Abstract The pre-salt carbonates of Brazil pose drilling and characterization challenges associated with inherent reservoir heterogeneity; and borehole imaging while drilling often provides insights helpful for both, operational and subsequent decisions. The findings and learnings from a 3-well campaign, offshore Brazil are presented to assess and validate a recently deployed high-definition borehole imaging technology that provides industry’s first real-time ultrasonic amplitude images and time-to-depth corrections for best possible images maintaining the geological features integrity. High-definition ultrasonic measurements were acquired at two central frequencies with 0.2-in resolution and provided amplitude and transit time images for geological characterization and petrophysical evaluation in addition to azimuthal ultrasonic calipers. The lossy nature of amplitude data makes it difficult to transmit in real-time; therefore, a unique data compression technology was used to achieve industry’s first high quality amplitude images streaming while drilling. In deepwater operations acquisition of high-definition logging while drilling (LWD) images can be severely degraded if time-to-depth offset due to heave is not compensated. Recently developed heave-filtering workflows ensured the integrity of subsurface features. The time-indexed data was processed with this application in real-time, providing good results and confidence in the capability of this technology. Image-logs of the first well were helpful in interpretation and added value to the reservoir understanding; however, many intervals suffered from lack of confidence in image features. Simulations were performed to improve the images acquisition parameters based on learnings from this experience. New optimized operational parameters were applied in next two wells, resulting in image logs of excellent quality. Data from second well suffered from high heave while drilling, which required implementation of the heave-filtering memory data workflow. For the third well, an additional requirement for real-time image quality-control was defined, requiring data to be processed after every drill-stand. Real-time data quality provided confidence in optimal quality of memory data, thereby eliminating the need of post-drilling wireline operations in open-hole. The images acquired in memory helped characterize intervals of stromatolites with various morphology, and zones of vugs distribution, providing excellent alternative for wireline logging, de-risking the operations in pre-salt carbonate logging in Brazil offshore operations.

Abstract Logging while drilling (LWD) ultrasonic imaging tools have been recently introduced for slim hole size. Due to fundamental differences in data acquisition methodologies with other previously utilized LWD and wireline imaging techniques, field trials have been performed with the objective of validating and evaluating the new ultrasonic tool’s measurement. Ultrasonic imagers have been deployed in multiple wells of different environments and formation characteristics to evaluate the tool’s measurement quality and potential applications. The trials were performed in carbonate and clastic formations, horizontal and vertical trajectories, oil- and water-based drilling fluid systems, and in drilling and wipe operations. An LWD ultrasonic imager has also been deployed back to back with wireline. Multiple passes were performed to evaluate the time dependency and hole deterioration effect. In water-based mud, an ultrasonic imaging tool was run in the same bottomhole assembly with the proven LWD laterolog resistivity imager for the comparison of both technologies. In addition to stratigraphic dips, bed boundaries, fractures, faults, and other geological features usually detected by other imaging techniques, ultrasonic imaging tools also provided high measurement sensitivity for detecting geometric features relating to wellbore shape and wellbore stability. LWD microresistivity-based image comparisons indicated a robust correlation of the fractured zones contributing to lost circulation while drilling. Multiple passes for drilling and wipe images with wireline comparisons logged days after the LWD run clearly illustrated the time-dependency of the image quality due to borehole deterioration, invasion, and progression of geomechanical effects used to benchmark future data acquisition requirements. This paper evaluates the capabilities and performance of ultrasonic imaging tools in comparison with other LWD and wireline high-resolution imaging sensors.

