Fine Resolution Core Mineralogy from Infrared Spectroscopy and How to Use

These Data to Calibrate Logs Dr Adam K Moss – Core Analysis Petrophysicist, AKM Geoconsulting Ltd

Gavin Hunt & Richard Williams – Spectra-Map Ltd

10th January 2019

Light from an Infrared lamp is reflected off a core surface and recorded by an imaging reflectance spectrometer into spatial and spectral dimensions to form a hyperspectral image data cube.

Mineralogy using Infrared Spectroscopy

Mineralogy using Infrared Spectroscopy

SpecCam spectra of some of the commonly encountered clay minerals with their diagnostic 2.2μm Al-OH absorption features (a), and carbonate and chlorite minerals with their diagnostic 2.3μm absorption features (b). Functional combination and overtone group absorptions for the common SWIR active minerals encountered in hydrocarbon projects are shown in (c).

Mineralogy using Infrared Spectroscopy

Image (mineral) maps from a one metre section of clastic core from the North Sea, showing a False Colour Composite (FCC) (a), the chlorite content (b), phengite content (a mica K(AlMg)2(OH)2(SiAl)4O10 ) (c) and the hydrocarbon type (d).

Mineralogy using Infrared Spectroscopy

How to Use SpecCam to Help Select SCAL Plug Samples

1) Measure core spectral gamma & CT scan core in barrels.

2) If core is competent remove from core barrel & clean away drilling mud. If core is friable, orientate core using

CT scan images & cut a 10-15cm wide ‘window’ in core barrel, remove ‘window’ & clean mud from core surface.

3) Within 15-20 mins of exposing core surface scan core using SpecCam. Use a 2-3cm wide scan and scan each

0.5cm or 1cm down core length.

4) Process SpecCam data and supply mineralogy information within 10-15mins for each one meter section of core.

5) Petrophysicist & geologist can now use the SpecCam mineralogy, spectral gamma data & the CT scan images to

help with SCAL sample selection.

• A joint study between AKM Geoconsulting & Spectra-Map Ltd

• We use these high resolution mineral data from reservoir core to calibrate common log interpretation

models, including:

• Shale/clay volume from gamma logs

• density log porosity models

• clay bound water from NMR

• The fine scale mineralogy data are also used to evaluate mineralogical controls on permeability.

• “How to use Infrared Spectroscopy Mineralogy Data to Calibrate Logs” – Presented at the 2017 Society

of Core Analysts Conference, Vienna, Paper No. SCA2017-067

How to use Infrared Spectroscopy Mineralogy Data to Calibrate Logs

Slabbed North Sea core totalling 64.5ft in length was available. The core was scanned at a resolution of one core width line scan per 0.5mm.

The measured spectra were deconvoluted to determine core mineralogy and the modal percentage of each mineral calculated.

Mineralogy using Infrared Spectroscopy

Mineralogy using Infrared Spectroscopy

Total gamma log and optimised gamma min and max

values versus depth for the non-linear gamma.Spectrometer total clay volume versus depth.

𝑉𝑠ℎ ∗ =𝐺𝑅 𝑣𝑎𝑙𝑢𝑒 (log) − 𝐺𝑅(min)

𝐺𝑅 (max) − 𝐺𝑅(min)

𝑉𝑠ℎ = 0.33 (22𝑉𝑠ℎ∗ − 1)

Where:Vsh* = Shale/clay volume (fraction)GR value (log) = Log gamma value (API)GR (max) = 100% shale (API)GR (min) = 0% shale (API)

The gamma minimum and

maximum values at each depth

are obtained using Excel Solver

to obtain the values needed to

match the modelled volume of

shale/clay with the total clay

volume measured by the core

spectroscopy

Optimising parameters in the Gamma Shale Model Using Infrared Spectroscopy Mineralogy

Operator GR Min

Operator GR Max

Optimising parameters in the Gamma Shale Model Using Infrared Spectroscopy Mineralogy

The mineralogy data from

the core spectroscopy

scanner can be used to

calculate grain/matrix density

at each 0.5mm interval. A

grain density for each

mineral is defined and the

relative proportion of each

used to calculate average

grain density at each depth.

If the density of the mineral

grains and fluid are known an

estimate of porosity can be

made using:

Spectrometer mineralogy modelled and core plug

grain density versus depth.Density log and core plug porosity versus depth.

𝜙 =𝜌𝑚𝑎 − 𝜌𝑏𝜌𝑚𝑎 − 𝜌𝑓

Where:ϕ = Total porosityρma = Grain (matrix) density (g/cc)ρb = Bulk (log) density (g/cc)ρf = Fluid density (g/cc)

Using Core Mineralogy to Optimise Porosity from

the Density Log

PlagioclaseZone?

AnhydriteZone

• The clay bound water NMR T2 cut-off can be obtained for individual core plugs by inspection of the humidity

oven dried sample T2 distributions.

• Clay bound water volume can be calculated if we know both the clay volume and the clay porosity.

• For the purposes of this workflow illustration we assumed a clay porosity of 20%.

• The calculated clay bound water volumes values are then used to estimate the clay bound water T2 cut-off

using the ‘sum of amplitudes’ method.

Using Core Mineralogy to Optimise Clay Bound Water T2

Cutoff

• In many clastic formations clay and cement type and volume have a large effect on permeability.

• High resolution mineralogy data can be used to evaluate the mineralogical controls on permeability.

• The infrared imaging spectrometer can also detect solid and liquid hydrocarbon.

• The hydrocarbon parameter appears to relate to permeability, although the link is weak.

Core Mineralogy Controls on Permeability

Total Clay vs Mini-Perm Permeability

Total Dolomite vs Mini-Perm Permeability

Total Hydrocarbon vs Mini-Perm Permeability

• Infrared imaging spectrometer measurements on core produce high resolution

mineral data.

• Workflows have been developed to use these data to help calibrate log

interpretation models and evaluate mineralogical controls on permeability.

• Spatially continuous mineral data of this type are invaluable to both geologists

and petrophysicists.

Conclusions

Thank You for Your Attention – Any Questions?

Services Offered by AKM Geoconsulting Ltd (adam@akmgeo.co.uk)

· SCAL PROGRAMME DESIGN AND MANAGEMENT

· QUALITY CHECKING AND ANALYSIS OF SCAL DATA

· CORE TO LOG INTEGRATION

· INTEGRATION OF CORE DATA WITHIN RESERVOIR MODELS

· SATURATION HEIGHT FUNCTION MODELLING

· TRAINING AND MENTORING