Core logging is the systematic recording of what you observe in drill core — rock type, texture, structure, alteration, mineralisation, and geotechnical properties — at measured depth intervals along the length of a drillhole. It is the foundational data collection step in mineral exploration: the moment between pulling core out of the ground and building a resource model. Get it right and every estimate, every interpretation, every decision downstream benefits. Get it wrong and the errors compound silently for months before anyone notices.
This guide covers what core logging actually is, what types exist, how it’s done in practice, and how the data flows from the field into the models that drive exploration decisions.
Why core logging exists
Drilling is expensive. Depending on depth, diameter, terrain, and remoteness, a single hole can cost anywhere from $50 to $500 per metre to drill. A 500-metre diamond hole in northern Canada can run $150,000 before assay costs. When you’ve committed that capital, you want to extract every piece of information the core can give you.
Core logging is how you do that. It transforms physical rock into structured data: depth-referenced records of what the ground looks like, how it’s behaving mechanically, and where the mineralisation is. That data feeds resource estimation, drill program planning, environmental assessment, and regulatory reporting — often for years or decades after the original drilling campaign.
The other reason core logging exists is permanence. Physical core is expensive to store and eventually gets sampled, discarded, or lost. A well-kept log is the lasting record of what that core told you.
The types of core logging
Core logging isn’t a single activity. Different disciplines capture different things from the same core, and most exploration programs run several logging passes, often by different specialists.
Lithological logging
Lithological logging is the foundation. It records the rock types present — their mineralogy, texture, grain size, colour, and any primary features like bedding, flow banding, or igneous contacts. On most programs this is the first logging pass, and it defines the depth intervals that structure every other dataset.
A lithology log at its simplest assigns a rock name and a description to each interval. In practice it includes:
- Rock type (e.g. feldspar porphyry, mafic schist, massive sulphide)
- Texture descriptors (coarse-grained, foliated, brecciated, mylonitic)
- Colour in both fresh and weathered states
- Grain size where relevant
- Primary fabric or structure (bedding, foliation, flow banding)
- Contacts — sharp, gradational, faulted, irregular
The intervals you choose matter. A program focused on porphyry copper might log lithology in 2-metre intervals across a uniform intrusive but shift to 10-centimetre intervals through a contact zone or a breccia pipe. The resolution should match what you’re trying to understand.
Geotechnical logging
Geotechnical logging captures the mechanical properties of the rock mass — how strong it is, how broken, how it will behave when you excavate around it. It’s required for mine planning, pit slope design, underground development, and increasingly for resource categorisation under NI 43-101 and JORC.
The core parameters in geotechnical logging:
Rock Quality Designation (RQD). The length of intact core pieces longer than 10 cm, expressed as a percentage of the total core run length. An RQD of 90%+ indicates competent, well-indurated rock. Below 25% suggests heavily fractured or weak material. RQD is the most widely reported geotechnical parameter in resource reports.
Core Recovery. The percentage of core actually recovered relative to the interval drilled. If you drilled 3 metres and recovered 2.5 metres of core, recovery is 83%. Low recovery can mean weak or highly fractured rock — or it can mean drilling conditions (lost core due to flushing, core blockages, or poor drilling practice). Distinguishing between the two matters.
Fracture frequency. The number of natural fractures per metre of core. Combined with RQD, this gives a clearer picture of rock mass quality than either metric alone.
Rock strength. Estimated by point load test, Schmidt hammer rebound, or qualitative classification (very weak to extremely strong on the ISRM scale). Direct measurement is preferred for design, but field estimates are standard in early-stage logging.
Discontinuity characteristics. Fracture orientation (dip and dip direction, measured with a goniometer or core-orientation tool), infill material (clay, calcite, quartz, iron oxide), roughness (smooth, undulating, rough), and surface weathering.
Weathering profile. Classification of weathering state — fresh, slightly weathered, moderately weathered, highly weathered, completely weathered — which affects both strength estimates and geochemical interpretation.
Many programs also record core orientation data (alpha and beta angles relative to a reference line) to reconstruct the true three-dimensional orientation of structural features.
