E3 ยท Publication Volume 25

Survey Validation

ordering, ranges, intervals, magnetic interference and outliers

Learning objectives

  • Explain the decision and evidence boundary for ordering, ranges, intervals, magnetic interference and outliers.
  • Design and implement the relevant drillhole data or algorithm contract without hidden conventions.
  • Separate hard release gates from diagnostics, interpretation and authorised review.
  • Produce a rule-based survey validation report with explainable findings from synthetic evidence.

The lesson is complete only when the learner can defend the data model, algorithm, tests and release decision. An attractive trajectory or clean interval table without source evidence and executable invariants remains unverified.

This is a general, institution-neutral tutorial with no relationship to any company or individual. All borehole identifiers, coordinates, depths, directions, intervals, values and review events in the lesson are synthetic and must not be used for an operational decision.

Decision context

Validation decides whether a station series is structurally valid, scientifically interpretable and eligible for a stated trajectory use. Structural failures include missing identities, non-finite values and unresolved depth conflicts. Range and continuity checks expose implausible or unusual observations but do not by themselves prove which value is wrong. Tool, correction and reference metadata determine whether a directional observation is comparable with its neighbours.

Write the intended use, consequence of error, required evidence and release authority before selecting a transformation. The same source can be suitable for exploratory display and unsuitable for a released derivative. Fitness is evaluated against a versioned contract and use, not attached permanently to a file.

Core concept

Apply validation in layers: schema and identity, units and conventions, measured-depth sequence, angular range, duplicate resolution, station spacing, dogleg behaviour, method-specific interference indicators, collar tie and trajectory-level geometry. Each rule has an identifier, version, severity, rationale, evaluated fields and remediation path. Hard failures block the affected trajectory version; diagnostic findings require contextual review.

Keep received observations, accepted evidence views and derived results as distinct objects. This separation allows corrected evidence or a changed method to generate a new result without rewriting history. Every derived coordinate or interval therefore answers both a scientific question and a provenance question.

Algorithm and data model

Produce findings rather than mutating input. A finding identifies borehole, survey series, station or course, observed values, expected condition, evidence links and status. Corrections create new observations or explicit derivations. Outlier detection may compare angular separation, dogleg severity, spacing and local trends, but thresholds are stratified by acquisition method and intended use. A physically possible turn can still be suspicious; a statistically unusual value can still be valid.

Define the transformation as a pure, testable operation wherever practical. Parsing, semantic validation, evidence selection, numeric calculation and release evaluation are separate stages. Each stage emits structured output and does not depend on interface state, filename order or an undocumented default.

Constraints and invariants

| Invariant | Executable or review test | | --- | --- | | Validation never changes received observations in place. | Reject or quarantine any record that violates this condition and record the exact affected identity. | | Every threshold includes unit, scope and severity. | Evaluate this condition before producing a derived trajectory or interval result. | | Circular quantities use circular comparisons. | Preserve received evidence and create a new version for every correction. | | Diagnostic outliers require evidence-based disposition. | Include the rule identifier, observed value and resolution state in audit output. |

An invariant must survive import, conversion, processing, export and rerun. A failed hard invariant produces no apparently valid substitute. Diagnostic checks remain visible with their threshold, scope and evidence, and require a reviewed rule before they can trigger correction.

Quantitative reasoning

Report \Delta MD_i=MD_i-MD_{i-1}, angular separation, dogleg severity and robust local deviation. A useful diagnostic is median absolute deviation: MAD=\mathrm{median}(|x_i-\mathrm{median}(x)|), reported with the local window and minimum sample count. Never apply a universal dogleg threshold without its normalisation length and use context. Zero spacing with different directions is a conflict; large spacing is a coverage warning, not a fabricated intermediate station.

Every reported metric includes units, numerator and denominator where applicable, exclusions, comparison policy and evaluation version. Aggregate values are stratified when pooling could hide a local failure. A quantitative diagnostic supports a decision but cannot overrule missing identity, invalid geometry, unresolved conflict or broken lineage.

Evidence and uncertainty

Keep observation uncertainty, interpolation uncertainty, numeric approximation and metadata uncertainty separate. A smooth trajectory can be numerically precise while still poorly constrained between widely spaced stations. An exact interval overlay can still be unfit when a source depth datum is unknown. The assessed result states which uncertainty belongs to the phenomenon, the measurement, the algorithm and the interpretation.

