True Randomness in the Oklahoma and Texas Oil Fields: QuantumLaso’s QRNG-Powered Simulation Studio
- mansour ansari
- Apr 12
- 3 min read
The USB QRNG hardware I am using is from Cryptalabs. This nifty little cool device made this project possible. I will cover the hardware in another post.
I’ve seen quite a few Monte Carlo simulation desktop apps out there—some of them look slick, and a few are very expensive. But you know what they’re all missing?
A Quantum Interface.
That’s where mine stands apart.
While others rely on classical randomness—predetermined pseudo-random number generators—I wanted something different. Something that taps into the raw, unpredictable chaos of nature itself. So I built it.
Over the past few weeks, well, since January when I was thinking about this, I put in about 150 hours of deep, focused work—designing, breaking, stitching, testing, failing, redesigning, doubting, swearing, walking away, coming back, and then finally… breakthrough. Like sunshine after weeks of rain.
The result? A Monte Carlo simulation app powered by true quantum randomness—not just another number factory on a loop. And while yes, AI has made certain aspects of building such systems easier, the real challenge is still the same: making the damn thing work. Now, writing apps using the Python language is a lot easier than doing the same project, given its complexities, it takes a lot of extra work to maintain a working Python workbench. Small mistakes set you back a few hours.
I mean, you can’t shortcut the process. You have to live inside the trial and error. You hit walls, you question your sanity, you chase a bug for two days that turns out to be a missing comma—and somehow, in all that chaos, you find a shape.
And this time, I found mine.
I believe simulations deserve more than pseudo-random guesses. That’s why I’ve built a next-generation Oil & Gas Monte Carlo simulation engine powered by Quantum Random Number Generation (QRNG) — not just any RNG, but a hardware-verified quantum entropy source. I tap into a USB device and pass it the quantum bits and pollens to an app that, in turn, injects the key into the live simulation. How about that? Huh?
When I ran into the Streamlit website, I knew I could use this to build what I want. The application, built on Streamlit, (You should check it out - see the link below!) allows users to simulate oil exploration scenarios using real-world geological and economic parameters. Writing a simulation using their framework is now easy for developers while allowing you to wrap your core logic in a nice-looking presentation. So here is a snapshot of my new oil and gas simulations. A working demo will be uploaded to the CLOUD soon, simulating the real app running in a secure local desktop PC.
Users can select between:
Classical PRNG (for baseline tests)
Quantum Key Storage Mode (true entropy from .bin files)
Live QRNG Mode (real-time randomness via USB QRNG device on COM4)
With this tool, users can:
Define porosity, recovery factor, oil price ranges, and drilling costs
Generate true stochastic reservoir scenarios
View profitability histograms, cumulative probability curves, and key risk metrics like P10/P50/P90 profit levels
Export results for reporting or strategic decisions
But the real power lies in the Quantum Entropy Core. It’s not just a buzzword — this system leverages the Pycalabs USB hardware that meets NIST SP 800-90B entropy standards, pushing the fidelity of simulation models into a new probabilistic frontier.
This is the first simulation tool of its kind in Oklahoma — and proudly built by a garage-based rebel team unafraid to combine physics, AI, Python Scripting, and rugged engineering. I love this incredible tool - I hope you can find it useful, and it will be available for sale!
PS: I have two more simulations cooking right now—one for Drug Discovery and the other for Wealth Management. Stay tuned!
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