Investigating the integrity of a casing, with the tubing in place, has always presented a challenge to operators worldwide. Even more challenging, is taking on an investigation into cross flow between formations & identifying regions of flow behind pipe, all while the tubing is still in place. Flow behind pipe has always been a well debated subject amongst industry professionals; most advancement in this matter has been subjective, based on well educated speculation and largely dependent on temperature profiles and changes in the geothermal gradient. Saudi Aramco have recently utilized a new ultrasonic based, diagnostic technology, in order to map regimes of flow behind pipe, identify cross flow between downhole formations, locate casing leaks with a pin-point accuracy, all while the tubing is in place, and while using conventional Electric Line logging. This technology exploits the innate physical properties of ultrasound. The capacity of ultrasonic waves to propagate through numerous and varied media, including steel, liquids & compressed gas; allows a radial investigation of up to 3m. Unlike several technologies that utilize ultrasound, this diagnostic tool, is a passive listener, with no transmitters. It is designed to pick up the sonic energy fluctuations created by the turbulent flow of fluids over a specific spectrum within the ultrasound frequencies window. A window that is so uniquely suited for precision wellbore diagnostics. This paper presents the basic physics behind the technology chosen by Saudi Aramco to address the aforementioned issues. It will highlight the possible applications of these tools and more specifically discuss the recent case studies successfully performed in Saudi Aramco.

Milling a stuck partially opened wellhead tubing master valve (TMV) becomes inevitable to access the wellbore if all repairing attempts had failed. Typically, the milling can be accomplished by utilizing a milling machine, mounted on a wellhead, equipped with motors and special mills. In this case history, CT was selected to fully satisfy standard well control requirements. Different sizes of mills were utilized to provide access through the double disc gate valve to facilitate setting downhole barriers to replace the defective TMV with a new one safely and successfully. The post-job visual inspection of the milled bore showed regular cut of this gate valve. This paper highlights the extensive planning and preparation work performed to execute the job safely and successfully. The paper will also focus on the thorough risk assessment procedure and contingency plans to ensure all well control requirements are fully covered. This unique operation has showed that milling TMV using CT is proved to be a viable option addressing well control issues while performing the milling operation. The paper will also present many lessons learned to be applied in future similar jobs.

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This paper presents a well performance modeling approach to generate reservoir static bottom hole pressure (SBHP) data from on-stream oil well production data in wells completed with Electrical Submersible Pumps (ESP). The approach does not require shutting-in the well to obtain the SBHP as conventionally required prior to data collection. Hence, production losses are eliminated without compromising reservoir pressure surveillance. Recording downhole SBHP is an essential requirement for reservoir pressure surveillance as it provides significant information to evaluate reservoir inflow performance. SBHP data is used to generate the periodic isobaric maps, update the reservoir simulation models, and re-evaluate the applied injection strategy for possible adjustments when needed. Rigorous reservoir and wellbore performance analysis techniques were employed to generate accurate top-down reservoir pressure prediction models. The predictability of these models was statistically assessed on field representative samples of ESP completed wells with a wide-ranging operating parameters i.e. liquid rate, flowing wellhead pressure, water cut and reservoir pressure. In this modeling, ESP downhole sensors data were leveraged to reduce the uncertainty of the outflow performance models. A sample of 22 case studies from 4 different reservoirs was studied. These case studies were diligently selected to represent all ranges of operating parameters and reservoir pressure. Sensitivity analysis was performed on the well performance models to identify sources of uncertainty that can affect the model accuracy. Overall, this method has been proven to be widely accurate. The prediction performance of this method was found to be within 1.5% accuracy of actual pressure measurements.