A legacy geoscience archive may contain well-log prints, geological maps, seismic sections, scout tickets, and photographs of core boxes. All can hold useful information, but they do not require the same digitization service. Some need numerical curve recovery, some need spatial feature capture, and others need structured transcription or carefully registered imagery. Choosing the right workflow starts with the information you want to reuse.<\/p>\n\n\n\n
The distinction matters when preparing a specification or comparing quotations. A scanned document can be easier to find and view without becoming usable data for analysis. A successful digitization project defines what will be extracted, how the result will be organized, and how it will be checked against the source. This guide compares the five services and explains how to scope a mixed archive.<\/p>\n\n\n\n
Ask what a user must be able to do after delivery. Do they need to plot a historical curve, query geological boundaries, load a seismic line, search well histories, or review core alongside depth-based information? Each answer points toward a different output and a different acceptance test. The file extension alone does not define whether the result will meet that need.<\/p>\n\n\n\n
Also distinguish source recovery from new interpretation. Capturing a mapped contact is different from reinterpreting geology; transcribing a formation name is different from confirming that identification. Agree whether the assignment is faithful reproduction, normalization into an existing data model, or a separate interpretive exercise. This keeps responsibilities clear and helps preserve the limits of historical evidence.<\/p>\n\n\n\n
Geophysical well-log digitization converts plotted curves into numerical values associated with depth. GAEA\u2019s well-log digitization service<\/a> describes delivery in LAS 3.0, with scoped curves and available header information. Curve names, units, sampling intervals, and missing-value conventions are important parts of the agreed output.<\/p>\n\n\n\n Source review needs the complete log context: depth labels, track boundaries, curve scales, and any changes between pages. A curve position means little without its calibration. Overlapping traces, faint printing, scale reversals, and gaps require attention during capture and review. Plotting the delivered values against the source helps identify discrepancies that a file-format check alone would miss.<\/p>\n\n\n\n For example, if your aim is to compare a specific curve across several wells, request that curve explicitly and agree how different labels or units will be handled. Keep original labels available when standardizing names. A useful pilot should include a difficult page as well as a clear one, so the review tests the actual archive conditions.<\/p>\n\n\n\n This service should not be confused with extracting every field from a descriptive geotechnical borehole log. If you need lithological intervals, samples, construction details, or handwritten notes, identify those requirements separately rather than assuming that a curve-digitization scope includes them.<\/p>\n\n\n\n A georeferenced map image provides a spatial backdrop; vector digitization creates features that can be queried and edited. GAEA\u2019s map digitization service<\/a> covers point, line, and polygon layers with agreed attributes and reference information. The scope should identify which features matter, such as geological units, faults, observation locations, or boundaries.<\/p>\n\n\n\n Supply the complete legend, coordinate information, and reliable reference material. A geological contact and a road may look similar in a poor scan but belong in different layers. Historical map scale, distortion, and uncertain control limit the output; digitization does not turn the source into a new survey. Review should address both feature placement and the information assigned to each feature.<\/p>\n\n\n\n A practical pilot might ask a reviewer to select a geological unit, retrieve its source code, and follow a contact across adjoining sheets. This tests whether the output is usable as a dataset, beyond simply looking like the original map. Decide how uncertain boundaries and conflicting sheet edges will be recorded before full production.<\/p>\n\n\n\n Request a format that your GIS or CAD workflow can actually load. Include layer names and attribute definitions in the handover so future users can distinguish the captured evidence from subsequent edits or interpretations.<\/p>\n\n\n\n Seismic-section digitization addresses printed or scanned seismic displays. GAEA\u2019s seismic digitization service<\/a> describes trace recovery to SEG-Y and the option to incorporate navigation information. Source presentation, readable scales, line identity, and available navigation should be reviewed together when defining the work.<\/p>\n\n\n\n Agree the vertical reference and sampling requirements, trace identification, and what the receiving software expects. A file may load successfully while still being incorrectly positioned or labeled. Review a representative section in the destination application and compare recognizable events, orientation, and scale with the source. Include checks of navigation where it forms part of the delivery.<\/p>\n\n\n\n An image-derived section represents what can be recovered from a printed display. It should not automatically be treated as equivalent to the original acquisition or processing dataset. If your intended analysis depends on information not preserved in that display, discuss that limitation before commissioning the work.<\/p>\n\n\n\n For a pilot, choose a line that includes the source conditions likely to complicate production, such as annotations or changes in image quality. Ask the reviewer to document where the recovered section is adequate for the intended interpretation and where further source information is needed.<\/p>\n\n\n\n Scout tickets and related well-history forms combine identifiers, dates, depths, construction details, geological observations, and results. Their layouts and terminology vary. GAEA\u2019s scout-ticket digitization service<\/a> organizes captured information into an agreed schema while keeping records linked to their source documents.