Abstract Faulting is one type of structural trap for hydrocarbon reservoirs. With more and more fields moving toward the brownfield or mature operations stage of life, the opportunity to target bypassed or attic oil in the vicinity of bounding fault(s) is becoming more and more attractive to operators. However, without an effective logging-while-drilling (LWD) tool to locate and map a fault parallel to the well trajectory, it has been challenging and potentially high risk to optimally place a well to drain oil reserves near the fault. Operators often plan these horizontal wells at a significant distance away from the mapped fault position to avoid impacts to the well construction and production of the well. Often, the interpreted fault position, based on seismic data, can have significant lateral uncertainty, and uncertainties attached to standard well survey measurements make it challenging to place the well near the fault. This often results in the wells being placed much farther from the fault than expected, which is not optimal for maximizing recovery. In other cases, due to uncertainty in the location of the fault, the wells would accidentally penetrate the side faults and cause drilling and other issues. Conventional remote boundary detection LWD tools do not assist with locating the fault position, as they only detect formation boundaries above or below the trajectory and not to the side. In this paper, the authors propose a novel approach for mapping features like a fault parallel to the well trajectory, which was previously impossible to map accurately. This new approach utilizes a new class of deep directional resistivity measurements acquired by a reservoir mapping-while-drilling tool. The deep directional resistivity measurements are input to a newly devised inversion algorithm, resulting in high-resolution reservoir mapping on the transverse plane, which is perpendicular to the well path. These new measurements have a strong sensitivity to resistivity in contrast to the sides of the wellbore, making them suitable for side fault detection. The new inversion in the transverse plane is not limited to detecting a side fault; it can also map any feature on the transverse plane to the well path, which further broadens the application of this technology. Using the deep directional resistivity data acquired from a horizontal ultra-ERD well recently drilled in the Wandoo Field offshore Western Australia, the authors tested this approach against the well results and existing control wells. Excellent mapping of the main side fault up to 30 m to the side of the well was achieved with the new approach. Furthermore, the inversion reveals other interesting features like lateral formation thickness variations and the casing of a nearby well. In addition, the methodology of utilizing this new approach for guiding geosteering parallel to side fault in real time is elaborated, and the future applications are discussed.

Abstract Siliciclastic turbidite lobes and channels are known to exhibit varying degrees of architectural complexity. Understanding the elements that contribute to this complexity is the key to optimizing drilling targets, completions designs and long-term production. Several methods for 3D reservoir modelling based on seismic and electromagnetic (EM) data are available that are often complemented with outcrop, core and well log data studies. This paper explores an ultra-deep 3D EM inversion process during real-time drilling and how it can enhance the reservoir understanding beyond the existing approaches. The new generation of ultra-deep triaxial EM logging tools provide full-tensor, multi-component data with large depths of detection, allowing a range of geophysical inversion processing techniques to be implemented. A Gauss-Newton-based 3D inversion using semi-structured meshing was adapted to support real-time inversion of ultra-deep EM data while drilling. This 3D processing methodology provides more accurate imaging of the 3D architectural elements of the reservoir compared to earlier independent up-down, right-left imaging using 1D and 2D processing methods. This technology was trialed in multiple wells in the Heimdal Formation, a siliciclastic Palaeocene reservoir in the North Sea. The Heimdal Fm. sandstones are generally considered to be of excellent reservoir quality, deposited through many turbiditic pulses of variable energy. The presence of thin intra-reservoir shales, fine-grained sands, heterolithic zones and calcite-cemented intervals add architectural complexity to the reservoir and subsequently impacts the fluid flow within the sands. These features are responsible for heterogeneities that create tortuosity in the reservoir. When combined with more than a decade of production, they have caused significant localized movement of oil-water and gas-oil contacts. Ultra-deep 3D EM measurements have sensitivity to both rock and fluid properties within the EM field volume. They can, therefore, be applied to mapping both the internal reservoir structure and the oil-water contacts in the field. The enhanced imaging provided by the 3D inversion technology has allowed the interpretation of what appears to be laterally stacked turbidite channel fill deposits within a cross-axial amalgamated reservoir section. Accurate imaging of these elements has provided strong evidence of this depositional mechanism for the first time and added structural control in an area with little or no seismic signal.

