What the data for this category looks like
Oil and gas exploration and development data mainly comes from real-time drilling logs collected by on-site exploration equipment, seismic exploration waveform data, geological modeling reports, and monthly development performance reports. The update rhythm varies significantly. On-site operation data is generated in real time alongside construction progress. Monthly reports are updated on a fixed natural month basis. Documents are divided into two categories: structured tables and unstructured text. Structured fields include well ID, measured depth, formation pressure, permeability, and more. Common units are meters, megapascals, millidarcy, and others. Unstructured documents include on-site work logs and technical disclosure documents, with a wide range of lengths.
What constraints these characteristics impose on deployment and upgrade
Real-time collected on-site operation data requires low-latency vector retrieval and storage links during deployment. Delayed data synchronization will affect the response speed of office tools. Mixed data types require compatibility with structured field indexing and unstructured text chunking rules during upgrades. This prevents a decline in retrieval accuracy. Data with different update rhythms need flexible configuration for incremental synchronization and full backup. The upgrade process must ensure data backup integrity. This prevents loss of historical operation data during cross-version migration. The classified nature of oil and gas exploration data requires pre-configured compliant storage permission rules during deployment. Upgrade operations must avoid peak operation hours. This prevents interference with on-site operations and office workflows.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | Configure as a local cluster connection string, set read-write separation weights | Oil and gas exploration data has large storage volume and high read-write concurrency; local clusters guarantee storage performance |
REDIS_URL | Configure as a cluster address with a single instance memory of no less than 8192 MB | Real-time operation data and user sessions require caching; large memory reduces cache elimination probability |
DB_MAX_LINK | Set to 200–300 | Matches the concurrent request volume of on-site data collection, avoids connection pool exhaustion |
STORAGE_S3_ENDPOINT | Configure as a compliant internal object storage service address | Adapts to classified storage requirements for oil and gas data, avoids public cloud storage use |
FE_DOMAIN | Set as the secondary domain name bound to the internal office system | Ensures employees access FastGPT services only through the internal network |
ROOT_KEY | Generate a random 32-bit string and store it encrypted | Used for administrator permission verification, ensures access security of the deployment backend |
Three Common Mistakes
- Phenomenon: After upgrade, search results for historical exploration data are empty, or database connection timeout errors occur. Cause: Full data backup was not performed in advance, or the read-write permission configuration of the original
MONGODB_URIwas not retained during upgrade, resulting in interrupted data links. - Phenomenon: External models cannot be called after configuration, and the interface returns a 400 status code. Cause: Internal network external access permissions were not enabled in the deployment configuration. The internal network in oil and gas exploration scenarios usually restricts external connections, causing model requests to fail to send normally.
- Phenomenon: When processing multiple well log batches in bulk, only a single task runs, and parallel execution cannot be triggered. Cause: The
DB_MAX_LINKconnection count configuration was not adjusted, leading to concurrent tasks exhausting the database connection pool and unable to start parallel processes.
How to Confirm Proper Configuration
- Log in to the FastGPT management backend, check the connection status of the storage cluster corresponding to
MONGODB_URI, and confirm that read-write delay meets internal office response requirements. - Upload a typical drilling log document, verify that the vector retrieval function can normally return matching results, and check whether the cache hit rate of
REDIS_URLmeets expectations. - Perform a full data backup operation, confirm that the backup file can be normally stored in the storage service corresponding to the configured
STORAGE_S3_ENDPOINT. - Initiate a batch task test, confirm that tasks can be started and executed according to the configured concurrency count, with no connection pool exhaustion 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.