Realization of Precise Perforating Using Dynamic Threshold and Physical Plausibility Algorithm for Self-Locating Perforating in Oil and Gas Wells
For the oil and gas industry, this work provides a computationally efficient solution for automated depth correlation in wireless perforating, reducing reliance on surface infrastructure.
The paper tackles the challenge of real-time depth measurement for perforating in oil and gas wells using downhole casing collar locator signals. The proposed DTPPMP system achieves a collar recognition F1 score of 98.6% at 1000 Sa/s with only 1.5 μs per sample, enabling accurate depth calibration on resource-constrained downhole electronics.
Accurate depth measurement is critical for targeting designated perforation intervals to maximize hydrocarbon recovery. While next-generation automated wireless perforating techniques reduce reliance on costly surface infrastructure and personnel, they lack the continuous depth correlation provided by conventional wireline cables. Consequently, correlating real-time casing collar locator (CCL) signals with a pre-recorded casing tally is essential for automatic depth determination. However, implementing this measurement remains challenging: downhole instruments must process CCL signals in real-time to identify collar signatures from complex interference, a task severely restricted by the limited computational resources and power budget of high-temperature downhole electronics. To address these constraints, this work proposes the Dynamic Threshold and Physical Plausibility Depth Measurement and Perforation Control (DTPPMP) system. This integrated solution enables in situ depth calibration by correlating CCL signals with the casing tally using lightweight algorithms for dynamic-threshold-based collar recognition and physical plausibility verification. Field tests demonstrate a collar recognition F1 score of 98.6% at a throughput of 1000 Sa/s. Notably, the algorithm requires only 1.5 μs per sample, confirming its computational efficiency and suitability for deployment on resource-constrained, high-temperature downhole platforms.