Abstract The objective of this paper is to provide a context for strategic use of fluid sampling while drilling (FSWD) in the deep-water environment. Our work is based on data collected from Gulf of Mexico wells over the last 7 years and we incorporate both operator and service company experience. In this paper we review the current FSWD technology and the quality of the fluid samples. We provide practical guidelines for executing the FSWD operation and review types of wells where FSWD has been most effective. We also discuss the role FSWD plays in the business of efficient well construction (drilling, evaluating, and completing). Strategic use of FSWD can provide time savings and operational risk mitigation. FSWD has proven to provide high quality data and fluid samples, however, an awareness of the differences between conventional fluid sampling (wireline) and sampling while-drilling is important for maximizing benefits. Additionally, long term strategic commitment to FSWD is likely to provide the largest benefits to operators. FSWD has been around for about 10 years, but how, and where, to apply the technology has not been clear to many operators. The broader industry can benefit by learning from experiences accumulated through consistent and extensive FSWD use in deep-water wells showing how the technology has progressed, and how it is used to achieve business benefits.

Abstract Recently the drilling industry has seen many advances in the application of deep directional electromagnetic (EM) measurements for mapping deeper into the reservoir, with the latest one capable of seeing over 250 ft above and below the wellbore providing unprecedented understanding of the reservoir. This measurement technology is now being used to look ahead of bit while drilling, for exploration wells to reduce drilling risks associated with unexpectedly penetrating certain formation. With the increasing complexity of the reservoirs that the industry is targeting, there is more and more quest for expanding the reservoir mapping capability, not just a 1D approach that can only map resistive boundaries on the vertical axis or near vertical axis and assume infinite extend in all other directions, but to enable geoscientists to better steer the well and better understand the reservoir structure and fluid contact in a full three-dimensional context around the wellbore. In this communication, the authors introduce a new solution to this quest for full three-dimensional real-time reservoir mapping. The solution is composed of three parts: a set of new measurements acquired downhole and transmitted to surface in real-time, a new inversion algorithm that is model independent and therefore fit for any reservoir complexity, and a new computing paradigm that make it possible to provide answers in real-time while drilling. The new set of measurements almost doubles the number of well logs that were acquired before and greatly enriches formations evaluation around the wellbore. The new algorithm, different from all previous algorithms, is not confined to any specific forms of models, making it suitable for exploring and finding solutions in complex reservoir settings. Finally, taking advantage of the latest advances in the Cloud computing, turnaround time of the new inversion is improved by over hundred times, thanks to the scalability of the algorithm design and Cloud computing infrastructure. Combining all these together allows to achieve three-dimensional reservoir map, without having to tradeoff between high resolution and depth of investigation. The 3D reservoir map that is generated from multiple transverse 2D inversion slices in real-time, enables timely update of reservoir model as drilling progress for the operator to make informed decisions. This new technology is currently deployed in several locations around the world and in different environments. In this paper, the authors review deployment results, to illustrate the technology, from preparation to real-time execution, and finally to post-job model update. With the ability of mapping in all directions while drilling, this technology opens the door to many applications and will enable the operators to target more complex reservoirs and achieving better geosteering results where 3D mapping and steering are required. In addition to its benefits for real-time operations, the technology also enables the geoscientists to update and calibrate their reservoir models with fine and accurate details, which can further benefit multiple disciplines including drilling, completion, production and reservoir management.

