What the data for this category looks like
Data for internal office and employee services in oil and gas exploration and development mainly comes from original record documents collected via field exploration, PDF drilling operation logs, reservoir analysis reports, internal approval process documents, and employee training materials. Data updates follow work node milestones. Drilling operation logs for a single well are updated daily, while regional exploration reports are compiled and released quarterly.
Document structures vary widely. They include pure long text paragraphs, professional reports with embedded charts, structured parameter tables, and a small number of scanned handwritten field records. Professional fields contained in the documents include well ID, drilling depth, formation pressure, and permeability. Corresponding units are none, meters, megapascals, and millidarcys respectively.
What constraints do these characteristics impose on the document parsing and chunking process?
The document characteristics of oil and gas exploration and development impose multiple constraints on the parsing and chunking link. First, a single professional report may be dozens of pages long. General chunking rules may interrupt cross-page professional term associations, so strict retention of paragraph and title hierarchy is required. Second, mixed-structure documents include tables and charts. General parsing tools may lose typesetting structure, failing to fully restore professional information from drilling parameter tables and logging curve reports. Third, scanned field operation records require OCR support; otherwise valid text content cannot be extracted. Fourth, internal office process documents and training materials use custom formats, requiring adaptation to non-standard content typesetting.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 1200–1500 characters | Adapt to the paragraph length of single-well analysis reports, avoid splitting content linked by professional terms |
chunkSplitter | Split by paragraph + title | Retain document hierarchy, adapt to the title and paragraph logic of oil and gas industry documents |
customPdfParse | Enabled | Support parsing exploration PDF documents with embedded charts and tables, restore original typesetting |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Address parsing time for single long drilling logs, avoid timeout failures |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Adapt to large-capacity three-dimensional exploration data report PDFs |
chunkSettingMode | Manual mode | Adjust chunking rules for professional documents, adapt to custom content for internal office use |
Three Common Mistakes
- Phenomenon: A connection failure error occurs when calling
customPdfParsein a Docker environment, and connection cannot be established even when calling via local 127.0.0.1. Cause: The parsing service port inside the Docker container is not properly mapped, or the container network policy restricts local port access. - Phenomenon: Parsing tasks fail directly when uploading a single exploration report larger than 2000 MB. Cause: The
UPLOAD_FILE_MAX_SIZEparameter is not adjusted to the appropriate capacity threshold, exceeding the default limit. - Phenomenon: Parsed chunk results lose table content, or chunks split cross-page professional paragraphs. Cause:
customPdfParseis not enabled, and the default general PDF parsing logic is used, which cannot recognize the complex typesetting structure of oil and gas industry documents.
How to Confirm the Configuration Is Successful
- Upload a single-well drilling log PDF, and check if the parsed text retains the original row and column structure of tables.
- View task logs to confirm that parsing time does not exceed the threshold set by
PARSE_FILE_TIMEOUT_SECONDS. - Adjust the
chunkSizeparameter, then test whether the chunked result does not split continuous professional term paragraphs. - Verify the Docker port mapping configuration for FastGPT v4.17.0, try calling the parsing service via the container's internal address, and confirm there are no connection errors.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.