<\/p>\n\n\n\n This is primarily a transcription and data-structure problem. One well can have several completions, tests, or formation entries, so forcing everything into one spreadsheet row can obscure relationships. Agree the fields, repeating records, identifiers, and normalization rules before production. Unreadable or conflicting entries need an explicit review status rather than an unsupported guess.<\/p>\n\n\n\n A useful acceptance exercise begins with a well identifier, follows it to several related records, and opens the exact source page for a selected value. This tests both retrieval and traceability. Include a ticket with revisions or handwriting in the pilot, because a clean typed form may not reveal the archive\u2019s real complexity.<\/p>\n\n\n\n Decide which fields must be reviewed most closely for the intended use. A misplaced decimal and a wrong well identifier have different consequences, but either can make a record misleading. Clear field definitions help reviewers identify those differences consistently.<\/p>\n\n\n\n Core-photo splicing assembles imagery from individual boxes or rows into a more continuous depth-related view. GAEA\u2019s core-photo splicing service<\/a> describes separating core imagery from box photographs and producing a depth-corrected image for compatible software workflows. The project needs reliable box identity, sequence, and depth information.<\/p>\n\n\n\n Agree cropping, orientation, scale, and image treatment before processing. The visual result should help users understand the recorded core sequence without hiding missing intervals or uncertainty. Retaining the original photographs provides essential context for labels, breaks, and decisions made during preparation.<\/p>\n\n\n\n For example, ask a reviewer to trace a selected interval from the assembled image back to the original box photograph. They should be able to explain the sequence and any gaps. A visually smooth join is not sufficient evidence that the depth registration is correct.<\/p>\n\n\n\n Image preparation also has a different purpose from geological logging. A spliced image can support review, but it does not itself establish lithology, recovery, or other interpreted properties. If those outputs are required, specify them as distinct tasks with their own evidence and review requirements.<\/p>\n\n\n\n Start with a manifest rather than a single folder count. Group materials by source type, project, condition, and intended use. Identify where several documents describe the same well or investigation, but do not merge them merely because their names resemble one another. Record the identity rules that will connect the outputs across services.<\/p>\n\n\n\n Consider a hypothetical archive containing curve logs, scout tickets, and core photographs for the same wells. A shared well register could link all three outputs, while each service retains its own source references and quality checks. The pilot should demonstrate that a user can move between the datasets without losing track of which well, interval, or document they are reviewing.<\/p>\n\n\n\n Prioritize according to the work the archive must support. A small group of records needed for an active interpretation may deserve attention before a large, uniform collection intended mainly for preservation. Separate urgent operational needs from broader archive modernization so the first delivery remains manageable and useful.<\/p>\n\n\n\n Provide a representative sample that shows both ordinary and difficult material. Include the approximate volume, required outputs, receiving application, desired schedule, and the person who will review the result. Explain which metadata already exists and which relationships will need to be reconstructed. This gives the provider a basis for defining the work rather than estimating from page count alone.<\/p>\n\n\n\n Compare quotations on equivalent scope. Check whether source preparation, metadata capture, exception reporting, import testing, and corrections after review are included. Agree the delivery sequence and review turnaround. A lower initial price can describe a smaller service, so make the deliverables and acceptance process explicit before comparing totals.<\/p>\n\n\n\n Approve a small pilot before committing a varied archive to full production. Use it to test the data specification, the treatment of ambiguous material, and the receiving workflow. Record expected outcomes in advance, then document differences and decisions. Changes discovered during the pilot should update the production instructions.<\/p>\n\n\n\n At handover, retain the source inventory, delivered files, field or layer definitions, exceptions, and review record together. Verify the result in the application where it will be used. A successful delivery allows a future user to understand what was captured, what remains uncertain, and where the supporting evidence can be found.<\/p>\n\n\n\n To plan your project, review GAEA\u2019s data solutions<\/a> or request a source assessment and quotation<\/a>. Describe the task you want the information to support, and supply representative material through an agreed transfer method. That provides a practical starting point for selecting the right service and defining a useful result.<\/p>\n","protected":false},"excerpt":{"rendered":" Compare GAEA\u2019s geoscience digitization services and identify the source material, deliverables and quality controls required for each project type.<\/p>\n","protected":false},"author":1,"featured_media":91717,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[975],"tags":[49,2041,245,54,217,199],"class_list":["post-92984","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-geoscience-data-digitization","tag-core-photos","tag-geoscience-digitization","tag-map-digitization","tag-scout-tickets","tag-seismic-digitization","tag-well-log-digitization"],"yoast_head":"\n2. Map digitization: turn mapped features into spatial data<\/h2>\n\n\n\n
3. Seismic-section digitization: recover a usable digital section<\/h2>\n\n\n\n
4. Scout-ticket digitization: structure historical well records<\/h2>\n\n\n\n
5. Core-photo splicing: organize imagery around depth<\/h2>\n\n\n\n
Compare the service by the question it must answer<\/h2>\n\n\n\n
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How to scope a mixed geoscience archive<\/h2>\n\n\n\n
What to include in a quotation request<\/h2>\n\n\n\n
Accept the result through a pilot and documented review<\/h2>\n\n\n\n