Abstract: A method for well integrity assessment using machine-trained prediction of physical characteristics related to well integrity across a depth interval of a cased wellbore having one or more casing strings. The method includes collecting scattered X-ray signals from a plurality of X-ray detectors arranged within a well logging tool, learning trained weights to predict wellbore characteristics from the scattered X-ray signals, collecting further scattered X-ray signals from the X-ray detectors, using the trained weights to quantitatively predict the wellbore characteristics from the further X-ray signals, and using the predicted wellbore characteristics to assess well integrity.

Abstract: The complement system is part of the innate immune system and is highly regulated by regulatory proteins belonging to the Regulators of Complement Activation (RCA) family. It is known that lack of regulation causes damage to host cells and deficiencies in the regulation is also linked to diseases such as age-related macular degeneration, atypical hemolytic uremic syndrome, and dense deposit disease. The regulatory proteins primarily include decay-accelerating factor (DAF; CD55), membrane cofactor protein (MCP; CD46), complement receptor 1 (CR1; CD35), factor H (FH) and C4b-binding protein (C4BP). Structurally, these proteins are composed of repeating complement control protein (CCP) domains where 2-4 successive domains contribute to the regulatory functions termed as decay-accelerating activity (DAA) and cofactor activity (CFA). However, no four-domain chimeric protein currently exists having both strong DAA (CP-DAA and AP-DAA) and strong CFA (C3b-CFA and C4b-CFA). Therefore, chimeric protein DCP (i.e.

Abstract: A method for well integrity assessment using machine-trained prediction of physical characteristics related to well integrity across a depth interval of a cased wellbore having one or more casing strings. The method includes collecting scattered X-ray signals from a plurality of X-ray detectors arranged within a well logging tool, learning trained weights to predict wellbore characteristics from the scattered X-ray signals, collecting further scattered X-ray signals from the X-ray detectors, using the trained weights to quantitatively predict the wellbore characteristics from the further X-ray signals, and using the predicted wellbore characteristics to assess well integrity.