What the data for this category looks like
Data sources for oilfield services engineering intelligent due diligence reports include on-site operation logs, third-party exploration and testing reports, equipment maintenance archives, and project bidding-related materials. Update rhythm aligns with project progress. Updates occur per operation node or weekly during a single project cycle. Documents mostly consist of structured tables paired with long text passages. They include fields such as well location coordinates, operating pressure, consumable model, and compliance inspection number. Units involve engineering-specific units like megapascals, cubic meters per minute, and hours. A single report often includes multiple attachments.
What constraints these characteristics impose on deployment and upgrade
The multi-source heterogeneous, long-document, high-frequency update, and specialized field features of oilfield services engineering due diligence data create multiple constraints for deployment and upgrade. Multi-source data such as on-site operation logs and testing reports have inconsistent formats. This requires presetting parsing rules for engineering documents during deployment, to adapt to recognition of specialized fields like well location coordinates and operating pressure. Single reports have large length and file size. This requires adjusting parameter thresholds for file upload and parsing, to avoid timeouts or truncation. High-frequency synchronized operation data requires configuring incremental update mechanisms, to reduce resource consumption from full synchronization. Specialized engineering units require presetting unit matching rules, to prevent recognition deviations from general parsing modules.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Oilfield services engineering due diligence reports often include multiple construction logs and testing report attachments, resulting in large individual file sizes |
PARSE_FILE_TIMEOUT_SECONDS | 1200 seconds | Specialized field recognition and format parsing for long documents require longer processing time, to avoid mid-process timeout interruptions |
CHUNK_SIZE | 1000–1500 characters | Context of specialized parameters such as operating pressure and well location coordinates must be fully retained, to avoid truncation of critical information during chunking |
Similarity threshold | 0.75–0.85 | Specialized due diligence data has high relevance requirements, to filter low-relevance non-engineering content |
Recall count | Top 8–12 results | Balances information completeness and retrieval efficiency. Too many retrieved results introduce irrelevant content, too few fail to cover key operating parameters |
Incremental Sync Trigger Mode | Triggered by file modification time | Oilfield services engineering data is updated in real time with operation nodes. Syncing by modification time accurately obtains incremental content, reducing resource usage from full synchronization |
The parameter values provided on this page are common recommendations for initial configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common errors
- Phenomenon: A code execution node in the workflow returns
500 Internal Server Error, and logs showmodule not found. Cause: The locally deployed FastGPT container does not mount the directory of the corresponding dependency package, or the JS code references a third-party library that is not installed. - Phenomenon: Due diligence reports uploaded via local file paths cannot automatically synchronize updates. The vector database only updates after manual re-upload. Cause: The
Incremental Sync Trigger Moderule is not configured to trigger by file modification time, and only static one-time upload synchronization logic is used. - Phenomenon: Engineering units such as MPa in imported due diligence reports are recognized as plain text, and cannot be accurately matched by vector retrieval. Cause: Specialized unit field mapping rules are not preset, and the default configuration of the general parsing module is used.
How to confirm the configuration is correct
- Upload a typical oilfield services engineering due diligence report, and check that the upload process completes normally, with no timeout or file size limit error messages.
- Trigger an incremental sync operation, and check the sync logs to confirm that only updated files are processed, and no full re-import of all historical reports is performed.
- Initiate a retrieval request for specialized engineering parameters, and check that the relevance of retrieved results meets expectations, and the quantity conforms to the preset retrieval rules.
- Configure a code execution node in the workflow and run test code, confirm that the node executes without errors and operates normally.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.