Deepwater turbidite QI: Girassol-style fluid prediction

The basin and the field

Block 17 sits in 1300-1500 m water depth offshore Angola. The Congo deep-sea fan deposited a stack of sand-rich turbidite intervals through the Late Miocene and Pliocene. Salt mobilization from the underlying Aptian Loeme salt has created complex structural traps over much of the area. Girassol is a STRATIGRAPHIC TRAP: the reservoir sands are channel-lobe complexes whose shapes themselves are the trap geometry. Specifically:

• Reservoir interval: stacked turbidite sand bodies (channels + lobes) at ∼2000-2400 m TVDSS. Net reservoir thicknesses of 30-100 m per channel-lobe complex.
• Source rocks: deeper Cenomanian-Turonian organic-rich shales, oil-mature in the syn-rift section.
• Migration: vertical from source through fault networks, charging the Pliocene reservoirs.
• Seal: regional Pliocene mudstones above each turbidite package.
• Fluids: 35° API oil with a small dissolved-gas content; expected reservoir pressure modestly under-pressured.

The QI question

In the late 1990s, the operator faced a familiar deepwater problem: a 3D seismic survey covered the entire area, showing dozens of bright amplitude anomalies. Which of these are oil-bearing turbidite sands worth drilling? Which are wet sands or non-reservoir bright spots that look promising but won’t pay back? At deepwater drilling costs of $50-100M per well, every dry hole hurts.

The QI program was designed to answer one question per anomaly: is this a commercial-scale oil-bearing reservoir? Answering it requires three pieces of evidence working together (the THREE-LEG TEST):

• SAND: Is reservoir-quality sand present in this area? Net-sand cubes from inversion answer this.
• FLUID: Is the sand hydrocarbon-charged? AVO Class III intensity answers this.
• CLOSURE: Is the trap geometry capable of holding a column? Top-reservoir structure maps answer this.

Only a prospect that PASSES ALL THREE is a high-confidence drill target. Failing any one leg drops the prospect substantially.

Exercise — cycle the QI products and synthesize

• Open the widget in RMS amplitude mode. You see the channel-lobe architecture: a main NW–SE feeder splits into two distributaries that empty into a broad lobe complex in the SE corner. This is the GEOLOGY — inferred from seismic attribute analysis (Part 6) without any fluid-prediction information yet.
• Switch to AVO Class III intensity. Now you see only the FLUID-BEARING regions: the SE lobe (Lobe A), a mid-fan anomaly, and a small upstream pocket. Most of the channel-lobe system DOES NOT show AVO anomaly — those are wet sands or partially-saturated sands. The AVO map TELLS YOU WHICH SANDS HAVE OIL.
• Switch to Net-sand thickness. This is the QI inversion product (§7.4). High-net-sand (yellow) traces the channel axes and lobe interiors quantitatively. This is what feeds NET PAY computations (§7.6).
• Switch to Top-reservoir depth (structure). Regional dip is NW–shallow to SE–deep, with two LOCAL CLOSURES (red highs): one over Lobe A, one at the mid-fan. Without closure, hydrocarbons leak updip; closure is the structural prerequisite (Part 3).
• Switch to Composite prospect ranking. The brightest gold spots are the BEST DRILL TARGETS — they have all three legs passing simultaneously. The Lobe A target stands out as the highest-ranked; mid-fan is the secondary target. Other parts of the channel system drop out because they fail one or more legs.
• Note how the ranking map COMPRESSES the integration: a single visualization that the asset team can use to decide which 2-3 prospects to drill first. This is the SYNTHESIS DELIVERABLE that QI exists to produce.

