This paper demonstrates the advantages and replicability of utilizing Distributed Fiber Optic Sensing (DFOS) combined with LYTT's customary machine learning, signal processing and interpretation tools in downhole oil and gas operations.
Paper Number: SPWLA-2022-0016
This paper describes a Middle East case study in which the challenge of big data generated by distributed fiber optic well monitoring systems was addressed through the use of LYTT’s sensing and analytics platform. The platform conducted intelligent feature extraction and enabled data to be streamed, processed, stored and visualized in real-time.
Paper Number: SPE-207848-MS
This paper demonstrates an innovative approach to processing Distributed Fiber Optic Sensing (DFOS) deployed to a gas condensate well.
Paper number: SPE-205435-MS
The paper describes the case of a critical injection North Sea well that developed sustained casing pressure in the B-annulus and required an investigation to understand the leak origin.
Paper Number: OTC-30930-MS
In the case study outlined in this paper, an innovative cloud-based injection monitoring application is deployed that uses DAS and DTS and overlays physics-informed machine learning models to deliver real-time visibility.
Paper Number: OTC-30982-MS
In the case study outlined in this paper, the oil production rate was increased by 25% using a predictive pressure optimization workflow to minimize sand production in a horizontal, sand prone well.
Paper Number: SPWLA-2021-0001
This paper summarizes the main findings from the first successful deployment of a continuous multiphase inflow profiling application that uses innovative signal processing techniques and machine learning that leverage distributed fiber optic data to identify the phase and rate of the inflow along the wellbore during production
Paper Number: SPE-201543-MS
The paper describes a case study of a well where persistent sustained casing pressure (SCP) in the A-annulus resulted in the well being shut in for a period of almost three years.
Paper Number: SPE-204450-MS
Within a comprehensive overview of the evolution of downhole surveillance in the customer's field, DAS sand detection is discussed as a new, real-time downhole sand monitoring technology.
Paper Number: SPWLA-2018-V59N4A6
DAS sand detection surveillance in the customer's field delivers substantial production and safety benefits.
Paper Number: SPE-188991-MS
A new DAS solution identifies real-time downhole sand ingress locations across a reservoir.
Paper Number: SPE-183329-MS
This paper describes the application of fiber optic technology to identify and differentiate multiple downhole well integrity events such as tubing leaks, casing leaks, flow behind casing and overburden integrity.
Paper Number: SPE-203447-MS