The evaluation of logging data in shaly sand reservoirs can be a challenging task, particularly in the presence of accessory minerals such as glauconite. Accessory minerals affect the measurements of conventional logging tools, thus, introducing large uncertainties for estimated petrophysical properties and reservoir characterization. The application of traditional Gamma Ray and Density-Neutron crossover methods can become unreliable even for the simple objective of differentiating reservoir from non-reservoir zones. This was the situation for many years in the glauconite-rich Upper Bahariya formation, Western Desert, Egypt. Formation evaluation was challenging and the results often questionable. Adding Nuclear Magnetic Resonance (NMR) Logging While Drilling (LWD) data in three wells changed the situation radically. The NMR data unambiguously indicate pay zones and simplify the interpretation for accurate porosity and fluid saturation dramatically. Key to success is NMR total porosity being unaffected by the presence of accessory minerals. NMR moveable fluid directly points to the pay zones in the reservoir, while clay-bound and capillary-bound water volumes reflect variations in rock quality and lithology. Although the NMR total porosity is lithology independent, the presence of glauconite affects the NMR T2 distribution by shifting the water T2 response to shorter T2 times. This requires an adjustment of the T2 cutoff position for separating bound water from movable hydrocarbons. A varying T2 cutoff was computed by comparing NMR bound water to resistivity-based water saturation. The calibrated T2 cutoff exhibits an increase with depth indicating a decreasing amount of glauconite with depth throughout the Upper Bahariya formation. Based on these volumetrics, an improved NMR permeability log was calculated, now accurately delineating variations in rock quality throughout the different pay zones. In addition, viscosity was estimated from the oil NMR signal. The estimated values match the expected values very well and illustrate the potential of NMR to indicate viscosity variations. Many of these results are available today already in real-time by transmitting NMR T2 distributions to surface while drilling. Besides the application for formation evaluation, the data can be used to initiate optimized side-tracking and completion decisions directly after finishing the drilling operations.

Developing new interpretation methods in line with new technology measurements to improve reservoir characterization becomes a must to overcome the challenges that petrophysicists are facing on a daily basis, among others, thinly bedded reservoirs. The standard acoustic logs vertical resolution (VR) is oftentimes insufficient to resolve the Formation features. In the case of laminated thin beds (LTB), conventional petrophysical characterization has often delivered results, such as hydrocarbon saturation, affected by uncertainties. The main objective of this work is to develop a methodology, and to reliably integrate high-resolution acoustic processing outputs into the Formation evaluation (FE) routines, including the quality controls to identify and remove artifacts and ultimately enhance the accuracy of reservoir characterization. The approach used in this study is based on the high-resolution acoustic slowness analysis. The measurement standard VR of the acoustic array measurement is determined by the array aperture (the length of the receiver’s array section; generally 3.5 ft), which tends to obscure features that are thinner than the aperture length. The configuration of the highest resolution is 0.5 ft aperture subarray combination, which considers only two receiver levels in the subarray, i.e., single Rx-Rx spacing. The processing has limitations, inherent to physics; one of them is the "Validity condition". The high-resolution acoustic slowness methodology cannot be applied to acoustic waveform arrivals with very long wavelengths. The subarray aperture should be greater than a quarter wavelength of the wave being used. In addition, as increasing the resolution goes hand in hand with decreasing the number of waveforms, the signal-to-noise ratio decreases. There are several quality control and consistency check workflows to be introduced in this study, which will help in differentiating between the real high-resolution acoustic slowness data and any encountered processing artifacts. These analyses will enable the right evaluation strategy that will enhance the accuracy of FE. Examples highlighting the value of high-resolution acoustic processing/analysis for both carbonate and clastic reservoirs evaluation are provided in the paper. Finally, this approach will evaluate the potential added value to the FE of the heterogeneous reservoirs. We propose workflows in various Formations and borehole settings to demonstrate that with the aid of enhanced VR acoustic data, the log interpretation becomes more representative of the actual subsurface. The resulting sonic profiles show better consistency with other log responses of similar resolution. These workflows then can be used on a more regular basis, especially in complex situations.

Monitoring downhole drilling dynamics is an essential element to quality check the measurements provided in logging while drilling (LWD). LWD nuclear magnetic resonance (NMR) is sensitive to the motion induced from the bottom-hole assembly (BHA) during drilling, therefore, quantifying the motion effects becomes important to understand how to correct the measurements. Quantification and correction of lateral motion effects on NMR LWD are the objectives of this paper. Data was collected from various BHA combinations with LWD NMR to model the responses, which were compared with actual downhole conditions to assess the need for the lateral motion correction (LMC). Vibrational assessment criteria are utilized to assign a severity level, which dictates the level of the LMC. The LMC applies an algorithm to differentiate true formation signal responses from the vibration signal response. Specifically, the motion effect function was integrated into the forward matrix of the NMR joint inversion, and a nonlinear optimization algorithm was used to determine the four motion parameters, and if present, compensate for lateral motion effects. In wellbores with severe motion vibration there were large discrepancies between real-time and memory data, which resulted in mismatches with the measured partial porosities. Investigations were conducted on the BHA design, well trajectories, and wellbore environment to quantify the lateral motion effect on the NMR measurement. This information was then compiled to incorporate all aspects of BHA design techniques to mitigate the lateral motion effects on the NMR measurement. The LMC algorithm gives added confidence to ensure all data collected is consistent and reliable even in more challenging wellbore environments, which could be subjected to unanticipated lateral motion. This paper highlights an approach to integrate BHA simulation principles to anticipate severe motion effects during drilling. This knowledge, coupled with the LMC, creates a platform to enhance NMR data quality.

Carbonate reservoir complexity imposes some challenges in formation evaluation and characterization. Grain, pore, and throat size distributions play major roles in rock typing to understand static and dynamic behaviors of carbonate reservoirs. Special core analysis techniques, such as MICP and digital core imaging, revealed that the presence of different types of pore structures can be classified based on sizes as micro, meso and macro pores. This paper explores a unique inversion technique using nuclear magnetic resonance (NMR) data to deliver fast, accurate, and continuous pore typing across logged intervals. The traditional NMR data processing technique consists of sequential steps that ultimately convert echoes from time domain into T2 domain using an exponential inversion, also known as Laplace transform. NMR-gamma inversion (NMR-GI) workflow is a mathematical approach to process the NMR data using probabilistic functions. The gamma inversion function has a form of a bell curve with the base in the logarithmic x-axis. Unlike exponential inversion technique, this inversion produces multiple components. Each component is located at a particular time and it is labeled with a specific number, which reflects the T2 time stamp of each component. The individual area under each component is translated into porosity units. The application of gamma inversion in a T2 spectrum results in subcomponents via deconvolution of the original spectrum. The display of the components makes it easy to visually analyze and interpret the porosimetry for pore size distribution and group the components for pore typing. A deeper look into the different components of the T2 spectrums enlarges the NMR measurement portfolio by displaying the porosimetry and pore size distribution. The inverted T2 results from both logging while drilling (LWD) and wireline tools in different fields are consistent with the reservoir geological and petrophysical models. The added value of this technique can be tangible for geophysical and geological (G&G) applications as well as completion design optimization. The NMR-GI technique can be further utilized and calibrated to improve reservoir understanding and optimize advanced core analysis by providing a quick continuous carbonate pore and rock type log.