A Novel Determining Borehole Fluid Density and Imaging Method Using X-ray Source

The wellbore's integrity can be compromised due to tool deformation and the fall of downhole fish, resulting in blockages. In order to guarantee the secure and effective restoration of a malfunctioning wellbore, it is essential that the wellbore must be the initial investigation during the repair procedure. Although the introduction of well visualization techniques such as ultrasonic imaging and downhole television has greatly reduced the risk of well intervention, the imaging capabilities of these techniques are still limited when the fluid is unknown and opaque. This presents a new challenge when it comes to completing downhole probes in a safe, efficient, and cost-effective manner. Historically, the high penetration and interaction between X-rays and matter have been used to image objects in fluids, but there have been few studies on imaging response theory and correction methods for imaging. In this study, the photon transport theory of downhole X-ray front-view imaging is proposed to address the poor understanding of the mechanism and influencing factors. To overcome the difficulties in quantifying the influencing factors, the correction method of the X-ray flux distribution-fluid layer thickness mapping library is proposed according to the photon transport theory, which enables the adaptive response correction of the mapping library to the fluid parameter in the imaging inversion. The X-ray flux distribution is recorded using a detection system consisting of a matrix detector, an imaging aperture, and an X-ray source. Irrational structural parameters and fluid corrections affect the X-ray flux distribution response to water layer thickness, leading to inverse imaging failures, with single Compton scattering contributing more than 90%. Therefore, it is essential to develop the photon transport theory for forward-looking imaging, which is the basis for the detection parameters of fluid and the correction method, in order to provide theoretical support for the design of the device structure. In this paper, mathematical expressions are derived to quantify the effect of instrumental parameters on the X-ray flux distribution, and the patterns of forward data response are consistent with the theoretical response form. To realize the measurement of fluid parameters and adaptive correction imaging, a parameters identification method and response library correction method are proposed, while scattering theory shows that the effect of fluid parameters is mainly related to the attenuation coefficient. Simulation results indicate the efficacy of the method in identifying fluid density in cased wells and adapting image libraries with over 99.8% confidence. Additionally, effective detection distances of 10 cm and 1 mm image inversion resolution were achieved.