Welcome to Danomics: Flows Guide
Getting Started with Flows
In this guide we will explain what Flows are and how you can use them to enhance your workflows and accelerate your interpretations. We will cover some basic examples that we hope will provide you with the fundamentals of how to construct a Flow. Flows can be quite powerful, but as they are a new concept to most users, we anticipate you’ll need some support. Don’t hesitate to contact us at support@danomics.com.
There are five videos in this series and walking through all of them will take 30-45 minutes.
Note: We’ll be using the data from the Welcome Project. You can access that data here:
- Production data (CSV format / Excel format)
If you need help loading the data, please see the Welcome Guide on Data Loading video.
What are Flows?
Flows are collections of tools that allow you to read in data, process data using a number of specified steps, and return modified data. For example, you can use Flows to condition your well log data, generate grids for mapping, calculating petrophysical properties, or making reports on your data. In the video below we briefly introduce the concept of Flows.
Example Flow: Log Health Checks
In this video we demonstrate Danomics Log Health Check Flow tool, which analyzes your data for a number of common problems.
Example Flow: Log Data Clean-up
In this Flow we demonstrate how to perform a workflow for cleaning your log data.
Example Flow: Making Grids
In this example Flow we demonstrate how you can generate grids from your petrophysical interpretation.
Example Flow: Using Python in a Flow
In this Flow we demonstrate a basic Flow that utilizes Python. We first build a simple Python tool, then enhance its functionality, and then add a graphical user interface and distribute it across the company.
Summary
Congratulations on completing the Welcome Guide for Flows. At this point you should have a basic understanding of how to use Flows to perform a number of basic tasks. There are a vast number of actions that can be done with Flows, so if you need help understanding the full scope of what you can do, contact us at support@danomics.com.
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DCA: Type well curves
In this video I demonstrate how to generate a well set filtered by a number of criteria and generate a multi-well type curve. Before starting this video you should already know how to load your data and create a DCA project. If not, please review those videos. Type well curves are generated by creating a decline that represents data from multiple wells.
DCA: Loading Production data
In this video I demonstrate how to load production and well header data for use in a decline curve analysis project. The first step is to gather your data. You’ll need: Production data – this can be in CSV, Excel, or IHS 298 formats. For spreadsheet formats you’ll need columns for API, Date, Oil, Gas, Water (optional), and days of production for that period (optional). Well header data – this can be in CSV, Excel, or IHS 297 formats.
Sample data to get started
Need some sample data to get started? The files below are from data made public by the Wyoming Oil and Gas Commission. These will allow you to get started with petrophysics, mapping, and decline curve analysis. Well header data Formation tops data Deviation survey data Well log data (las files) Production data (csv) or (excel) Wyoming counties shapefile and projection Wyoming townships shapefile and projection Haven’t found the help guide that you are looking for?