspond to roughly 2,400 m (about 7,870 ft) depending on the velocity field. A velocity error of even 3 to 5 percent can shift a target tens of metres, which is enough to miss a thin Cardium or Viking sand or to mislocate the crest of a Nisku structural closure.
Attributes Add Quantitative Power: Beyond structure, interpreters compute seismic attributes such as amplitude, coherence, curvature, and instantaneous frequency, then use amplitude-versus-offset and seismic inversion to predict porosity, lithology, and pore fluid, turning a structural picture into a reservoir-quality forecast for Montney or Duvernay targets.
Integration Reduces Risk: Robust interpretation fuses seismic with well logs, core, biostratigraphy, and pressure data. The well ties calibrate the wavelet and velocity, while logs confirm whether a bright amplitude is gas, lithology, or tuning, converting a standalone seismic guess into a multi-disciplinary, defensible interpretation.
Uncertainty Is Explicit: Because interpretation is a hypothesis, professional workflows carry multiple scenarios and assign confidence. With a deep WCSB well costing CAD 8 to 20 million, ranking prospects by the probability the model holds, and flagging where fault location or velocity is poorly constrained, is core to capital discipline.

Structural Interpretation Versus Stratigraphic Interpretation

Structural interpretation maps the geometry of rock surfaces: it traces horizons across a 3D seismic volume, identifies and links faults, and builds depth-structure maps that reveal traps such as anticlines, fault closures, and the draped crests of carbonate reefs like the Leduc and Nisku. Stratigraphic interpretation instead reads the internal architecture of sediment packages, picking onlap, downlap, channels, and unconformities to predict where porous reservoir rock was deposited. In the WCSB, the Cardium at Pembina is a classic stratigraphic play where the productive conglomerate thins and pinches out, while the Montney is mapped both structurally and stratigraphically. Most prospects require both lenses together, since a perfect structure without reservoir-quality rock holds nothing.

Workstations, Velocity Models, and Quality Control

Interpreters work on specialized software such as Petrel, Kingdom, or DecisionSpace, loading migrated seismic volumes, well logs, and deviation surveys into a shared 3D project. The single largest source of error is the velocity model used for time-to-depth conversion, so interpreters build it from sonic logs, checkshot surveys, and stacking velocities, then test it against multiple wells. Quality control is continuous: looping seismic lines to confirm a fault is real and not a migration artifact, checking that a mapped horizon closes consistently in three dimensions, and confirming that a bright amplitude correlates with known pay rather than a coal or a tuning effect. Disciplined QC is what separates a drillable prospect from an expensive optimistic map.

Fast Facts

The interpretive leap from reflection patterns to oil discovery was first proven commercially in the 1920s, when reflection seismology found the Maud field in Oklahoma in 1927 and triggered a discovery wave. Yet the resolution limit has barely a parallel in everyday life: at typical WCSB target depths, conventional seismic can resolve beds only down to roughly 8 to 15 m thick, meaning a productive 4 m Viking sand often sits entirely below the tuning thickness and must be inferred from amplitude behaviour rather than seen directly on the section.

Interpretation depends on the quality of the input seismic data, since noise, poor migration, and low fold all degrade the confidence of any structural or stratigraphic pick. Accurate velocity control governs time-to-depth conversion and therefore where a target is actually drilled. The seismic attribute toolkit extends interpretation from geometry into quantitative reservoir prediction, while a sound understanding of the reservoir itself, its porosity, permeability, and fluid contacts, is the ultimate purpose of building the model in the first place.

Real-World WCSB Scenario: A Nisku Pinnacle at Pembina

A mid-cap operator working the Pembina area shoots a 60 km2 3D survey at a cost near CAD 2.4 million to chase a suspected Nisku pinnacle reef beneath roughly 2,650 m (about 8,690 ft) of section. The interpreter maps a 22 m structural closure on the reflector at 2,050 ms two-way time, ties it to two offset wells with checkshot velocities, and confirms a coherent amplitude anomaly draping the crest. Rock-physics modelling suggests porosity near 9 to 12 percent, consistent with gas charge under AER pool-classification practice.

The operator drills the crest and encounters 18 m of porous Nisku dolomite, validating the structural and attribute interpretation within 6 m of predicted depth. The CAD 11 million well ties back to existing infrastructure and pays out in under three years, while a sidetrack proposed off a weaker, lower-confidence amplitude flank is deferred pending reprocessing, exactly the kind of risk-ranked decision disciplined interpretation is meant to support.