BLOCKguAGE

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  Homepage

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  Data Populated Homepage through User Input File

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  Functionality to Delete Single Data Entries From The Table

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  Animated Loading Screen 1

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  Animated Loading Screen 2

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  Animated Loading Screen 3 (EOG Resources Logo)

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  Hydration Formation Prediction (sudden low gas volumes indicate high probability of a hydrate's presence and formation)

Inspiration

We are passionate about building solutions that require a strong logic and scientific reasoning. We are also interested in solving real-world problems through technology. We believe cutting down maintenance costs and simplifying jobs that require repetitive tasks such as Math and Physics calculations should utilize a scientific automation tool.

What it does

For lease operators at oil wells, this website can tell them when the gas pipe is likely to have been partially or completely blocked due to hydrate formation from change in pressure and/or temperature. The program detects anomalies in the data set provided by the user by calculating whether the instant gas value over the expected gas value is within the threshold of the amount that the gas valve is open (given as a percentage). Then, the program marks anomalies and identifies trends where they are clustered to mark it as a region where hydrates form.

How we built it

1. Backend: Flask and Python to simplify the process of reading an input stream.
2. Frontend: React in Javascript

Challenges we ran into

We ran into a challenge when trying to handle the multiple asynchronous requests between our back-end and front-end. Since we are taking a user's data stream via a file upload, using a database like Pinata, Supabase, or Firebase can help us store data to allow quick retrieval and avoid re-parsing when the json file is sent between function calls.

Accomplishments that we're proud of

Since our application uses flask to integrate the front-end and back-end components, we can easily scale our application and add many features. Our main focus was to display the hydrate concentration via the logic we defined in our python module. To improve this further, we added more UI elements in our front-end to display our summarized data.

What we learned

By using many libraries like pandas, papaparse, and axios we were able to receive, parse, and send data between our front-end and back-end components.

What's next for BLOCKguAGE

We wish to add further logic to the program so the website doesn't have to ask for a .csv file from the user to make accurate judgements of the data. Additionally, we hope to add notifications and instantaneous feedback from the website if there is a large hydrate forming at the time the user inputs any data, and also potentially develop an app version as well to provide customers with better user experience!

Built With

• flask
• javascript
• python
• react