Structural logging
Structural logging focuses specifically on structures in the rock — faults, shear zones, veins, contacts, folds, and foliations — and their spatial orientation. On structurally controlled ore deposits (epithermal veins, lode gold, fault-hosted uranium), structural logging is as important as lithology.
Key measurements:
- Vein logging: vein width, mineralogy, texture (massive, crustiform, colloform, brecciated), continuity, orientation
- Fault and shear zone logging: thickness, orientation, infill, kinematics indicators (slickensides, mineral lineations, drag folds)
- Foliation and fabric: foliation type, intensity, orientation
- Contact logging: nature of contacts, their orientation, any associated alteration haloes
Structural logging typically requires a geologist with structural competence and a properly oriented core (either natural orientation from a core-orientation tool, or geometric re-orientation from downhole survey data).
Alteration logging
Alteration logging records the hydrothermal or metamorphic alteration of the host rock — the changes in mineralogy and texture that often accompany and envelope ore deposits. It answers the question: what has the fluid done to this rock?
Common alteration types include:
- Potassic alteration — K-feldspar and biotite replacement, classic in porphyry copper systems
- Phyllic alteration — quartz-sericite-pyrite (QSP), strong acid-generating potential
- Argillic and advanced argillic — kaolinite, alunite, dickite; typically in epithermal and the upper zones of porphyry deposits
- Propylitic — chlorite-epidote-carbonate, the outermost alteration halo in many hydrothermal systems
- Silicification — pervasive quartz flooding, often associated with high-grade mineralisation zones
Alteration is often logged on a vectoring scale — intensity increases toward the fluid source, which is typically the mineralised zone. An alteration log lets you track proximity to the system even in holes that don’t intersect ore.
Mineralisation logging
Mineralisation logging records the ore minerals and their occurrence — abundance, distribution, mode of occurrence (disseminated, stringer, vein-hosted, massive), and any visible textural or grade indicators.
Visual estimates of sulphide percentages, visible gold or copper, oxide-supergene zones, and mineralisation style feed into sampling decisions and early grade estimation. On many programs, mineralisation logging and sampling are done in concert — the geologist logs the interval and decides where to cut a sample channel.
Core logging equipment
What a geologist carries to a core shed depends on the program, but the essentials are consistent:
Measuring tools. A fibreglass tape measure is the constant companion. Intervals are measured from the collar down, and every depth call needs to be consistent across the team. Depth blocks (small plastic markers placed in the core tray to confirm core run breaks) keep measurements honest.
Ruler and dividers. For measuring vein widths, crystal sizes, grain sizes, clast dimensions, and any feature where size matters.
Hand lens (loupe). 10× magnification minimum. Essential for identifying minerals, textures, and alteration assemblages at the scale of individual crystals. Some geologists carry a 20× or 30× for fine-grained rocks.
Dilute hydrochloric acid (10% HCl). For identifying carbonate minerals. Calcite effervesce strongly in cold acid; dolomite only effervesce when powdered or in warm acid; siderite and ankerite react weakly. A small dropper bottle is standard kit.
UV lamp. Some minerals fluoresce under shortwave or longwave UV — scheelite (calcium tungstate) glows bright blue, calcite fluoresces red, some REE minerals have characteristic responses. Invaluable on tungsten and rare-earth programs.
Streak plate and hardness picks. For mineral identification using Mohs hardness and streak colour. Useful in the field when lab analysis isn’t yet available.
Core orientation tools. If structural logging requires true orientations, either a downhole core-orientation tool (mechanical spear or optical device run with each drill run) or core-orientation marks made at the rig before the barrel is retrieved.
Goniometer. For measuring the alpha and beta angles of structural planes on oriented core.
Camera. Every core tray should be photographed before sampling, at consistent lighting and scale. Core photography is increasingly done with purpose-built scanning rigs (KORE Spector, Minalyze) on large programs, but a field camera with a scale bar is the baseline.
Field data capture. Paper field books, printed logging sheets, or a digital device running logging software. The choice has significant downstream consequences.
