Enhanced Well Remedial Decisions from Exact Location of Fluid Movement Behind Casing Identification


Authors

Marcel Croon (Weatherford) | Perry Huber (Weatherford) | Jacob Wright (Weatherford)

Publisher

SPE - Society of Petroleum Engineers

Publication Date

November 11, 2019

Source

Abu Dhabi International Petroleum Exhibition & Conference, 11-14 November, Abu Dhabi, UAE

Paper ID

SPE-197560-MS


Abstract

Historically, acoustic wellbore monitoring is one of the main methods of detecting fluid movement behind the casing. Analysis of the complex acoustic environment in the wellbore can be challenging. A standard hydrophone noise tool is unable to measure flow directions (vertical and horizontal) and cannot detect low flow, low pressure sporadic events or multiple sources. This uncertainty may result in subjective acoustic interpretation leading to poor advice on remedial actions for wells with well integrity issues. A geophone array, including four 3-component geophones deployed via Wireline, provides a solution for this problem by creating a three-dimensional map of the acoustic environment. This acoustic profile, with accurately measured background noise levels throughout the length of the well, is then analyzed to confirm source locations and presence of flow (gas / oil / water) behind casing. The Unique geophone array configuration has allowed us to confirm source locations and flow paths of unwanted fluid flow for hundreds of conventional and unconventional production wells. Scenarios include wells with surface-casing or annular vent-flow issues, multiple source vent-flow situations, wells with cross flow between zones and integrity confirmation for gas storage caverns / zones. Since the detected flow is rendered into horizontal and vertical components, we can determine flow direction and accurately pin-point depth levels of fluid entry from the formation into the wellbore annulus. Geophone array noise logging has occurred in approximately 500 wells globally and the success rate for first attempt repairs is about 80% which is significantly higher than the typical 30% success rate.