Choosing Between Cloud, Edge, and Hybrid Architectures for Drilling Analytics
Choose cloud, edge, or hybrid deployment from software responsibility, latency, connectivity, data scope, support burden, and failure consequence.
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Drilling engineering, explained from the data up.
Practical articles about drilling data architecture, statistics, engineering models, real-time systems, directional work, and applied AI.
Evaluating the Reliability of an AI Drilling Assistant
Evaluate AI drilling assistants claim by claim for entity, source, calculation, context, inference, uncertainty, abstention, and recommendation safety.
Read article →Engineering Context in Drilling RAG: Why Semantic Similarity Is Not Enough
Engineering retrieval must resolve authorization, wellbore, depth or time, BHA, state, source authority, and freshness before semantic ranking and synthesis.
Read article →Why Deterministic Engineering Calculations and LLM Reasoning Should Coexist in Drilling
Validated code should perform engineering calculations; an LLM should resolve intent, route tools, compare evidence, explain assumptions, and preserve uncertainty.
Read article →Why Drilling Analytics Need Memory: The Role of Moving Windows and Historical State
Developed drilling states require memory. Choose windows, trends, persistence, event aging, coordinates, and context resets from the physical process and decision timescale.
Read article →When “Unable to Determine” Is the Correct Output in Drilling Analytics
When evidence cannot separate plausible causes, unable to determine is the correct result. Explain the missing, conflicting, or out-of-domain evidence.
Read article →Probabilistic Reasoning for Drilling Dysfunction Detection
Drilling dysfunctions have overlapping surface signatures. Probabilistic reasoning preserves competing hypotheses, missing evidence, diagnostic separation, and scope.
Read article →When Should You Pull a Drilling Bit? A Decision Under Uncertainty
A bit-pull recommendation compares two uncertain paths to TD. Combine persistent degradation evidence with trip time, remaining footage, replacement performance, and risk.
Read article →Interpreting PDC Bit Wear from Surface Drilling Data
Surface data can indicate changing PDC cutting efficiency, not measure cutter damage directly. Use bit RPM, DOC, WOB, local baselines, context, and dull evidence.
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