What this category of data looks like
Data sources for oilfield services engineering investment research include real-time time-series data from drilling operations, fracturing job reports, well completion engineering documents, reservoir simulation analysis files, industry standard specifications, and supply chain quotation sheets. Update frequencies vary significantly: real-time pressure and flow data from drilling rigs updates every second, well completion reports during project cycles are updated irregularly in batches, and industry standard documents are synced quarterly. Document structures include structured time-series datasets, multi-page PDF reports, and Excel statistical reports. Fields include well ID, operation time, pressure (unit: MPa), flow rate (unit: m³/h), project number, service provider qualification level, and more.
What constraints do these characteristics impose on the database and operations link
The second-level update requirement for real-time time-series data means the database must support high-concurrency writes and low-latency queries. Hot and cold data storage must be separated to reduce operation and maintenance costs. Mixed storage of multiple document types requires the database to support both structured data queries and unstructured vector retrieval, avoiding the complexity of cross-system data synchronization. Individual unstructured documents have large volumes, leading to long parsing and vector conversion times, so sufficient resources must be reserved for long-text tasks. Minor differences exist in field formats across data sources, so unified field mapping rules must be configured to avoid format incompatibility issues during queries.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
VECTOR_STORE_TYPE | TimescaleDB + PGVector | Supports both structured time-series data storage for oilfield services engineering and vector retrieval for unstructured documents |
UPLOAD_FILE_MAX_SIZE | 1500 MB | The text volume of a single large reservoir simulation report from oilfield services engineering after conversion usually does not exceed this threshold |
PARSE_FILE_TIMEOUT_SECONDS | 1200 seconds | Parsing long documents and generating vectors takes a long time, which avoids task interruption due to timeout |
DB_CONNECTION_POOL_SIZE | 30-50 | Adapts to the concurrent access requirements of real-time drilling data and avoids connection exhaustion |
CACHE_TTL | 3600 seconds | Matches the update frequency of industry information and reduces the overhead of repeated vector retrieval |
RECALL_TOP_K | Top 10-15 results | Balances the coverage of research relevance and computing resource consumption |
The parameter values provided on this page are all common recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require on-site analysis, and it is recommended to test against your own samples before finalizing settings.
Three common mistakes
- Symptom: An
AVX instruction set not supportederror occurs when starting the vector database service. Cause: Themongo:5.ximage was used, which does not support the instruction sets of older CPU versions. - Symptom: When the same investment research query is initiated repeatedly, the vector database access logs still show repeated retrieval records. Cause: No reasonable value for
CACHE_TTLwas configured, so the caching mechanism did not take effect. - Symptom: Empty fields are returned when querying associated wellsite business data. Cause: The database table name corresponding to the associated data was not explicitly configured, and no data association index was established.
How to confirm the configuration is complete
- Upload a typical oilfield project report, and verify that the parsed text fields are complete, with no truncation or garbled characters.
- Initiate multiple identical investment research queries, and review the vector database access logs to confirm that repeated requests do not trigger repeated retrieval operations.
- Check the database connection pool monitoring data, and confirm that the number of active connections does not exceed the configured connection pool upper limit.
- Execute structured data queries, and cross-check that the units of returned fields match the source data format.
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.