Each month thousands of perforating jobs are executed without problems; however, certain wells are susceptible to gunshock damage if they are perforated with inappropriate gun systems. This paper presents the application of a simulation program that predicts perforating gunshock loads reliably. This simulation program enables us to evaluate gunshock loads for any perforating job, including gunshock loads sensitivities to changes in gun type, charge type, shot density, tubing or cable size and length, rathole length, use of shock absorbers, and placement of packers, among others.
This simulation program helps engineers to identify perforating jobs that have a risk of gunshock related damage, such as bent tubing, unintentional weak-point pull outs, failures in gun release systems, and unset packers. When predicted gunshock loads are large, changes to the perforating equipment or job execution parameters are sought to reduce gunshock loads and the associated risks. For example, in this paper we present a typical case where a simple change to the guns charge loading transforms a high-risk perforating operation into a very safe one.
A large number of comparisons between predicted wellbore pressure and field fast-gauge pressure data are available in related SPE articles. These comparisons show that predicted wellbore pressure transients are very good, and in most cases where shock absorbers were used, residual deformation of crushable elements correlate well with the peak loads predicted by this simulation program. Additionally, this program is able to simulate perforating job designs in a short time, allowing engineers to optimize perforating jobs in a timely manner.
The ability to predict gunshock-induced damage in deepwater perforating operations is very important because of the high cost of typical wells and rig time. With the gunshock simulation capabilities presented in this paper, engineers can optimize perforating jobs by reducing gunshock loads, thereby the risk of gunshock-related damage and non-productive time.