Where ancient Nigerian earth meets tomorrow's intelligence — drilling smarter, finding faster, risking less across every Nigerian basin
Aeromagnetics · Seismic · Petrophysics · Image Analysis · Dry Hole Risk
MagnaTrace AI is the world's most deeply trained geoscience intelligence platform for Nigerian basin interpretation — a proprietary intelligence layer built on Nigerian basin physics, petrophysical standards, and exploration history, covering every sedimentary basin in Nigeria.
Five modules, one pipeline. Each one below is a different data type feeding the same underlying intelligence layer — not five disconnected tools.
Anomaly detection, geological classification, depth estimation, and ranked exploration targeting calibrated to Nigerian basement architecture.
DHI interpretation — bright spots, flat spots, phase reversals, AVO anomalies — all referenced to Niger Delta and inland basin seismic signatures.
Well log analysis (GR, Rt, NPHI, RHOB): Vsh, effective porosity, water saturation, net pay, permeability — calibrated to Agbada Formation benchmarks.
Upload seismic sections, core photos, or well log screenshots. MagnaTrace's visual interpretation layer identifies fault zones, bright spots, lithology, fractures, and gas-oil crossovers from raw pixels.
Integrated Probability of Success (PoS) scoring across all six petroleum system elements — referenced to Nigerian basin analogues and NUPRC standards.
One-click branded MagnaTrace AI report generation — professional, watermarked, shareable. Built for Nigerian industry decision-making.
MagnaTrace AI was built with the explicit objective of surpassing existing geoscience tools in Nigerian-specific basin intelligence — encoding the stratigraphy, petroleum systems, exploration history, and structural geology of all seven Nigerian sedimentary basins into every analysis.
MagnaTrace AI is being built as a global basin-specific geoscience intelligence platform. Nigeria is the first market and proving ground — not because the ambition stops here, but because the depth of regional geological context required to do this properly has to be built somewhere first, and Nigeria's sedimentary basins are where that foundation is being laid.
This is not "AI applied generically to geology." Every assumption, cutoff, correction model, and interpretation rule in MagnaTrace is built basin-first — starting with the Niger Delta's Akata-Agbada system and Nigeria's other six sedimentary basins, then extending the same discipline to new basins as the platform grows. The Nigerian basin intelligence already built is the foundation the rest of the platform is built on, not a feature to be diluted as MagnaTrace expands.
Three things converged to make basin-specific geoscience intelligence possible now, not before.
Four steps from raw data to a defensible exploration decision.
Select your basin. Select your module. Paste your data or upload an image. MagnaTrace AI's intelligence layer does the rest — basin-specific computation first, interpretation second.
Run two or more modules on the same prospect, then cross-check them here. This engine compares the platform's own outputs against each other and reports where they contradict.
Real dry holes get drilled partly because a petrophysical read and a geophysical read quietly disagreed and nobody forced the reconciliation before the rig moved. Conventional interpretation suites leave that check to the human. This one performs it explicitly.
Display multiple wells side by side on a shared depth axis. Run a petrophysical analysis on each well, add it here, then correlate.
A real petrophysical workflow, start to finish — the same path any well run through MagnaTrace follows.
A .LAS file is uploaded. MagnaTrace parses the curve set, cross-checks the header's declared depth range against the actual data, and flags unit mismatches automatically — a depth curve logged in feet doesn't get silently mislabeled as meters.
Vsh via an age-appropriate Larionov correction, effective porosity shale-corrected from the well's own shale baseline, water saturation via Archie or the Indonesian shaly-sand equation depending on shale content — every parameter and cutoff stated explicitly, not buried in a black box.
Reservoir intervals are named, characterized, and benchmarked against Agbada Formation norms — with an explicit basis for every quality call, not just a label.
Net pay, fluid type, and dry-hole risk are derived directly from the computed intervals — a well with no net pay is reported as high risk with the specific evidence that led there, not softened into a vague summary.
A structured report — Well Reference, Computed Parameters, Reservoir Intervals, Data Limitations, Recommended Next Steps — exportable as a branded PDF in one click.
Great Ufanobong founded MagnaTrace AI with a singular starting thesis: Nigeria's seven sedimentary basins deserved geoscience software that actually knew them — not a generic tool with Nigerian data bolted on. That conviction started as deep research inside a geology degree at Akwa Ibom State University, under Dr. Anietie Ekot, and has grown into the company being built today.
While global platforms like Oasis Montaj, Petrel, and Interactive Petrophysics are powerful general tools, none of them carry embedded, formation-specific intelligence about the Agbada-Akata petroleum system, the Nkporo-Ajali reservoir-seal pair, the Muglad-correlative Chad Basin play, or the growth fault architecture of the Niger Delta. MagnaTrace AI does.
That depth-first approach — build the intelligence layer properly for one region before claiming to generalize — is the same discipline MagnaTrace intends to carry into every basin it reaches next.
MagnaTrace is looking for the operators, geoscientists, technology partners, and investors who want to help shape what basin-specific geoscience intelligence becomes — starting here.