Abstract

Abstract This study produced a quantifiable dataset that provided analysis and interpretation of field activities over more than 20,000 rig-hours during a 14-month period. The data was obtained by sealed independent electronic measurement from selected well service providers performing assorted jobs during a variety of conditions. This work was begun because there are no known published or accredited standards or guidelines for well service performance. Primary focus of the study was overall job quality, rod and tubing make-up (measuring sequences in time increments of seconds), time studies, crew efficiency, and safety. Information stored on the rig recording unit was retrieved with remote electronics. Archived data was analyzed graphically and reported to well service and oil companies to develop and maintain well histories and crew efficiency, identify optimum procedures, safety, and time studies. Current industry quality-assurance practice is the occasional overview of well service crews by a field engineer or foreman. Those positions rely on visual perception and experience to judge service quality and procedures. Existing methods still result in extraordinary repeat failure rates and unresolved service problems. This new technology documents and resolves deficient intrinsic field cultural practices. Our empirical data and analysis conclusively show that repeat failure rates and downtime are reduced. Service crew awareness about their work and efficiency is raised to a higher level. Productivity increases, artificial lift costs decline, and fair accountability is maintained with permanent records. Oil companies are using this new technology to establish and monitor their alliances. Service companies are using the results to train crews in proper techniques. Credible reporting now enables and mandates performance over personalities when making long-term economic decisions. This technology will push evolution of the well service industry with the establishment of quality and performance standards. Quality standards rather than perceptions will be the basis for decisions.

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