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add totals as measurements #284
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Original file line number | Diff line number | Diff line change |
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@@ -140,6 +140,9 @@ def _production_data(self) -> pd.DataFrame: | |
- WOPR Well Oil Production Rate | ||
- WGPR Well Gas Production Rate | ||
- WWPR Well Water Production Rate | ||
- WOPT Well Cumulative Oil Production | ||
- WGPT Well Cumulative Gas Production Rate | ||
- WWPT Well Cumulative Water Production Rate | ||
- WBHP Well Bottom Hole Pressure | ||
- WTHP Well Tubing Head Pressure | ||
- WGIR Well Gas Injection Rate | ||
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@@ -153,7 +156,7 @@ def _production_data(self) -> pd.DataFrame: | |
* Improve robustness pf setting of Phase and Type. | ||
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""" | ||
keys = ["WOPR", "WGPR", "WWPR", "WBHP", "WTHP", "WGIR", "WWIR", "WSTAT"] | ||
keys = ["WOPR", "WGPR", "WWPR", "WOPT", "WGPT", "WWPT", "WBHP", "WTHP", "WGIR", "WWIR", "WGIT", "WWIT", "WSTAT"] | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. You're adding Should you read those values at all? You can reconstruct the cumulative at any given date by calculating the cumulative sum over the rates (this would also be easier to use later on in other data sources)? Or do we expect big differences based on differences in reporting steps? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Edit: Sorry, you are only referring to injection here @wouterjdb. Then you may be right. The rates are instantaneous, and depending on the report step length we can get a quite different result reading the actual cumulative volumes and calculating them from rates. Over the years when doing uncertainty studies I have always calculated average yearly or monthly rates from cumulative volumes - for history matching purposes I guess the instantaneous rates are important - what I am saying is that we may need to import both then. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. We will only be using WGIT and WWIT if we prescribe BHP instead of the well rates during the history matching. Although I am not sure if there are cases where you would prefer to do that, I thought it would be good for completeness to just add them. I forgot about adding them to src/flownet/config_parser/_config_parser.py. |
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df_production_data = pd.DataFrame() | ||
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@@ -187,6 +187,9 @@ def _calculate_wconhist(self): | |
oil_rate=value["WOPR"], | ||
water_rate=value["WWPR"], | ||
gas_rate=value["WGPR"], | ||
oil_total=value["WOPT"], | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Recalculating could potentially mean that one doesn't have to supply this at all. |
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water_total=value["WWPT"], | ||
gas_total=value["WGPT"], | ||
bhp=value["WBHP"], | ||
thp=value["WTHP"], | ||
) | ||
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When adding WOPT (or WGPT or WWPT), should we allow for also adding WOPR (or WGPR or WWPR)? Conditioning on both rates and cumulatives i guess is kind of a messy thing with all the correlation going on. Should we add a check in the config_parser to make sure both are not defined?
Update: Let's leave it for now and add an issue on it so we don't forget about it completely
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I will make a new issue suggesting this and add an item to the CHANGELOG