In the oil and gas industry, downhole well integrity risk management is an important aspect for safe operations, and for optimizing production and overall costs. Diagnosis and evaluation services used by operators for these well integrity management programs include leak detection, corrosion inspection and cement evaluation. However, effective measurements for this critical task are more challenging when there is tubing or completion in the well, in front of casings that need to be evaluated. This paper presents the recent developments of through-tubing cement evaluation (TTCE) techniques with focus on applications, benefits, and limitations. Novel solutions to enhance data quality, while optimizing costs and improving safety, are also discussed.
There are several techniques currently used to evaluate cement quality behind casing with pressure testing being the most common hydraulic method to confirm a seal. In terms of logging techniques to determine the cement bond across the interval of interest, temperature logs were very common in the past but have since made way for sonic logs, ultrasonic logs, intelligent completion systems and others. Generally, these logging techniques require direct access to the casing or liner being evaluated and do not provide reliable answers when a tubing is in front of it. More recently however, sensing technologies, data processing and interpretation from these techniques has evolved thereby helping to overcome the signal attenuation and noise from the interface between the sensor and the actual cement sheath. This paper summarizes key findings and insights which form part of ongoing research and provides an overview of the methods and procedures involved in each technique. The elaborated processes in conducting TTCE and the challenges and limitations associated with each technique are also discussed. Results from this study show the importance of TTCE for evaluating the quality and integrity of cementing operations in oil and gas wells. Advances in downhole sensor design and signal processing is complemented by the fourth industrial revolution allowing use of machine learning algorithms for big data analysis and interpretation, which assists in improving the TTCE reliability considering certain constraints. However, each TTCE technique has unique benefits and limitations which allows it to be applied to specific well scenarios, and these are explored further here. This paper presents a comprehensive analysis of TTCE techniques and their applications for improving well integrity management. Key areas where TTCE can provide significant benefits are identified, such as in wells with complex geometries or with limited access for conventional cement evaluation methods. The paper also highlights the limitations and challenges associated with each technique and identifies opportunities for future research and development.