What this category of data looks like
Data for oil and gas exploration and development declaration materials and case review mainly comes from drilling core analysis reports, seismic exploration data documents, project declaration approval case files, compliance review materials, and similar sources. Data updates trigger alongside exploration project phases. A single update includes full data for a single well or block. Documents mix structured tables and unstructured text, with fields including project number, exploration block, well ID, submission time, approval status, and more. Units include professional parameters such as square kilometers, meters, and percentage. The length of individual documents varies widely, ranging from hundreds of characters to tens of thousands of characters.
What constraints do these characteristics impose on the vector models and indexes component
Large variation in document length and long individual content require vector indexing chunking strategies adapted for long text splitting, to avoid semantic information breaks. Mixed structured and unstructured data require indexes to support unified encoding and retrieval of multiple data types. Dense professional terminology and industry-specific semantic associations require vector model semantic encoding adapted to the professional context of oil and gas exploration. Data updates trigger in phases with project stages, requiring incremental update logic for indexes to match the non-real-time synchronization rhythm, and avoiding high-frequency full reconstruction.
How to set the configuration
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the conventional length of professional paragraphs in oil and gas exploration documents, avoids single chunk content exceeding the maxToken limit |
| Overlap Length | 100–150 characters | Retains the association between professional terms and context, prevents core exploration parameters from being split across different chunks |
| Similarity Threshold | 0.72–0.85, calibrated via actual testing | Matches the semantic similarity range of professional terms in the oil and gas field, filters invalid low-match results |
| Single Search Limit | Top 8 entries | Balances retrieval accuracy and efficiency, adapts to the retrieval needs of cross-document comparison in case review |
defaultToken | 4096 | Adapts to the input length limit of most open-source vector models, compatible with the token count of a single chunk after conventional chunking |
maxToken | 8192 | Matches the default context window limit of FastGPT v4.17.0, accommodates combined retrieval content from multiple case files |
Three common errors
- A 404 error is prompted when adding a local vector model through the interface. The cause is that the local call port of the model is not configured correctly, or the model container and FastGPT container are not connected to the same network.
- The vector model service cannot be started in a GPU-free environment. The cause is that a lightweight vector model adapted for CPUs is not selected, or GPU dependencies are not disabled in the startup parameters.
- The number of retrieval results does not meet expectations after index construction is completed. The cause is that the chunk length is set too large, causing some long documents to not be fully split, or the similarity threshold is set too high, filtering valid matching content.
How to confirm the configuration is complete
- Navigate to the vector model management page in FastGPT, confirm that the status of the added model is displayed as "Ready".
- Upload a typical oil and gas exploration declaration document, perform a chunking test, confirm that the length of the fragmented chunks conforms to the preset chunk length range.
- Submit a test query containing professional exploration terms, check that the number of retrieval results and similarity distribution conform to the configured threshold and limit requirements.
- Submit a new case file, perform an incremental index update, confirm that the new content can be retrieved normally.
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.