A novel formation tester for high quality virgin formation fluids sampling and its arrival prediction under deep invasion

Wireline formation fluid sampling is extensively utilized to acquire downhole fluid samples. Due to mud filtrate invasion, enough time is required to pump out the formation fluid so that an acceptable level of contaminant is reached. Excessive cleanup time would increase costs and the risk of the testing tool becoming stuck within the drilling mud. The challenge lies in deciding what type of formation-tester probe should be used to ensure minimally contaminated measurements for a specific tool configuration and when the withdrawal sample is sufficiently purged of contaminants. A numerical simulator to simulate the virgin formation fluid sampling was developed, and the accuracy of the simulator was validated based on the spherical flow theory. Through running 2515 simulation cases, the effects of various operational and formation conditions on the breakthrough and pumpout times with three different probes (i.e., the standard probe, the elliptical probe, the elongated probe, and their corresponding 3D radial probes) were compared and analyzed quantitatively. We numerically investigated the key factors influencing the breakthrough and pumpout times and delved into the impact of the formation anisotropy. This study reveals the parameters that encompass the first-order effect on the breakthrough and pumpout times, enabling the determination of the probe-type selection and the early predictions of pumpout time. By leveraging these insights, sampling operations can be optimized to enhance sample quality, reduce operational time, and mitigate the risks associated with tool entrapment.

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A novel formation tester for high quality virgin formation fluids sampling and its arrival prediction under deep invasion

Cited by 2 publications

References 18 publications

Enhancing wireline formation testing with explainable machine learning: Predicting effective and non-effective stations

Enhancing wireline formation testing with explainable machine learning: Predicting effective and non-effective stations

Numerical Simulation of Formation Fluid Sampling with Three Different Probe-Type Wireline Formation Testers

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