What the data for this category looks like
The internal office data for oil and gas exploration and development comes primarily from drilling operation logs, seismic exploration reports, trial production data analysis documents, internal operating procedures, and similar sources. Data updates occur on an irregular schedule alongside new well completions and exploration phase progress. The length of individual updated documents varies widely, ranging from short procedures of a few hundred words to long exploration reports totaling hundreds of thousands of words. Documents contain structured fields such as well numbers, operating depth, pressure values, and fluid parameters, and use professional units including meters, megapascals, and cubic meters.
Constraints imposed by these characteristics on knowledge base retrieval and recall
The high share of long documents requires retrieval systems to support context-aware matching after chunking, to avoid breaking the logical connections of professional content. The large number of structured fields requires retrieval to support both semantic matching and exact field matching, to ensure accurate recall of key information such as well numbers and operating parameters. Irregular update schedules require flexible incremental synchronization rules, to support triggering updates based on operation nodes. Mixed multi-format content requires the system to adapt to multiple document parsing formats such as xlsx, pdf, and word, to ensure that table data from drilling logs and text content from reports can be recognized normally.
These configurations are formulated for FastGPT v4.17.0.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Semantic similarity threshold for matching oil and gas exploration professional terms, filters low-relevance non-professional content |
limit | Top 8 entries | Controls the number of results returned per recall, adapts to result density for long document retrieval, avoids result overload |
searchMode | Semantic + keyword hybrid retrieval | Balances semantic matching for professional terms and exact matching for structured fields such as well numbers and parameters |
usingReRank | Enabled | Reranks recall results, corrects semantic drift after long document chunking, improves result relevance |
datasetSearchUsingExtensionQuery | Enabled | Expands retrieval terms based on exploration professional terms, improves recall coverage for niche operating terms |
collectionIds | Configured by document type group | Limits retrieval scope to specified exploration data collections, narrows retrieval scope and reduces latency |
Three frequent configuration errors
- Symptom: Retrieval systems fail to recognize imported xlsx-format drilling Q&A pairs during retrieval. Cause: The question and answer columns of the xlsx file are not configured as specified fields recognized by the system, or the knowledge base parsing rule for xlsx format is not enabled.
- Symptom: Single knowledge base retrieval takes 6 to 7 seconds. Cause: The system does not limit retrieval scope to specified data collections via
collectionIds, leading to overly broad retrieval coverage, or thelimitsetting for recall results is too high. - Symptom: Retrieval systems cannot retrieve target content from the specified file collection. Cause: The
collectionIdsparameter is not configured correctly, or the corresponding dataset ID is not associated during retrieval, leading to an unexpected retrieval scope.
How to verify a successful configuration
- Upload a test drilling log xlsx file, initiate a retrieval that includes professional terms, confirm the file’s content appears in the results.
- Run the same retrieval multiple times, record the time taken per attempt, adjust the
limitandusingReRankconfigurations to align latency with business scenario requirements. - Set
collectionIdsto the specified exploration report collection, initiate a retrieval, confirm results only include documents from this collection. - Attempt to export knowledge base data, confirm the exported file contains the expected structured documents or Q&A pair content.
The values provided here are common starting points, and should be evaluated 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.