Data Analytics (ProdANALYTICS)

Prodanalytics is the data analytic tool uesd for the analysis of reservoir production data for the oil and gas E&P companies to maximize their operational efficiency and production optimization.

The tool is used for cost and time saving for by oil and gas (E&P) companies by doing analysis through production data itself rather than numerical simulation. This approach saves month’s time for operators in numerical simulation studies as wells as purchasing expensive simulation software.

Using this tool, operators can know many aspects of reservoir, production and field development planning which can extremelly improve their operational efficiency without any involvement of simulation work.

The software assists in evaluation of dependency of predicting variables (Injection rates, Water Cut, GOR, Down-time, Pressures etc) on response variable (oil rates) through different statistical regression methods such as:

  • Random Forest (RF)
  • Co-relation and Co-variance
  • Multiple linear regression
  • Neural network
  • Multivariate adaptive regression splines (MARS)
  • Gradient Boosting
  • AutoRegressive Integrated Moving Average (ARIMA)
  • Vector Autoregression (VAR)
  • FB Prophet
  • Long Short-Term Memory (LSDM)
  • K Nearest Neighbor (KNN)

The tool makes it remarkably easy to optimise production efficiency through analysis of inter-dependencies of multiple parameters. It assists in developing statistical set of equations to demonstrate interdependencies of predicting variables vs. response variable for a certain test data (for e.g. an EOR). These statistical relationships can be tested on a broader data set (for e.g. multiple well patterns).

Benefits of Prodanalytics:

  • Identify reservoir pressure regime: Identify producer (s) where injection support is not required and producer (s) where injection ramp up will be beneficial.
  • Production optimization: Optimize injection rate, slug size, concentration, viscosity and other controlled variables to maximize in-situ impact on EOR/IOR
  • EOR gain quantification: Measure gains from EOR processes by de-convoluting the multiple parameters involved and their relative importance for the EOR process itself
  • Predict production from future wells: Develop a library of type curves to estimate production for upcoming wells.
  • Analyze existing older wells that diverge from forecasted trends to be identified and remediated
  • EOR monitoring and analysis of field trials to predict the efficacy of EOR mechanism for e.g. WAG
  • Pressure Conditioning: Understanding reservoir pressure regime and pressure buildup process in shut-in wells to estimate optimum shut-in time for effecting wells for maximize production.
  • Locate and remediate underperforming wells
  • Develop EOR campaign for upcoming similar field or region.
  • Reducing operational downtime by sensing and predicting the performance envelope of equipment
  • Improving the HSE measures through preventive maintenance
  • Optimize drilling operations by identifying anomalies and problematic factors. Optimize drilling parameters through real time monitoring and decision making