While no forecasting tool can guarantee 100% accuracy, the NGL Monitor leverages the latest EIA data and advanced analytics to provide the most reliable and accurate forecasts possible. We continuously improve our forecasting models to enhance their accuracy and reliability. We will be providing deltas to our forecasts inside of the monitor to show their effectiveness. More information will be shared on this as the product continues to evolve.

In cases of missing or incomplete EIA data, the NGL Monitor employs advanced interpolation and estimation techniques to fill in the gaps, ensuring that the forecasts remain as accurate and reliable as possible.

The NGL Monitor utilizes a combination of statistical models, including time series analysis, regression analysis, and machine learning algorithms, to generate accurate and reliable forecasts for natural gas liquid supply and demand.

The NGL Monitor incorporates seasonal decomposition of time series data, which helps identify and adjust for seasonality patterns in natural gas liquid supply and demand trends. This ensures that the forecasts generated are more accurate and relevant to current market conditions.

The NGL Monitor employs robust outlier detection and smoothing techniques to minimize the impact of extreme events or anomalies in the data, ensuring that the forecasts remain as accurate and reliable as possible.

The NGL Monitor continuously incorporates the latest EIA data and market information into its forecasting models. As market conditions change, the tool adjusts its forecasts accordingly to ensure they remain relevant and accurate. Over the past decade, Primary Vision Network has positioned itself as an industry leader in monitoring operator and pumper activities through our proprietary Frac Spread Count. Our services offer unparalleled granularity, reflecting our deep understanding of industry seasonality and trends. To maintain our competitive edge, we have developed an advanced manual exception handling tool that allows for the fine-tuning of our forecasts in response to unforeseen events, such as short-term weather anomalies or major economic disruptions like the Covid-19 pandemic.