Workflow walkthrough — Parts 0-8 in action

• Acquisition + Processing (Parts 1-2): wide-azimuth 3D survey acquired over Block 17. Anisotropic Kirchhoff pre-stack depth migration produces a depth-converted volume suitable for inversion. Anisotropy modeling (§8.3) corrects for VTI overburden of stacked Pliocene shales.
• Structural framework (Part 3): top-of-reservoir horizons picked semi-automatically (§2.3); fault network mapped (§2.5); structural closure analysis (§3.6) identifies the Lobe A and mid-fan closures.
• Stratigraphic interpretation (Part 4): channel-lobe architecture mapped (§4.4-4.5); the channel system’s downflow direction (NW→SE) constrains where lobe deposition is concentrated.
• Rock-physics calibration (Parts 5 + 7.2): well-log data from any nearby wells used to build a basin RPT. Brine sands plot at Ip~7400, Vp/Vs~1.80; oil sands at Ip~6800, Vp/Vs~1.72. Clear separation — a QI-favourable basin.
• Pre-stack inversion (§7.3): simultaneous Ip + Is + density inversion delivers 3D elastic cubes. Wavelet estimation per angle stack; LF model from regional structural framework + analog wells.
• Rock-property transforms (§7.4): Ip + Vp/Vs cubes → net sand, Vsh, Sw cubes via per-facies linear regression calibrated against well logs.
• AVO attribute extraction (§5.4 + §6): Class III intensity computed per voxel from near-/far-stack difference. Cross-validated against the inversion-derived Sw cube.
• Probabilistic facies + uncertainty (§7.5-7.6): each voxel assigned per-class probabilities (oil sand, brine sand, shale). Monte-Carlo prospect ranking integrates all uncertainties.
• Composite ranking + drill program: highest-ranked prospects drilled first. Girassol’s actual drill program achieved >60% commercial-success rate — well above the deepwater industry average of 30-40%.

Outcome and lessons

Girassol came online in December 2001 with first oil from the Pliocene reservoirs above expectations. The full Block 17 hub (Girassol + Dalia + Pazflor + CLOV) eventually produced more than 2 billion barrels by 2024 with declining contribution as the field matured. Multiple Lobe A and mid-fan-equivalent prospects were drilled successfully on the back of the integrated QI workflow. The lessons that transfer to other deepwater plays:

• QI works best where all three legs cooperate. Bright AVO + clean sand + structural closure is the magic combination. Fields where one leg is marginal (e.g., wet sand cluster, no closure) have much lower hit rates even with the best QI.
• Composite ranking is the deliverable, not individual attribute maps. The asset team needs ONE map that tells them WHERE TO DRILL, not five maps they have to integrate themselves.
• Ranked drill programs build portfolio momentum. Drilling the best prospects first keeps the success rate high through the early development. Investor confidence builds, capital becomes available for the next phase.
• Iteration matters: each well drilled adds CALIBRATION to the QI model. Girassol’s QI improved over time as more wells confirmed (or refined) the rock-physics template. Today’s QI in Block 17 benefits from 20+ years of well-tied calibration.
• Failures are informative: even a few unsuccessful wells in the original program identified RPT calibration issues in specific stratigraphic intervals. Today those intervals are flagged with extra uncertainty.

Where this workflow generalizes — and where it doesn't

The Girassol workflow is the GOLD STANDARD for QI-favourable deepwater clastic plays:

• Generalizes to: West African deepwater (Niger Delta deepwater, Equatorial Guinea, Ghana), Brazil Campos Basin Tertiary, Gulf of Mexico Miocene-Pliocene, Norwegian Sea Tertiary turbidites. Anywhere with bright AVO Class III on Pliocene-Miocene clastic reservoirs.
• Does NOT generalize to: tight gas sands (Class II AVO, ambiguous fluid signal); carbonate reservoirs (different rock physics, often non-Class III); over-pressured Paleogene sands with complex AVO; reservoirs in heavily faulted compartments where compartment-by-compartment uncertainty dominates over QI signal.
• The Girassol-style workflow is also the template for CO2 storage screening. Replace "is there oil here?" with "is the storage reservoir present + sealed + structurally closed?" — same three-leg test, slightly different attributes.