Technology Focus: Sand Management (October 2021)

Abstract

Our industry is under pressure to produce cleaner energy. That is the mantra, more so than a few years ago. A recent report from the International Energy Agency suggested that all greenfield developments in the oil and gas sector should be stopped forthwith if we are to achieve the net-zero target by 2050. That essentially means that we squeeze what we can from the not-so-easy and mature reservoirs, many of which have sand-control problems. Perhaps that is the reason most operators are working ever harder to manage and produce such assets, a trend reflected in the number of papers written. More importantly, a large proportion of papers this year were on sand consolidation and through-tubing exclusion methods, which primarily target mature producing reservoirs. A few technology trends are becoming apparent. There is a move to gravel pack longer and longer horizontal sections. It is now possible to pack more than 7,000 ft with zonal isolation. Through-tubing sand-control remediation continues to evolve. Sand consolidation is moving toward nanoparticles, with a promise of better regained permeability. Further strides have been made in developing filters to achieve behind-screen compliance for better sand retention. Industry has been enchanted by what data analytics and machine learning can potentially offer, and perhaps rightly so. Several papers this year apply these tools to sand management. For those interested, I would recommend paper SPE 200949 and OTC 31234 as further reading. Unfortunately, from a sand-control perspective, I do not yet see a compelling narrative. One interesting statistic that I stole from a LinkedIn post is that the rising 3-year trend of papers in OnePetro on this subject has fallen dramatically between 2020 and 2021. I have not independently verified these figures, but it does tell a story. Is the excitement waning? Recommended additional reading at OnePetro: www.onepetro.org. SPE 203238 - Sanding Propensity Prediction Technology and Methodology Comparison by Surej Kumar Subbiah, Universiti Teknologi Malaysia and Schlumberger, et al. SPE 201768 - Using Artificial Intelligence for Determining Threshold Sand Rates From Acoustic Monitors by Srinivas Swaroop Kolla, The University of Tulsa, et al. OTC 30386 - Pioneering Slickline Deployed Through Tubing Gravel Pack in Malaysia: Successful Case Study and Lessons Learned by Ertiawati Mappanyompa, Petronas, et al.