Abstract Mature fields contain wells drilled over decades, resulting in a complex distribution of cased hole from active producers, injectors, and abandoned wells. Continued field development requires access to bypassed pay and the drilling of new wells that must be threaded between the existing subterranean infrastructure. It is therefore important to know the position of any offset wells relative to a well being drilled so collision can be avoided. A well’s position is determined by directional survey points, for which the measurement error accumulates along the length of the well, increasing the uncertainty associated with the well position. The positional uncertainty is greater in wells drilled with older generations of surveying tools. Thus, a new well may be required to enter the ellipse of uncertainty representing the potential position of an older well, risking collision, to be able to reach desired targets in more distal parts of the reservoir. A potential solution to reduce collision risks is ultra-deep electromagnetic (EM) logging-while-drilling (LWD) tools, whose measurements are strongly influenced by proximity to metal casing and liners. This paper presents 3D inversion results of ultra-deep EM data from a development well in a mature field, which were used to identify a nearby cased well. Due to the large effect of casing on the measured EM field, it is important to validate the 3D results; this has been achieved using a synthetic modelling approach and assessment of azimuthal EM measurements. Models were created with casing positioned within resistive media with similar properties to those seen in the studied cases. Inverting these models allows testing of the inversion algorithm to show that it is providing a good representation of the cased well’s position relative to the newly drilled well. Further analysis of recorded and synthetic data showed that the raw EM field is strongly influenced as the casing is approached. The casing can be seen to clearly affect the EM field measurements when it is in the region of 10 to 15 m ahead of the EM transmitter, with the effect increasing in magnitude as this distance diminishes. Modelling shows that the EM field measurements behave in a predictable manner. As the ultra-deep EM tool approaches a cased well, it is possible to determine whether the casing is above, below, or critically, directly in line with the planned trajectory of the new well. Existing subterranean infrastructure can pose a major hazard to the drilling of new wells. Being able to identify an old well ahead of the bit using ultra-deep EM measurements would allow a new well to be steered away from the hazard or drilling stopped, preventing a collision. In addition, this may also allow the drilling of well paths that would otherwise be impossible to drill, due to the limitations imposed by positional uncertainty of the new and offset wells. This use of ultra-deep resistivity technology takes it beyond its more traditional benefits in well placement and formation evaluation, making it useful for improving well drilling safety.

Abstract Borehole Imaging technology is often key for reservoir characterization and becomes more relevant when images are acquired while drilling to capture reservoir geology and petrophysical property distributions around the borehole. Logging While Drilling (LWD) high-resolution electrical/acoustics images of the borehole can resolve formation layers and heterogeneity down to 5mm (0.2in) scale and can detect response from far smaller features. This allows both, improved operational efficiency and better-informed drilling as well as shortening of the geological interpretation turn-around time from wireline logging time (days after drilling) to semi-real time (drilling time or hours after drilling). LWD high resolution images often suffer from the lack of direct downhole velocity measurements against the sensors. Depth tracking is on surface, referenced to the surface block movement. The imaging sensor acquiring data can be thousands of feet away from this surface reference. Imaging sensors on the bottom-hole assembly (BHA) are located not too far away from the drill bit. They are also subject to complex drilling-time motion such as tool whirling, stick and slip, vibration, mode coupling etc. This can make the downhole sensor movement dis-synchronized with the surface pipe depth increment. The Time-Depth conversion may accordingly get dis-synchronized to generate LWD depth image with missing features and distorted feature-integrity in depth. In severe conditions distorted image impacts real time image feature interpretation and leads to increased interpretation uncertainties. In this paper we investigate two main dissynchronization problems using synthetic data: heave effect and BHA stick and slip effect. Pseudo velocity is computed from the surface measurement due to the lack of downhole sensor velocity direct measurement. In order to minimize heave effect, an advanced band-pass filter is proposed. The filter order is chosen in consistency with the sensor’s pseudo velocity behavior. Other properties of this advanced filter are also presented. In order to minimize the BHA stick and slip effect, pseudo velocity is analyzed as a delayed and minimized representative of the downhole sensor movement. A windowed-thresholding method is proposed to restore the compressed and stretched image features. Dip error analysis is performed by picking bed and fracture surface on the synthetic image data, before and after image distortion correction. The analysis results show a non-negligible effect on the accuracy of the true dip computed if the distortions are left un-corrected. Even in favorable logging conditions, the apparent dip error can contribute up to 50% of the total error. In this case, the image post-processing method proposed in this paper can not only improve the image quality but also reduce image interpretation uncertainties.

