What the data for this category looks like
Declaration materials and file review data for oilfield engineering services comes from formal documents across the full project lifecycle: project approval, construction, and completion acceptance. These documents include drilling operation records, fracturing construction plans, oil test acceptance reports, and similar materials. Updates are generated in batches aligned with project milestones, with no fixed batch cycle. Most documents are multi-page PDFs or scanned files with attached engineering drawings. They contain standardized fields, numerical tables, and engineering drawings. Fields include project numbers, well IDs, operation volumes, acceptance criteria, and similar items. Units are standard engineering measurements such as meters, cubic meters, and hours.
What constraints these characteristics impose on document parsing and chunking
Documents include scanned files and engineering drawings. The parsing link must support image OCR and retain structured layouts to avoid losing drawing annotations and table structures. Fields use specialized units and key project identifiers. Chunking must not split key information across fields, as this breaks business logic. Single file sizes are generally large. The system must support large file uploads and long-duration parsing. Batch-generated documents must be linked to their project batches to avoid mixing content from different project phases during chunking.
Configuration Settings
This configuration is optimized for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Oilfield engineering files often include multiple pages of engineering drawings and scanned documents, so single file sizes are generally large |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Parsing large engineering drawings and multi-page files takes longer, this avoids mid-process timeout interruptions |
customPdfParse | Enable MinerU adaptation mode | Adapts to engineering drawings and table structures in oilfield documents, retains original layout and OCR recognition content |
chunkSize | 1000–1500 characters | Balances business field integrity and retrieval granularity, avoids splitting key information such as well IDs and operation volumes |
chunkSplitter | By paragraph + fixed character boundary | Adapts to multi-paragraph operation descriptions and table supplementary notes |
chunkSettingMode | Manual configuration | Adjust chunking rules for the special structure of oilfield documents, adapts to the fixed format of declaration materials |
Three Common Misconfigurations
- After uploading engineering files in scanned document format, the parsing result only contains blank placeholders. The cause is that the scanned document adaptation mode in
customPdfParseis not enabled, so text content in image-based documents cannot be recognized. - The parsing interface call returns a timeout error. The cause is that
PARSE_FILE_TIMEOUT_SECONDSis not adjusted to above 900 seconds, and the parsing time of large engineering files exceeds the default threshold. - Passing external image addresses fails to complete parsing. The cause is that public network access permissions for image resources are not configured, or the image parsing protocol supported by FastGPT is not used.
How to Confirm Proper Configuration
- Upload a single PDF file containing engineering drawings and numerical tables, check if the parsing result retains drawing annotations and the original layout of tables.
- Call the parsing interface to upload a large engineering file under 2000 MB, confirm the interface does not return a timeout error.
- Review the chunking results, confirm that key fields such as well IDs and operation volumes are not split into different chunks.
- After configuring
customPdfParse, upload a scanned document file, confirm the parsing result includes complete text content recognized by OCR.
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.