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How can we improve oilfield production forecasting with predictive analytics?

It's always been a challenge to estimate the reserves and predict production in oil and gas fields. The accurate analysis and estimation of reservoir behaviour are very essential to assess the reserves and potential forecasts for production. The complexity of data, combined with limited analytical insights help to understand the integrity of wells under management.<br><br>visit us : http://meerasimulation.com/

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How can we improve oilfield production forecasting with predictive analytics?

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  1. How can we improve oilfield production forecasting with predictive analytics

  2. How can we improve oilfield production forecasting with predictive analytics • It's always been a challenge to estimate the reserves and predict production in oil and gas fields. The accurate analysis and estimation of reservoir behavior is very essential to assess the reserves and potential forecasts for production. The complexity of data, combined with limited analytical insights help to understand the integrity of wells under management.

  3. How can we improve oilfield production forecasting with predictive analytics • All the processes in the oil and gas industry is exploration, development and production of crude oil or natural gas. The predictive analysis helps companies in asset maintenance improvement, exploration optimization, production optimization, risk assessment and drilling optimization. Based on this model, companies can easily identify which team with what kind of equipment can yield the highest work efficiency under specific geographic conditions.

  4. The Mechanism of Predictive Analysis Process The predictive analytics process usually contains different  features and steps as follows; • Define Business needs • Data collection • Data analysis • Statistics  • modelling and deployment.

  5. The Mechanism of Predictive Analysis Process • By establishing models, the companies can get maximum opportunities to capitalize on market conditions. In this process, the Predictive analytics, combined with decline curve methodologies, provides more informative forecasting results of future production. Different Reservoir simulation software also help to; •  Access well and reservoir data quickly and easily with automated data profiling and time-series selection.  • Apply analytical functions consistently using a forecasting solution that automatically selects the best model. • Perform decline analysis quickly with a robust analytical engine to adjust, industry-standard default values.  • Estimate unconventional sources of well production more accurately using best-fit prediction that uses smaller data sets when large volumes of historical data are not available.

  6. Automated Analytical Techniques • Different automated analytical techniques improve confidence in reserves estimation. These techniques also generate results your company can rely on for financial reporting. There are a lot of advantages of these techniques; • Analytical techniques define the most statistically significant data set for the production forecast.  • Analytical solutions normalize data distributions and minimize rogue values to ensure compatibility of data sets with curve type selection. • Better predictions result from evaluating the performance of wells and reservoirs under simulated business and environmental conditions.  •  Advanced data visualization identifies and visualizes problematic wells or reservoirs. • Advanced analytical approaches go beyond business, as usual, to quantify measures of uncertainty, increase forecast robustness and deepen understanding of oilfield performance.

  7. How Predictive Analytics Is Transforming Technology? • Different companies are using predictive analytics transforming their own technology and data capabilities to predict a better performing and sustainable future between operators, service providers and technology makers. Research proves predictive analytics are being tested and applied in:  • Machine learning to improve safety improvement capabilities • Unconventional wells to change management attitude • Behavioral modelling to reduce the frequency of safety incidents • Exploring fully automated drilling platforms • Automated analysis of subsurface data

  8. Conclusion Different studies show how the experience of predictive analytics is used in consumer markets. It can provide better insights on how more accurate predictions are generated when multiple sets of data from different sources are gathered up.

  9. Thank YOu This presentation brought to you by Meera Simulation – A first hybrid 3D reservoir Simulator

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