Abstract During a drilling operation, rock cuttings are often sampled off a shale shaker for lithology and petrophysical characterization. These analyses play an important role in describing the subsurface; and it is important that the depth origin of the cuttings be accurately determined. Traditionally, mud-loggers determine the depth origin of the sampled cuttings by calculating the lag time required for the cuttings to travel from the bit to the surface. These calculations, however, can contain inaccuracies in the depth correlation due to the shuffling and settling of cuttings as they travel with drilling fluid to the surface, due to unplanned conditions like drilling an overgauge hole, and due to other unforeseen drilling events, especially critical in horizontal sections. We therefore aimed to remedy these inaccuracies by developing a series of styrene-based nanoparticles that tagged the cuttings as they were generated at the drillbit. These “NanoTags” were tested while drilling in Q4, 2019; and the results indicated that the NanoTags did in fact have the potential to identify some systematic errors compared with traditional mud logging calculations.

Abstract Spectral gamma-ray (SGR) data were acquired from a new slim logging-while-drilling (LWD) tool and from surface cuttings in a near vertical well and in a horizontal well across clastic deposits. Comparison of the data from both measurements indicates that there are advantages from both methods. X-ray diffraction (XRD) and X-ray fluorescence (XRF) data from cuttings also support the findings. The formation evaluation objective is to quantify the volumes of each mineral and fluid present in the formation. SGR data brings the required additional information to reduce the mineral volume uncertainty, especially for the clays in the formation with complex mineral assemblages. In the studied clastic deposits, several clay types are present (with the dominant contribution from illite and kaolinite) together with feldspars and trace elements like zircon and other heavy minerals. The presence of gas introduces another unknown, since it affects the porosity measurements and fluid volume calculation through bulk density and neutron porosity. The comparison of SGR data from LWD logs and from cuttings brings robustness to our conclusions. Comparison of the thorium, potassium, and uranium concentrations from LWD logs and from cuttings shows good agreement in the measurements for the low-angle well. The high-angle well data also shows good agreement between the two measurements except for the cleaner sand section. The results from the cuttings are affected by the accuracy of sample depth control due to the poor borehole conditions and inefficiency in evacuating cuttings in high-angle wells compared to low-angle wells. The trend of the SGR is maintained. The LWD SGR elemental concentrations are then used to solve the formation mineral fractions, which are compared with the same fractions from the XRD on cuttings. Similar conclusions are drawn for the elemental concentrations. The potassium concentration enables the quantification of illite and potassium feldspar. Uranium brings a significant contribution to the total GR measurement, which could lead to a clay volume overestimation if the uranium contributions weren’t excluded. In conclusion, LWD provides superior quality SGR data compared with SGR from cuttings because of the better depth control and vertical resolution. SGR on cuttings can be an alternative when combined with other LWD measurements and accepting a higher uncertainty, in case LWD SGR cannot be run due to certain borehole conditions. This paper compares the results of a slim tool LWD and cuttings SGR data for the first time and concludes on the applicability of each technique.

