The Time Series widget is the only widget that visualizes time series data in Diagnostics 2.0 (v1). It’s designed for rollups and side-by-side comparisons of production history, forecast volumes, and derived series.
Displays aggregated time series across your chosen scope:
Selections (manually selected wells)
Saved Filters (named groups)
Header groups (e.g., operator, county—based on available headers) which you need to create Row Groups in order to "Group By" on the charts within the Columns window
Depending on the time series settings used when Diagnostics was run and what you’ve enabled in the UI, you may visualize:
Production history
Forecast volumes
Stitched volumes
Cumulative profiles
Delta series (differences)
Rollup mode (Selection / Filter / Header):
Selection: Aggregates your currently selected wells.
Filter: Plots multiple saved filters independently on the same chart (useful for A vs. B comparisons).
Header: Aggregates by a header category (e.g., Current Operator).
Important: The header must be enabled in the Metrics Manager to appear here.
Toggle series visibility: You can turn off series types you don’t need (e.g., hide delta columns).
Export: Right-click to export to CSV/Excel. Export respects the ordering and series choices you’ve set in the widget at that moment.
Note: Some ordering choices are not saved between sessions.
The Time Series widget is highly interactive with selection:
If you select wells (from the Map or the Scalar Table), the Time Series rollup updates immediately.
Clearing the selection resets the rollup (no selection = no selection-based time series).
The Histogram widget shows the distribution of a selected scalar metric (e.g., b-factor, Qi, EUR) across wells or across aggregated groups if you choose to group.
Metric selection: Choose which scalar metric to histogram (only metrics enabled in the Metrics Manager will be available).
Group by: Switch between:
Wells (each bar represents a distribution of individual wells)
Aggregated groups (e.g., operator-level values)
Aggregation behavior: If you group by operator (or other header), the values shown are derived from the Scalar Table rollups, using the aggregation rules defined in the Metrics Manager (sum vs average vs min/max, etc.).
Driven by the Scalar Table scope and the Metrics Manager’s loaded fields.
Responds to selections (depending on how your dashboard and selection scope are used).
The Cumulative Distribution widget plots the cumulative distribution of a selected scalar metric so you can quickly understand percentiles and compare spread across wells or across aggregated groups if you choose to group.
Metric selection: Select a scalar metric to evaluate (must be enabled in Metrics Manager).
Group by: View distribution at:
Well level (each point = well)
Aggregated level (each point = group such as operator)
Common “why don’t I see X?” scenario: If you don’t see gas/water metrics (or a specific metric) in the selector, it’s because it wasn’t enabled in the Metrics Manager.
Powered by Scalar Table data and limited to what you’ve loaded through Metrics Manager.
Best used alongside Histogram for a quick “shape + percentile” view of the same metric.
The Cross Plot widget compares two scalar metrics (x vs y) to reveal relationships, clusters, and outliers across wells or across aggregated groups if you choose to group.
X metric & Y metric: Choose any loaded scalar metrics or numeric headers.
Color by: Can use string fields (e.g., operator) to color categories.
Size by: Must be numeric (headers or diagnostics metrics).
Grouping: Choose whether points represent:
Individual wells, or
Aggregated groups (based on current Scalar Table grouping / aggregation rules)
Cross Plot allows comparing forecasts (especially when in comparison mode), but:
Certain forecast-specific selections are not saved in a Visualization Configuration because forecast context can change between projects.
What is saved is typically the metric choices (which fields you plotted), while forecast references may reset based on context.
Uses Scalar Table values, so it’s tightly coupled to:
What’s loaded (Metrics Manager)
How rollups are defined (Metrics Manager aggregation settings)
Whether you’re viewing wells or grouped data (Scalar Table grouping)