Real-Time Digital Survey

In the industry, the collection of information, data capture, and activity logging on paper have been a tedious and error-prone process. This working methodology has led to inefficiency in planning, task allocation, and results review, as well as the generation of a large number of unnecessary documents and errors. However, the availability of technology such as laptops, tablets, and smartphones has enabled a more efficient solution for data gathering.

Two application examples presented in this article illustrate how this technological solution has transformed the industry. In the first case, at a gas expansion plant, a solution was implemented using Lemon Forms to expedite visual inspections. In the second case, during the inspection of injection wells in oil fields, a customized form was developed, allowing for the rapid evaluation of well suitability and risk assessment.

Evaluating Coating on Stored Pipes: Ensuring Integrity during Prolonged Storage.

In a world where pipes often rest in warehouses for extended periods, despite being designed for buried service, the need for a thorough evaluation of their condition and fitness for service arises. This issue, often overlooked, has been exacerbated by the growing global problem of poor adherence in three-layer polyethylene coatings, compromising cathodic protection and exposing the pipes to insidious corrosive processes.

In this context, it is vital to implement a responsible integrity strategy that includes sampling, visual inspections, and laboratory tests to ensure the durability and safety of stored pipes, particularly at a time when infrastructure expansion is crucial. This article explores the key challenges and solutions for maintaining the integrity of these pipes in prolonged storage situations.

Matching Anomalies from Different ILI Runs Using a Corrosion Prediction Algorithm

Corrosion is a significant challenge in the oil and gas industry, with important economic and environmental implications. To address this issue, an algorithm has been developed that uses Internal Line Inspection (ILI) data to predict corrosion rates accurately and efficiently. The approach is based on matching anomalies detected in multiple ILI inspections, utilizing geometric features and location data. This matrix-based approach improves accuracy and analysis times compared to traditional methods, which can lead to optimization in repair plans and cost reduction in the oil and gas industry.