Build an evidence packet containing immutable received records, semantic declarations, validation findings, algorithm inputs and outputs, test results, reviewer decisions and fingerprints. Contradictory evidence remains available. When a required dependency cannot be resolved, return an explicit unknown, conflict or blocked status rather than choosing the most convenient value.

Interfaces and storage

Interfaces transmit identities, units, coordinate and depth references, conventions, value states, versions and lineage beside numeric values. A trajectory exchange includes collar and datum context, accepted station identities, algorithm identity, numerical policy and output coordinates. An interval exchange includes support type, boundary convention and source links. Structured errors identify the record, field, observed value, expected condition and rule.

Store authoritative received evidence separately from reproducible derivatives and disposable views. Indexes, caches and visualisations may improve access but cannot become the only copy of angle conventions, accepted-station decisions or interval lineage. Export round trips verify that identifiers, precision, ordering and missing states survive encoding changes.

Governance and review

Assign responsibilities to roles rather than named organisations or people: evidence custodian, rule author, implementation maintainer, independent validator and release reviewer. A role may propose a correction but cannot erase source evidence. Rule and algorithm changes are reviewed, versioned and evaluated against fixed regression fixtures before they affect a release.

Exceptions are explicit decisions with scope, rationale, evidence, approving role, affected versions and review trigger. They never rewrite a failed rule and never propagate automatically. The host website has no ownership or scientific-authority role in this workflow; it only delivers the tutorial.

Integration checkpoint

a rule-based survey validation report with explainable findings
a rule-based survey validation report with explainable findings

Read the figure as a reasoning map from preserved evidence through explicit conventions, deterministic calculation, validation and release. Each arrow represents a declared relationship or transformation. Integrate a rule-based survey validation report with explainable findings into the evolving synthetic drillhole package, rerun all earlier fixtures and record any changed assumption.

Synthetic worked example

Synthetic series SYN-S005 contains an azimuth wrap, one exact duplicate, one conflicting duplicate, a wide station gap and a local direction jump. Circular comparison clears the wrap. The exact duplicate is linked without affecting the accepted view. The conflict blocks the definitive trajectory. The wide gap remains a warning, while the direction jump is reviewed against method metadata instead of being automatically smoothed away.

  1. Preserve the received records and state the intended decision without correction.
  2. Resolve identities, units, conventions and evidence eligibility; mark every unresolved item.
  3. Run the versioned algorithm and tests while retaining intermediate diagnostics.
  4. Issue accept, reject or quarantine and show how an independent reviewer can reproduce it.

Practice task

Implement the chapter artefact against a synthetic fixture containing one normal case, one boundary case, one invalid case and one unresolved-evidence case. Preserve the received fixture. Produce canonical input, validation findings, derivative output, processing manifest and a short release decision.

Acceptance criteria:

  • Every input identity, unit and convention required by the rule is explicit.
  • The implementation is deterministic under stable ordering and the declared numerical policy.
  • No correction overwrites received evidence or turns unknown into a guessed value.
  • All hard failures block the affected derivative and remain machine-readable.
  • A second implementation or reviewer can reproduce the result from the package alone.

Submit a rule-based survey validation report with explainable findings, the golden and adversarial fixtures, exact findings and a limitations note. A screenshot is not sufficient evidence because it does not identify the input version, algorithm or rule configuration.

Common failure modes

  • Sorting hides duplicate-depth conflicts.
  • A global threshold ignores method and spacing.
  • A suspicious station is silently deleted.
  • A missing correction flag is assumed false.

These failures share a pattern: an implicit convenience is substituted for evidence. Diagnose the earliest boundary where the assumption entered, restore the source statement, make the convention or rule explicit, rerun every dependent derivative and supersede rather than overwrite the affected release.

Review questions

  1. Which survey failures are hard structural gates?
  2. Why is an outlier not automatically an error?
  3. How should a wide station gap be reported?
  4. What evidence is needed to resolve a conflicting duplicate?

For every answer, identify the governing invariant, the evidence needed to evaluate it, the numerical or semantic policy involved and the correct behaviour when the condition fails.

Sources and further reading