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02 Geology Services

Well Correlation & Petrophysical Integration

Tops, logs, image logs and petrophysical zone averages reconciled into one QC’d database across every deviated well.

Deliverable A correlated tops database plus correlation panels.

Correlation panel of four wells in depth, with log tracks, tops correlated from well to well and the oil-water contact marked
Synthetic demonstration data · 4-well correlation in depth (SSTVD) with the OWC Full size: 4-well correlation in depth (SSTVD) with the OWC

2.1

Tops Picking, Fault Cuts & Correlation Panels

Consistent tops in every well, including the hard ones.

Well-tops spreadsheet listing each top by well with its depth, TVT, TST, dip angle, dip azimuth and missing section at fault cuts
Synthetic demonstration data · Well-tops spreadsheet with fault cuts: TVT, TST, dip, azimuth, missing section Full size: Well-tops spreadsheet with fault cuts: TVT, TST, dip, azimuth, missing section

Scope

  • Tops picking and QC across deviated wells
  • Fault-cut identification: dip / azimuth and missing section
  • TST / TVT zonation by zone
  • GR, RDEEP and Sw log integration; fluid contacts (OWC / GOC) carried onto the panels

Proof Refreshed full-field thickness mapping by reinterpreting dozens of sub-seismic well faults and moving correlations from a lithostratigraphic to a chronostratigraphic framework; the maps met regulatory commingling requirements.

Deliverable

A correlated, QC’d tops database plus correlation panels.

Who it's for

Asset teams inheriting tops from several interpreters, or adding new wells to a mature field.

Ben Hilton and a colleague in high-visibility jackets holding up a fluvial depositional systems poster below sandstone cliffs

What I'm Really Good At

I am a data wrangler: tops from different interpreters, vintages and sources get reconciled into one consistent database before anything is mapped. My data-QC habits go back to testing Landmark DecisionSpace and GeoProbe, and at BP I set the modeling and QC workflows for a 14-geoscientist Petrel Studio project.

2.2

Stratigraphy: Image-Log, Log & Seismic Well-Top Harmonization

Tops that agree across image logs, logs and seismic. Combined with, and linked to, structural geomodeling.

The same four wells flattened on the TopCret_Res top and shown in true stratigraphic thickness, with zones correlated across the panel
Synthetic demonstration data · 4-well correlation flattened on TopCret_Res (TST) Full size: 4-well correlation flattened on TopCret_Res (TST)

Scope

  • Depositional fabric to log facies
  • Machine-learning-assisted depositional-environment interpretation
  • Mapping at subregional-to-local scales
  • SLB Quanta Geo image-log interpretation integrated with seismic response, reducing overburden drilling risk and enabling more effective well planning
  • Well tops linked to the structural geomodel, so framework updates and tops stay in step

Proof Taught on the first run of a multi-day paralic geology field course, with a 200-plus-page field guide and excellent attendee ratings, and spoke at an image-log workshop on the value of image logs.

Deliverable

Harmonized well tops with facies and environment calls, mapped at the scale you need.

Who it's for

Teams planning wells through complex overburden, or reconciling tops between disciplines.

Core integration

I've participated in about two dozen core workshops and facilitated four to five of them with multidisciplinary teams, integrating core description, image facies and depositional environments to predict flow units and reservoir performance.

A roadcut through stacked sandstone and mudstone beds

What I'm Really Good At

I trained in sedimentology and stratigraphy, so I read depositional fabric first and then tie it to logs and seismic. At BP I completed a stratigraphic-to-seismic characterization of 4,000+ ft of overburden using Quanta Geo image logs, published as an internal integration standard.

2.3

Well Pointsets: Zonal Thickness & Petrophysical Zone Averages

Spatial representation of well information is critical to mapping initiatives and modeling efforts.

Pointset attribute list: true stratigraphic and true vertical thickness, net rock and net pay, porosity, water saturation, contacts, permeability, GR and resistivity averages
Synthetic demonstration data · Pointset attributes: thickness and zone averages Full size: Pointset attributes: thickness and zone averages
Table of zone thickness by well, giving each zone's start depth, name, and its TVT and TST
Synthetic demonstration data · Zone TVT / TST by well Full size: Zone TVT / TST by well

Scope

  • Pointsets that carry, at every well, zonal thickness (TST / TVT) and petrophysical zone averages: N:G, net pay, PORO, Sw, PERM, GR and RDEEP averages, and OWC / GOC contacts
  • Each point flagged as unfaulted, reconstructed or faulted, so fault-affected thickness never contaminates a map
  • True TVT tied to image logs and seismic dip / azimuth; image-log dips calibrated to seismic
  • The same pointsets feed thickness and property maps, volumetrics and 3D property models

Deliverable

Maps plus spreadsheets, built to be easily maintained and updated as new wells are drilled.

Who it's for

Asset teams on deviated or high-dip wells, where measured thickness overstates the reservoir.

Data wrangler and integrator

I pull messy, multi-source subsurface data (well logs, tops, image logs, seismic, maps, core and production) into one consistent model that geologists, petrophysicists and reservoir engineers can all trust. At BP I served as the G&G–reservoir engineering integrator for deepwater Gulf of America fields, led full-field 3D static modeling, and administered a Petrel Studio project for 14 geoscientists. My specialty is petrophysical zone averaging and thickness mapping in structurally complicated, faulted fields.

Sweeping red cross-bedded sandstone foresets above a reservoir

What I'm Really Good At

Building well pointsets is where my data-wrangling pays off: thickness and petrophysical zone averages for every well and zone, in one place, mapped where the wells actually are. At BP I built a Petrel workflow that rapidly updated and displayed petrophysical zone averages spatially for development decisions.

Synthetic demonstration data: all datasets shown were built solely for demonstration purposes and are not client data.

How to engage

Start small, prove value on one block, then scale. Fast turnaround, remote, Houston-based.

  1. 30-minute fit call

    We walk through your field, data and decision. You leave with a clear view of where the subsurface risk sits and whether I am the right fit.

  2. Fixed-scope pilot

    One fault block or one zone, fixed price and fixed scope. You see my framework, zone averages, maps and QC on your own data before committing further.

  3. Full study

    Field-wide framework, correlation, mapping and volumetrics, with handoff-ready grids for reservoir engineering.

Book a 30-minute fit call

Remote delivery · Houston, TX · Petrel and RMS on your license or mine

Let's map your next development well.

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