Economic development of unconventional resources relies heavily on the effectiveness of propped hydraulic fracture stimulation treatments (HFS or "fracs"). Non-stimulated and/or under-stimulated reservoir continues to be a critical industry concern. Mitigation is expensive and may require refracturing and/or additional wells to be drilled. Techniques to monitor and diagnose the geometry of HFS are limited and analysis typically has large uncertainties. This paper summarizes multiple datasets to demonstrate how complementary diagnostics significantly reduce uncertainties in their analysis, help to calibrate frac models and improve completion design of multi-stage wells. Diagnostics utilized in the datasets include: fiber optic distributed sensing (acoustic & temperature), non-radioactive tracers and production logs. We found that integrating these complementary diagnostics with other subsurface and well information not only confirmed that actual frac heights were different than intended in about half of the monitored stages, but also provided new insights that allow us to modify the HFS treatment design to better match the desired geometries. These diagnostics were used to history match and calibrate our frac models, allowing us to extrapolate results from the few wells with diagnostics to additional wells in the field. Statistics are also provided for the datasets including: percentages of perforation clusters and net sand treated to demonstrate the potential opportunity for improved stimulations and reserves recovery.

Borehole-log data acquisition accounts for a significant proportion of exploration, appraisal and field development costs. As part of Shell technical competitive scoping, there is an ambition to increase formation evaluation value of information by leveraging drilling and mudlogging data, which traditionally often used in petrophysical or reservoir modelling workflow. Often data acquisition and formation evaluation for the shallow hole sections (or overburden) are incomplete. Logging-while-drilling (LWD) and/or wireline log data coverage is restricted to mostly GR, RES and mud log information and the quality of the logs varied depending on the vendor companies or year of the acquisition. In addition, reservoir characterization logs typically covered only the final few thousand feet of the wellbore thus preventing a full quantitative petrophysical, geomechanical, geological correlation and geophysical modelling, which caused limited understanding of overburden sections in the drilled locations and geohazards risls assessment. Use of neural networks (NN) to predict logs is a well-known in Petrophysic discipline and has often used technology since more than last 10 years. However, the NN model seldon utilized the drilling and mudlogging data (due to lack of calibration and inconsistency) and up until now the industry usually used to predict a synthetic log or fill gaps in a log. With the collaboration between Shell and Quantico, the project team develops a plug-in based on a novel artificial intelligence (AI) logs workflow using neural-network to generate synthetic/AI logs from offset wells logs data, drilling and mudlogging data. The AI logs workflow is trialled in Shell Trinidad & Tobago and Gulf of Mexicooffshore fields. The results of this study indicate the neural network model provides data comparable to that from conventional logging tools over the study area. When comparing the resulting synthetic logs with measured logs, the range of variance is within the expected variance of repeat runs of a conventional logging tool. Cross plots of synthetic versus measured logs indicate a high density of points centralized about the one-to-one line, indicating a robust model with no systematic biases. The QLog approach provides several potential benefits. These include a common framework for producing DTC, DTS, NEU and RHOB logs in one pass from a standard set of drilling, LWD and survey parameters. Since this framework ties together drilling, formation evaluation and geophysical data, the artificial intelligence enhances and possibly enables other petrophysical/QI/rock property analysis that including seismic inversion, high resolution logs, log QC/editing, real-time LWD, drilling optimization and others.

