Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
Oil and gas exploration and development data mainly comes from drilling operation logs, 3D seismic exploration reports, trial production condition records, reserve assessment documents, and internal approval process documents. Data update frequency shifts based on project phases. Bulk new documents are generated during the prospecting phase, and updates are made per well or monthly during the development phase. A single document typically includes fields such as well ID, operating depth, formation pressure, construction steps, and approval nodes. Units cover professional measurement standards like meters, megapascals, and cubic meters. Some documents include multi-page charts and parameter tables.
What constraints do these characteristics impose on the vector models and indexes link
Professional documents for oil and gas exploration and development contain long paragraphs of construction processes, parameterized operation tables, and structured fields. When splitting text chunks, avoid splitting associated parameters such as well ID and operating depth. This requires precise boundary definition for chunking logic. Data update frequency fluctuates with project phases. Bulk new documents are added during the prospecting phase, and incremental updates are made per well during the development phase. The index must support on-demand incremental synchronization. Documents contain many professional terms and measurement units. The vector model must adapt to embedding effects for industry-specific semantics to avoid loss of professional meaning.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to long paragraphs of construction processes and parameterized operation tables, avoiding splitting associated parameters |
| Overlap Length | 100–150 characters | Retains professional contextual continuity between chunks, preventing construction steps from being truncated |
defaultToken | 2000 token | Adapts to the vector embedding length of long documents, covering the complete semantics of professional paragraphs |
maxToken | 4096 token | Adapts to the total length limit of vector embeddings, avoiding exceeding the model's input upper limit |
| Similarity Threshold | 0.72–0.80 | Matches the semantic similarity range of professional terms for oil and gas exploration and development, filtering low-relevance results |
| Single Search Limit | Top 8 results | Adapts to the number of core nodes in a single exploration document, avoiding redundant results interfering with process guidance |
| Maximum Context | 6000 characters | Matches the multi-step associated retrieval requirements of business handling processes, ensuring coherent guidance logic |
Three common configuration mistakes
- The interface displays the prompt "This token does not have permission to use the model", and logs show embedding model call failure. This occurs when the exclusive
defaultTokenfor the corresponding model is not configured, or an unauthorized third-party token is used. - After adding an embedding channel, a prompt of no available channels appears during retrieval. This happens when the call address and port of the embedding model are not configured to be accessible, or the channel name does not match the configuration in FastGPT.
- Retrieval results lack associated parameters such as operating depth and formation pressure. This is caused by setting the chunk length too small, which breaks the connection between professional parameters and their corresponding context.
How to confirm the configuration is correct
- Upload a single-well drilling log document, run a process guidance test, and verify that retrieval results include the corresponding well ID and operation steps.
- View vector index synchronization logs to confirm that the indexing task for new documents has executed successfully.
- Check embedding model call logs to confirm there are no token permission errors or channel unavailable prompts.
- Adjust the chunk length parameter, compare the contextual completeness of retrieval results, and confirm that it meets business requirements.
The values provided here 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.