Using logging while drilling resistivity imaging data to quantitatively evaluate fracture aperture based on numerical simulation

ABSTRACT Fractured formations are strongly heterogenous, and thus exhibit a complex logging response mechanism. By using the logging while drilling (LWD) resistivity imaging tool, fractures can be visually identified and their aperture quantitatively calculated. Because physical fracture model simulation is time consuming and costly, we propose using a 3D finite element method (FEM) numerical simulation to interpret the LWD resistivity imaging tool logging responses in conjunction with a new aperture calculation model based on the forward model. First, we used the single fracture model to investigate the effect of fracture aperture and formation resistivity contrast on the maximum current contrast at the fracture. The results showed that the aperture is linearly related to the maximum current contrast, while the formation resistivity contrast exhibits a pronounced exponential relationship with the maximum current contrast. Both of these relationships are affected by the fracture's dip angle, so segmented fitting is required when the fracture dip angles differ. Next, using the forward model, we developed the fracture aperture calculation model based on the maximum current contrast. The aperture calculation model was established in three segments in accordance with the different fracture dips, and the influence factors affecting the fracture inverting inclination were analyzed using multi-fracture simulation images. Finally, the accuracy of the new model was verified with the simulated fracture images. The novel model for calculating fracture aperture is of great significance for processing and interpreting LWD resistivity imaging logging data.

REAL-TIME 2.5D INVERSION OF LWD RESISTIVITY MEASUREMENTS USING DEEP LEARNING FOR GEOSTEERING APPLICATIONS ACROSS FAULTED FORMATIONS

We develop a Deep Learning (DL) inversion method for the interpretation of 2.5-dimensional (2.5D) borehole resistivity measurements that requires negligible online computational costs. The method is successfully verified with the inversion of triaxial LWD resistivity measurements acquired across faulted and anisotropic formations. Our DL inversion workflow employs four independent DL architectures. The first one identifies the type of geological structure among several predefined types. Subsequently, the second, third, and fourth architectures estimate the corresponding spatial resistivity distributions that are parameterized (1) without the crossings of bed boundaries or fault plane, (2) with the crossing of a bed boundary but without the crossing of a fault plane, and (3) with the crossing of the fault plane, respectively. Each DL architecture employs convolutional layers and is trained with synthetic data obtained from an accurate high-order, mesh-adaptive finite-element forward numerical simulator. Numerical results confirm the importance of using multi-component resistivity measurements -specifically cross-coupling resistivity components- for the successful reconstruction of 2.5D resistivity distributions adjacent to the well trajectory. The feasibility and effectiveness of the developed inversion workflow is assessed with two synthetic examples inspired by actual field measurements. Results confirm that the proposed DL method successfully reconstructs 2.5D resistivity distributions, location and dip angles of bed boundaries, and the location of the fault plane, and is therefore reliable for real-time well geosteering applications.

On the depth of detection of logging-while-drilling resistivity measurements for looking-around and looking-ahead applications

The depth of detection (DOD), which is an important concept in logging data interpretation, describes the detection capability of the borehole measurements. We have extended the definition of DOD for azimuthal information, namely, the geosignal delivered by azimuthal resistivity tools, to resistivity logs in logging-while-drilling (LWD) applications. Instead of using the radial geometric factor, the detection thresholds in predicting a geologic boundary are used to describe the DOD of a measurement. This definition unifies the criteria to evaluate the detectability of different borehole measurements, such as LWD resistivity measurements and geosignals. It also can be generalized to other kinds of well logging methods in LWD applications. Using the proposed definition, we analyze the detection capability of the LWD resistivity measurements in looking-around and looking-ahead applications; they provide more tangible descriptions. In vertical or near-vertical wells, the definition provides an indicator to evaluate the capability and reliability of looking ahead of deep/ultradeep LWD resistivity tools. The investigations on the influence of the DOD on the distance-to-boundary inversion, which can help in developing a robust and accurate inversion scheme, also are presented and discussed.