Quantifying Perf Erosion: Discover the Cause and Fight Against It on Your Next Pad
Data Science & Analytics

Quantifying Perf Erosion: Discover the Cause and Fight Against It on Your Next Pad

Rosemary Jackson  •  

Q:Can perf erosion be quantified for post-job analysis?

A: Dr. Nitin Chaudhary, Senior Data Scientist explains, “Petro.ai, in a post-job completions report, gives you when the perf erosion started, when it ended and how much your perf diameter changed over that time period. This report is one of many generated to provide a full well life cycle understanding. We start by helping you plan your pad, where to place the wells. That is our pad design report that we generate for you. We can plan out the completion intensity, that is our completions scenario analysis that we generate for you.

“You take our recommendations; you pump in that same design. Then once you finish pumping all your stages on the pad, we can take that pumping data and help you understand what the effectiveness of your completion was, by generating a post-job completion report. One of the key aspects of that post-job completion report is that it quantifies the amount of perf erosion you had. We also curate some other KPIs around it to help you answer what caused the perf erosion and how you can fight against that in the next pad you will be doing.”

perf erosion

Perf erosion has been linked to missed limited entry targets. One perforation in a casing grows large while another hardly changes. In an article titled, Fracturing Plans and Reality Often Look Really Different, SPE reveals that “hydraulic fracturing often misses its target, and productive early wells in stacked plays may be the template for development plans that leave a lot of hydrocarbons stranded.”

“Petro.ai has addressed this critical issue,” Dr. Chaudhary continues, “Most engineers have a qualitative concept around what’s happening with perf erosion, where the hole size in the lateral increases for some holes but not for others, but they don’t quantify it. You know that you have a non-uniform stimulation across the lateral, but you don’t know why and diagnostic testing is time consuming and costly.”

perf erosion

“Let’s say I drilled five wells in the last month, there’s no way to quantify what stages had perf erosion and what stages didn’t have perf erosion. And if they had perf erosion, why did it happen. Perf erosion is qualitatively understood, but engineers until now hadn’t been able to quantify the process.

“Operators have tried to quantify it by literally putting cameras down hole and taking a picture of that hole. They would take a picture before they start pumping fluid down there. Then, they pump fluid for a two-hour period and at the end of the stage, they take a picture of that hole again to see how much bigger the hole got. That’s the extent of quantitative measurement that people have done for perf erosion.

“As you can imagine that’s not very sustainable. It’s extremely expensive to run down hole cameras like that. And even if we were to make that measurement, we’d still need to build some sort of a model so that the next time we’re doing a new well, we’d know beforehand if there’s going to be erosion and how much erosion there’s going to be. We can plan around it.

“That’s what the Petro.ai perf erosion model does. You can curate a quantitative measurement of how much perf erosion you’ve had over the hundreds of wells you’ve drilled in the past. If you have frac van files over all those wells, Petro.ai can, with an automated algorithm, go in and clean up your perf fragment files and upload them into our platform. We run this prediction where it will go in and for every stage on all the wells, it will quantify the amount of perf erosion you experienced.

perf erosion

“Using Petro.ai for the full well life cycle allows our operators to model the important sensitivities and draw in all the relevant factors that affect the productivity of a well and of a pad. Understanding and reducing perf erosion is possible with the data you provide and the AI analysis generated by Petro.ai.”

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