Aug 2026· SPE Nigeria Annual International Conference and Exhibition· 0 citations· 10 references
TL;DR
Smart PetroDesk is presented, an integrated suite of browser-based applications built to support day-to-day petroleum and reservoir engineering tasks within a single working environment, and shows measurable gains in efficiency and consistency relative to spreadsheet-based practice.
Abstract
Petroleum and reservoir engineers routinely perform well design, production surveillance, decline curve analysis, forecasting, and reserves estimation using toolchains that combine spreadsheets, desktop software, and ad hoc scripts. The lack of integration across these tools reduces analytical transparency, increases rework, and introduces data quality risk at each handoff point. This paper presents Smart PetroDesk, an integrated suite of browser-based applications built to support day-to-day petroleum and reservoir engineering tasks within a single working environment. Smart PetroDesk brings together lightweight browser visualization and a Python analytical backend to cover end-to-end workflows: wellbore and casing design, production data ingestion and quality control, decline curve analysis, production forecasting, reserves back-allocation, and regulatory reserves reporting. Data quality is enforced at the point of ingestion through schema validation, range checks, business-rule enforcement, and cross-file consistency checks. Decline model fitting covers the full Arps suite (exponential, harmonic, and hyperbolic), using objective goodness-of-fit selection and explicit abandonment criteria. Application across representative engineering workflows shows measurable gains in efficiency and consistency relative to spreadsheet-based practice. By housing established petroleum engineering methods in a modular, extensible platform, Smart PetroDesk offers a practical foundation for production and reserves work and a clear upgrade path toward broader digital oilfield capability.
Nigeria's oil and gas sector continues to face a persistent digital bottleneck: valuable subsurface and production data remain difficult to access, costly to acquire, and tightly constrained by proprietary controls, while advanced simulation and analytics ecosystems are still largely dependent on imported platforms....
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