Data Integrity as the Prerequisite for Validation (DOT → Runtime Simulation)

Simulation accuracy is often discussed in terms of physics models, resolution, or solver performance. Far less attention is given to a more fundamental constraint: simulations are only as credible as the data used to configure them. In high-consequence operations, even small data inconsistencies — misapplied assumptions, spreadsheet drift, or manual interpretation errors — can invalidate results long before physics is ever solved.

This case documents how Endeavor addressed that upstream failure mode by structurally linking DOT with runtime simulation, creating a validation pipeline where clean, decision-grade data feeds directly into a continuously solved physical system.

This case involved organizations responsible for complex drilling and well operations where simulation results were used to inform training, planning, and operational readiness. These teams had access to advanced simulators and engineering tools, yet struggled with a recurring problem: simulation outcomes were often questioned not because the physics was wrong, but because the inputs were uncertain.

Operational data was assembled manually from spreadsheets, emails, and paper artifacts. Assumptions were embedded implicitly rather than declared explicitly. Configuration effort was time-consuming and error-prone, particularly for deviated wells, tapered strings, and non-standard operations.

As a result, simulations were frequently treated as illustrative rather than authoritative.

DOT was deployed as the authoritative system for operational data creation and validation. Well configuration, equipment details, operating parameters, and procedural constraints were structured explicitly within DOT rather than inferred or reconstructed.

Once defined, this data flowed directly into Endeavor’s runtime simulation environment without manual translation. The simulation instantiated automatically from verified inputs, eliminating the need for duplicate data entry, spreadsheet import, or interpretation layers.

Because DOT enforced calculation integrity and standardized outputs, the simulation always started from a known, validated baseline.

Most simulation workflows treat data preparation as a preliminary step — something to be completed before “real” simulation begins. In practice, this step introduces significant uncertainty. Manual calculations, spreadsheet customization, and implicit assumptions accumulate error before physics is ever evaluated.

Endeavor inverted this relationship.

By embedding engineering logic upstream and enforcing data integrity at the decision layer, DOT removed entire categories of configuration error. The runtime simulation did not need to compensate for ambiguous inputs or reconcile conflicting interpretations. It could simply solve physics.

This structural linkage between data integrity and runtime execution is absent in legacy platforms, where simulation credibility depends heavily on user discipline rather than system design.

Teams gained confidence that simulation outcomes reflected physical behavior rather than configuration artifacts. Disputes over “whether the model was set up correctly” diminished, allowing teams to focus on interpreting results rather than questioning them.

This shifted simulation from an advisory role to a validation role within the organization.

Simulation setup time decreased materially. Engineers and instructors no longer rebuilt scenarios manually or reconciled spreadsheet discrepancies. Iteration accelerated because trusted inputs were always available.

Across deployments, scenario configuration and validation effort was reduced by 30–50%, enabling more frequent and more meaningful use of simulation.

By eliminating setup-driven error, organizations reduced the risk of making decisions based on flawed assumptions. Avoiding even a single misconfigured scenario — which can lead to incorrect planning or training conclusions — represents hundreds of thousands of dollars in avoided downstream cost.

More importantly, simulation outputs became defensible in reviews, audits, and cross-disciplinary decision forums.

Credible simulation does not begin with physics. It begins with data integrity. This case established that DOT is not an accessory to simulation, but a prerequisite for validation-grade outcomes. By structurally linking decision-grade data to runtime execution, Endeavor removed a silent but critical failure mode present in most simulation workflows.

Organizations often attempt to increase simulation fidelity by refining models while leaving data workflows untouched. Endeavor demonstrated that this approach misses the point. Without trusted inputs, even the most advanced physics engine becomes an approximation. This case establishes Endeavor’s platform as one where validation begins before simulation starts.