Ledger Summary and Report Generation for Oilfield Engineering Services: Deployment and Upgrade

Ledger Summary and Report Generation for Oilfield Engineering Services: Deployment and Upgrade

What the data for this category looks like

Oilfield engineering service ledger data originates from original records of on-site construction such as drilling, fracturing, and cementing. It is updated upon completion of a single construction or via daily summary updates. Each ledger document includes fields such as construction team information, equipment operating parameters, construction duration, material consumption details, and safety inspection records. Field units include meters (well depth), cubic meters (fracturing fluid usage), hours (construction duration), tons (steel usage), and others. The character length of each document varies widely, ranging from hundreds to tens of thousands of characters.

Constraints on the deployment and upgrade process

Reference only; verify against the target FastGPT release and deployment documentation.

How to configure the settings

Configuration ItemRecommended ValueRationale
MONGODB_URImongodb://internal IP:27017/fastgpt_oilfieldMost oilfield scenarios are deployed on internal networks. Using internal IP addresses ensures data transmission security, and specifying the business database name isolates oilfield engineering service ledger data
PG_URLpostgresql://username:password@internal IP:5432/oilfield_ledgerStores structured ledger fields and report metadata. Internal network addresses adapt to internal network deployment environments, and a dedicated database name avoids confusion with other business data
REDIS_URLredis://internal IP:6379/0Caches ledger search results and intermediate states of report generation. Internal network deployment reduces cross-network latency, and database index 0 isolates business caches
DB_MAX_LINK20–30 connectionsThe concurrent query volume of oilfield ledger data is moderate. This range avoids connection exhaustion or resource waste
STORAGE_S3_ENDPOINTinternal MinIO address:9000Stores original construction ledger documents with large character volumes. Internal network endpoints adapt to offline deployment requirements and avoid public network transmission costs
FILE_TOKEN_KEYrandomly generated 32-bit stringEncrypts access tokens for ledger files. Random strings improve the security of data access

Three common configuration mistakes

  • Symptom: After initiating a ledger search, reordered results always return false. Cause: The internal network access address of the reranking model was not configured, so FastGPT cannot connect to the tei-deployed reranking service, and the reranking task cannot execute normally.
  • Symptom: After uploading a ledger document, structured fields read as empty. Cause: PG_URL was not correctly configured to point to the dedicated oilfield ledger structured storage database, so standardized field data cannot be read.
  • Symptom: Large character volume ledger documents cannot be stored normally. Cause: The internal network storage endpoint for STORAGE_S3_ENDPOINT was not configured, so the public network storage path cannot adapt to the internal network deployment environment.

How to confirm the configuration is correct

  • Run a database connectivity test to verify that the addresses configured in MONGODB_URI and PG_URL can establish normal connections, with no authentication or network errors.
  • Upload a standard oilfield construction ledger document, trigger the summary task, and confirm that the task status shows completed with no abnormal errors.
  • Configure the internal network access address of the reranking model, initiate a search request containing multiple ledgers, and verify that the reranking results return valid sorted data.
  • Check the storage path to confirm that large character volume original ledger documents have been stored according to the path configured in STORAGE_S3_ENDPOINT.

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.