In the current market, operational geology and geoscience asset teams have clear and aggressive financial reduction targets that need to be met without compromising the formation evaluation (FE) requirements of a well construction project. Advances in drilling and completion technologies and practices for deep-water wells commonly require operators to drill larger borehole sizes throughout the well construction process. For deep-water subsalt wellbores, this often implies exiting a thick salt layer with borehole deviation in borehole sizes ranging from 14.5 to 17.5 in. This paper introduces a unique 9.5-in. nominal collar size logging-while-drilling (LWD) density tool that makes it possible to address the FE challenges encountered in large borehole sizes. Any LWD method that can provide crucial cost-effective and accurate FE data can add value to well drilling and logging programs. The new tool provides density and photoelectric measurements in large-diameter boreholes. It also contains an ultrasonic sensor that can provide accurate borehole geometry information, which is useful for identifying stress-related breakout and providing accurate estimates of borehole volume for later placement of cement for zonal isolation. In such settings, formation density measurements are crucial for determining key evaluation parameters, such as porosity and rock mechanical properties, but acquisition of these measurements can be challenging using existing LWD technologies. In addition, real-time structural dip information for subsalt environments provides insight for the interpretation of the geological structure of the field but is often difficult to obtain in large-diameter boreholes. Several case studies demonstrate the value added by the new tool and its breadth of application, as well as the implications for pre-job analysis, bottom-hole assembly (BHA) modeling, data-acquisition procedures, sensor response analysis, and economic benefits to the operator. The capability of acquiring logging data for interpretation purposes and to fulfill specific regulatory requirements without negatively affecting the drilling program provides a desirable cost-management opportunity. The results presented here provide a reference for appropriate business cases to help justify the use of this unique LWD technology in drilling and logging projects involving large-diameter boreholes.

Hydrocarbon reservoirs with a large column height as well as tight gas rocks require a large range of capillary pressures to describe the saturation of fluids present in these formations. While mercury injection capillary pressure (MICP) can achieve high equivalent capillary pressures, the tests are destructive to the core plugs. Centrifuge techniques have gained in popularity since they are faster than the porous plate technique, but they are limited in the achievable pressure range. Here, we propose the use of fluorinated oils to extend the achievable capillary pressure of the air-brine centrifuge technique by a factor of two. We use Fluorinert FC-70 in an inverted bucket configuration which doubles the radius of rotation and keeps the density contrast comparable to an air-brine system. Furthermore, we show the application to NMR T2 cutoff determination as a function of capillary pressure. Since Fluorinert does not contain any hydrogen, there is no signal overlapping with the brine in the core plugs. Furthermore, in the inverted bucket configuration, the outlet face of the plug is not in contact with a drainage surface so that the Hassler-Brunner boundary condition of Pc = 0 is satisfied. Additionally, the method allows the storage under a liquid Fluorinert phase, which prevents evaporation and significantly extends the available time for NMR measurements at low water saturations.

Evaluation of cement placement is an important part of the majority of deepwater wells. Cement placement confirmation is an important step following a cementing operation. More than one technique can be used to provide information about the top of cement (TOC) and about the depth interval of a good bond between the formation and the casing. Determining the length of annular cement coverage, which is an indication of correct cement placement, is useful knowledge before drilling and/or completion operations can proceed. The requirement for additional and improved cement evaluation techniques is greater now than ever before. A variety of methods can be used to evaluate cement placement. The routine approach after a casing or liner cement job uses a job chart to calculate lift pressure and actual vs. predicted system pressure. These data enable an estimate of cement height in the annulus to be made, but they do not confirm the TOC. These methods vary in accuracy and difficulty, depending on well conditions. Common TOC evaluation methods in specific wellbore casing/liner sections typically require running a temperature survey or cement bond log (CBL) sensors/systems on a wireline. These operations use the rig's critical path time for each wireline run, which can add risk or difficulties, depending on the well trajectory. In addition, cement bond evaluation for large diameter casing can be technically challenging because it can reach the upper threshold measurement limitations for conventional wireline-conveyed CBL tools. Many operators now use logging-while-drilling (LWD) sonic sensors for compressional and shear data acquisition in openhole environments. Using the same sonic systems, with minimal additional rig time, logging data acquired through the casing/liner strings while running a drilling or clean out assembly can be evaluated to confirm the TOC. This paper demonstrates how LWD sonic technology can provide confirmation of the TOC, saving a considerable amount of rig time, as compared to performing a dedicated wireline evaluation run or potentially unnecessary cement squeeze operations. The paper presents and discusses Gulf of Mexico (GOM) case studies. Based on various specific challenges, through correct data analysis, TOC evaluation best practices are implemented to optimize the LWD acoustic data acquisition inside the casing/liner. New data examination techniques are reviewed that can be applied to different scenarios, such as TOC evaluation behind dual pipes and real-time assessment for quick data analysis turn-around. In conjunction with the case studies, the paper also provides information about the LWD cased-hole logging techniques, analysis, and results of the data application.