Arps type curve in spotfire new ways to make money online in 20 minutes – data shop talk

Type curves are an important part of resource assessment of new ways to make money online an oil and gas asset. In this workflow, well declines are aggregated to determine typical behavior of a new ways to make money online well ensemble. These well ensembles usually reflect a reservoir or set of new ways to make money online analog reservoirs that will help determine characteristic behavior. In this post, we will build a decline model for the group of new ways to make money online wells that is called a type curve. The type curve will capture the production rate forecast for new ways to make money online a single “average” well and so can be used to determine estimated ultimate new ways to make money online recover (EUR). Best yet, we’ll do it in 20 minutes. A little longer than GEICO, but you’ll save so much more money.

There are countless tools that support the type curve workflow. There are also many levels of sophistication around type curve new ways to make money online prediction, handling different flow regimes, decline characteristics, and uncertainty. Since type curve generation is so central to resource assessment, though, it’s useful to be able to merge it with the new ways to make money online adhoc analytics capability of spotfire. So useful, in fact, that it will open up a lot of different pathways new ways to make money online for improvements of the resource assessment process especially for unconventionals. But that’s for a different post.

At the end of the day, anyone who has done type curve fitting knows it’s as much of an art as it is a new ways to make money online science. The statistical best fit may not actually model the dynamics new ways to make money online of the reservoir and it takes an engineer’s intuition to model a more accurate forecast. The machine can get close, though, and that’s where the dynamic and interactive nature of spotfire is new ways to make money online really going to improve the type curve fitting workflow.

In this post, we will walk through the mechanics of calculating vanilla type new ways to make money online curves in spotfire. You can get the end result off of exchange.Ai. I call our objective ‘vanilla’ because this is the most basic, straightforward method. There’s a lot more you can add to the decline new ways to make money online fit to improve its usefulness. Let’s consider those extra toppings… like we could make hot fudge type curves. Who says data science can’t be delicious?

Because we want this to run out of the box new ways to make money online in spotfire, we are going to use base R, meaning we won’t use any packages. There are several things we are doing which would be new ways to make money online easier done with an R package, but we don’t want to complicate the user’s experience by having to install packages. Plus, there’s nothing better than implementing things from scratch to make new ways to make money online sure you know what you’re doing. Data

We will assume that you have access to well header new ways to make money online and production data. On the well header table, it’s nice to have location, reservoir, well type, and other metadata that will help you grab reasonable well new ways to make money online groupings. For production, there needs to be a valid lookup column to relate new ways to make money online it back to the well header table and should have new ways to make money online your fluid rates (oil, gas, water). The table itself can be daily or monthly. If you’re doing a play assessment, it’s likely you only have monthly data. The granularity of monthly data works well for the type new ways to make money online curve workflow as it cleans up a lot of the new ways to make money online noise inherent in daily rates. If you are using your own proprietary data then you new ways to make money online probably have daily. The method in this post is general to either; it really just changes the units of the results (e.G. BBLs decline per day or per month).

For this workflow, we will use the arps equation. You’ll see in the code how you can make this new ways to make money online more general (or put in your own “secret sauce” type curve equation). Ultimately, we will use R’s nonlinear equation fitting functionality to find the best fit new ways to make money online for parameters. Since it’s nonlinear, you can put in pretty much any function to be new ways to make money online fit. There are caveats, of course, as it may not be able to find the best new ways to make money online fit parameters given the starting conditions and function characteristics. Calculating a best fit type curve

Let’s start by getting the data into spotfire’s TERR environment. This is done by creating a data function and sending new ways to make money online in the production data. I’d suggest limiting the production data you send in by new ways to make money online marking or filtering, but of course that depends on the workflow you want new ways to make money online to develop. In this post, I’ll assume you’re only sending in production you’ve limited by marking. If you have no idea what I’m talking about, just keep reading because this part isn’t necessary for calculating type curves.

Now we are going to predict oil rate using time new ways to make money online (basically decline). We will use the arps function which takes three parameters: initial oil rate (qi), effective decline (de or a), and decline degradation (b). These three parameters describe the initial production rate, its initial decline, and how decline changes as a function of time. In R, we can use the ‘nls’ function to find a best fit of the parameters.

I’ve provided some reasonable start values for the parameters. If you don’t provide this, nls may not consistently find a good value. We could improve this by first doing a linear exponential new ways to make money online fit then using those values as start parameters. I’ve told the function to only warn me if it new ways to make money online doesn’t converge. Basically, I still want the values back even if we didn’t get to convergence. The user can just run it again if they don’t like the fit.

You can grab the spotfire template off of exchange.Ai. In the template, it helps the user define type curves for different regions, then compare the results of the fit curves. Usually you want to compare type curves from different areas new ways to make money online (geographically, geologically, or competitively). So, this means you need to store the results of each new ways to make money online type curve run if you like the fit. The template provides the functionality for you. Going further

Type curves are a core part of several oil and new ways to make money online gas resource assessment workflows. For anyone doing data science in oil and gas, they are a common and useful technique to have in new ways to make money online your back pocket. Because time is one of the strongest predictors for performance new ways to make money online of a reservoir – due to the drop in pressure of the reservoir by new ways to make money online production – any regression technique needs to take time into account. So, whether you like it or not, you have to take type curves into account!

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