Optimizing Hot Tapping Using the Fuzzy Logic Modeling Approach

Abstract

Strong demands for energy compels the oil and gas industries to increase productivity. Since transportation of oil and gas products through pipelines is the most efficient way to deliver these products, there is an ever increasing network of pipelines from the production fields to the processing plants. Construction and operating costs, however, limit the proliferation of pipelines. Hot tapping is an economical technology that the oil and gas industries use to minimize oil and gas pipeline segments by connecting a new facility to the nearest operating unit processing the same product. Technologically speaking, hot tapping is challenging especially during field installation. Welding a branch pipe/pipeline to an in-service pipeline has two major concerns: burn through and heat-affected zone (HAZ) cracking. Thin pipe wall thickness and the use of welding electrodes with high hydrogen contents can promote burn through and HAZ cracking. Improper hot-tapping procedures applied on a live pipeline may lead to disasters that can be life threatening to the welding operators. Parameter optimization is essential to ensure successful hot tapping. In this paper, fuzzy logic modeling was used to optimize the hot-tapping procedure, i.e. to minimize burn through and HAZ cracking, for processes that use shielded metal arc (SMA) welding. A total of 324 rules were built to consider multiple welding parameters, pipeline and operating characteristics such as heat input, electrode type, pipe inside surface temperature, wall thickness, hardness, and fluid flow to study the effects of these parameters on the weldment. These parameters were the fuzzy logic model inputs for successful hot-tapping conditions. For each pair of parameters, the output of the model is a processing surface on which successful hot tapping can be conducted. A graphical user inference (GUI) easily retrieves the different sets of parameters and their respective safe hot-tapping surfaces on which burn through and HAZ cracking can be avoided. As conclusion, the present study demonstrates that fuzzy logic modeling can be used to provide guidelines for in-service pipeline hot tapping. Careful modeling can result in safe welding space for hot tapping and allow for the specification of standard welding procedures within the safe welding zone. The guidelines and range of safe welding parameters from fuzzy logic modeling can reduce the size of the experimental matrix required during field weld testing for the determination of the final parameters.