How core logging is done in practice
Core layout and core tray setup
Core arrives at the logging facility (a core shed, a shipping container fitted out for logging, or a covered table in the field) in plastic core trays, typically 1 metre per row with 3–4 rows per tray. Each tray is labelled with the hole ID, depth from, and depth to. Core runs are separated by depth markers.
Before logging begins, the core is physically laid out in sequence. Core recovery is measured and recorded for each run — actual core length vs. drilling advance. Core that’s been disturbed (flipped runs, missing segments) is identified and documented.
Geologists mark the top of each core run with a line before any manipulation — a reference for re-orienting structural measurements later if needed.
The logging pass
Logging proceeds top-to-bottom through the hole. The geologist works through the trays, calling intervals and dictating or directly entering descriptions. Most programs use a defined coding system — a set of approved values for each logged attribute (rock type codes, alteration codes, mineralisation codes) — to enforce consistency across the team.
The structure of a logging interval:
- Call the depth. Measure from the last depth marker to the contact and record Depth From.
- Identify the contact. Mark the end of the previous interval and the start of the new one.
- Record the attributes. Work through the fields in the logging template — rock type, texture, alteration, mineralisation, veining, structure, colour, weathering, any other project-specific fields.
- Close the interval. Move to the next contact, record Depth To of the previous interval (= Depth From of the next).
An experienced geologist logging lithology and alteration on a porphyry copper program can move through competent core at 20–30 metres per hour. Heavily altered, fractured, or mineralogically complex intervals take longer.
Interval length decisions
Interval length is one of the most consequential choices a geologist makes while logging. Intervals that are too long average out important variations; intervals that are too short create datasets that are difficult to work with in modelling.
Practical rules:
- Log at contacts, not at arbitrary round numbers. An interval ends when the rock changes, not because you’ve hit a metre mark.
- Set a minimum interval for the program — typically 10 or 20 cm — to prevent runaway fragmentation of the dataset.
- Set a maximum interval — typically 2 or 5 metres — to prevent geological variation from being hidden in long, undifferentiated runs.
- Match your logging resolution to your sample interval. If your sample channel is 1 metre, logging at 10 cm for most of the hole creates data at a resolution your assays can’t match anyway.
Data recording
Data goes somewhere: paper, tablet, laptop. The format of the logging template defines what’s captured and in what form.
Paper logging is the historic default. Geologists fill out pre-printed forms in the field, and the data is later entered into a database by a data technician or the geologist themselves. The problems are well-documented: transcription errors, illegible handwriting, data entry backlogs, no validation at the point of entry. A depth overlap discovered three months later in the office cannot be corrected by going back to the core.
Digital logging captures data directly into the database. The logging software enforces validation rules — overlapping intervals are caught in real time, required fields can’t be skipped, dropdown columns prevent code inconsistencies across the team. The data is in the database the moment it’s entered. On most programs, this is now the standard approach.
The transition from paper to digital is one of the most impactful changes an exploration program can make. GeoSpark testimonials document reductions from six-week data verification processes down to five days after switching from paper. The errors that surface months later in resource models — overlapping intervals, mismatched codes, impossible depth sequences — are eliminated at source.
Logging codes and dictionaries
Most programs establish a standardised set of logging codes before drilling begins — a lookup dictionary of approved values for every coded field. Instead of each geologist writing “granite porphyry,” “granodiorite porphyry,” “granitoid porphyry,” and “Gr Porphyry” for the same rock type, the dictionary has one approved value: GRP.
A well-designed dictionary covers:
- Lithology codes (rock types relevant to the deposit and host stratigraphy)
- Alteration codes (the alteration assemblages relevant to the system)
- Mineralisation codes (ore minerals and commodity-bearing phases)
- Structural codes (vein types, fault types, foliation types)
- Weathering codes
- Quality codes for uncertain observations
Dictionary design requires geological input — the codes need to reflect the actual geology of the deposit, not a generic template. Getting this right before drilling starts prevents painful recoding later. Templates can be shared across holes and projects, and a well-structured logging dictionary can be replicated across an entire company’s database.
How core logging feeds resource estimation
The resource estimation workflow starts with logging data:
Wireframing. The resource geologist uses lithological and alteration boundaries to construct three-dimensional wireframe solids — the interpretive shapes that define where ore is and where it isn’t. These wireframes are built from the contacts logged in the drill core. A missed contact, a mis-called depth, or an unrecognised rock type directly affects the shape of the solid and the tonnes it contains.
Block modelling. The block model is populated with estimated grades inside the wireframes. The estimation uses composited assay data, and compositing is based on intervals. If your logging intervals don’t align with your assay sample intervals (because the core was sampled after logging, not at the same contacts), compositing becomes an averaging exercise that loses the geological signal.
Validation. Before a resource estimate can be reported under JORC or NI 43-101, the Qualified Person must confirm that the data has been collected to an appropriate standard, that validation has been applied, and that the database accurately reflects what was observed in the field. Poor logging documentation — inconsistent codes, missing fields, no record of who logged what and when — is one of the most common causes of resource estimate delays and failures in independent audits.
Data density and continuity. Where drill hole spacing is wide, the resource geologist relies on geological continuity interpreted from logging data to extrapolate between holes. A well-logged hole that captures alteration zonation, structural control, and mineralisation style provides far more interpolation power than a minimally described interval sequence.
The link from field observation to financial resource is direct. The resource drives the project economics, the economics drive the investment decision, and the investment decision is ultimately contingent on the quality of data in the core log.
The shift to digital core logging
The geology industry spent most of the twentieth century logging on paper. The transition to digital logging tools has been underway for about two decades but accelerated significantly in the 2010s, and by the mid-2020s, digital-first logging is standard on any well-run program.
The practical drivers:
Validation at entry. Digital logging software can enforce rules that paper cannot — overlapping depth intervals, values outside accepted ranges, missing required fields. Errors are caught in the field, not the office.
A single source of truth. When multiple geologists log the same project in the same database, there’s one version of the data. No spreadsheet reconciliation, no version conflicts when two geologists export data simultaneously, no question of which CSV is current.
Offline capability. Remote sites often have limited or no internet connectivity. Modern logging platforms work fully offline and sync to the cloud automatically when connectivity returns. No internet for two days is no longer a data-loss risk.
Audit trail. Digital logs are timestamped and attributed — you know who logged what and when. This matters for QP sign-off under JORC and NI 43-101.
Downstream efficiency. Data in a properly structured database can be exported directly to 3D modelling software (Leapfrog, Datamine, Micromine) without an intermediate reformatting step in Excel. Configure the export workflow once; run it every time you need a fresh export.
The cost of a paper-to-digital migration is front-loaded — dictionary design, template setup, team training. The cost of not doing it is distributed across every data cleanup exercise, every recoding exercise, every delay between field data collection and model update, and every error that makes it into a resource estimate.
What makes a good core log
After everything else, a core log is useful to the extent that it is complete, consistent, and honest.
Complete means no intervals without descriptions, no required fields left blank, no core runs where the geologist stopped before reaching the bottom. Missing data in a geological database is not neutral — it introduces uncertainty that downstream users can’t quantify.
Consistent means the same rock type gets the same code, the same alteration intensity gets the same descriptor, regardless of which geologist is logging or which day of the week it is. Consistency is what makes it possible to compare intervals across holes and build interpretations at the scale of a deposit.
Honest means recording what you actually see, not what you expect to see. The temptation to call a contact a metre shallower to make the lithology boundaries cleaner, or to upgrade an alteration intensity to support a geological interpretation, is real. These calls compound. A resource that’s built on honest observations, even disappointing ones, is more defensible than one built on optimistic interpretations that don’t survive drilling.
Core logging is the first data collection step in a chain that ends at a resource estimate, a mine plan, and a financial commitment. The quality of the log determines the quality of everything that follows.
Blue Butterfly is geological core logging and data management software for exploration programs. One database. Works offline. Set up by a geologist in an afternoon.