Abstract The first Eni geosteering operation in Mexico was executed during the global COVID-19 crisis. The complex geology and the uncertainty related to this undrilled portion of the reservoir determined the employment of advanced Logging While Drilling (LWD) technology for real-time geosteering and a comprehensive geological interpretation. The target is an oil bearing sandstone reservoir, represented by deltaic front sands bars within an anticline structure on a salt core with faults and lateral heterogeneity. A sedimentological conceptual model was used to feed the 3D geological model, supporting a development strategy based on the geosteering of a horizontal well. The trajectory was designed within the best petrophysical properties interval to maximize production. The pre-drill risk analysis determined the need for a pilot hole to confirm structural setting, reservoir properties and fluid contacts to mitigate the associated uncertainties. The landing data acquisition strategy included standard LWD measurements and density images to optimize the wellbore inclination. The drain section was going to be geosteered with an Ultra-Deep Azimuthal Electromagnetic tool, dual-physics imager for oil-based mud systems and sourceless Density/Neutron technology. The pilot hole confirmed the pre-drill expected scenario but the LWD images and data interpreted while landing, revealed a more complex than expected target reservoir architecture. The detailed geological picture was completed while drilling the drain section. The multi-scale data (Reservoir Mapping information, Resistivity images, Logs, Seismic Interpretation and Pressure points) were integrated and exchanged 24/7 by experts through a commercial hub for team collaboration. A communication and information sharing protocol was customized to overcome the restrictions dictated by COVID-19 health emergency. The combination of acquired information and knowledge, unveiled a reservoir made of stacked clinoforms with internal geometries non-conformable with the general structural trend. Real-time geosteering with advanced technologies information, mitigated the impact of the unexpected complex subsurface setting. A total of 270 m were drilled inside the target, maximizing the drilled Net-to-Gross compared with the planned trajectory. Furthermore, the geological scenario reconstructed with multiscale LWD data, was exploited for a detailed 3D reservoir model update.

Abstract Most conventional log interpretation technics use the radial model, which was developed for vertical wells and work well in them. But applying this model to horizontal wells can result in false conclusions. The reasons for this are property changes in vertical direction and different depth of investigation (DOI) of logging tools. DOI area probably can include a response from different layers with different properties. All of this complicates petrophysical modeling. The 3D approach for high angle well evaluation (HAWE) is forward modeling in 3D. For this modeling, it is necessary to identify the geological concept near the horizontal well section using multiscale data. The accuracy of modeling depends on the details of the accepted geological model based on the data of borehole images, logs, geosteering inversion, and seismic data. 3D modeling can be applied to improve the accuracy of reservoir characterization, well placement, and completion. The radial model is often useless for HAWE because LWD tools have different DOI and the invasion zone was not formed. But the difference between volumetric and azimuthal measurements is important for comprehensive interpretation because various formations have different properties in vertical directions. Resistivity tools have the biggest DOI. It is important to understand and be able to determine the reason for changes in log response: a change in the properties of the current layer or approaching the layers with other properties. For this, it is necessary to know the distance to the boundaries of formations with various properties and, therefore, to understand the geological structure of the discovered deposits, and such information on the scale of well logs can be obtained either by modeling or by using extra deep resistivity inversion (mapping). The largest amount of multidisciplinary information is needed for modeling purposes - from images and logs to mapping and seismic data. Case studies include successful examples from Western Siberia clastic formations. In frame of the cases, different tasks have been solved: developed geological concept, updated petrophysical properties for STOIIP and completion, and provided solutions during geosteering. Multiscale modeling, which includes seismic, geosteering mapping data, LWD, and imagers, has been used for all cases. A more accurate determination of the effective lengths and formation properties helps optimize well completion design.

Abstract Drill cuttings are available in every well drilled and NMR is a powerful tool for characterization of rocks and fluids. It is thus desirable if useful petrophysical information can be derived from NMR drill cutting analysis. However, previous studies have shown that there are many uncertainties associated with cutting analysis by using NMR, such as (1) the small cutting size may not be representative of the formation rock pore system, and (2) the effect of drilling fluids which may penetrate and clog the pore space may result in uncertain pore typing and pore surface characterization. In this paper, based on a detailed methodology evaluation study using cuttings with different rock types, cutting sizes, and with different mud contaminations, we present experimental evidence to show (1) the best operational practices to remove mud and excess fluid contamination, and (2) the minimal cutting size required to obtain useful petrophysical information. In addition, we will also provide recommended cuttings preparation procedures and set the practical expectations for NMR drilling cutting analysis.

Abstract While proactive geosteering, special inversion algorithms are used to process the readings of logging-while-drilling resistivity tools in real-time and provide oil field operators with formation models to make informed steering decisions. Currently, there is no industry standard for inversion deliverables and corresponding quality indicators because major tool vendors develop their own device-specific algorithms and use them internally. This paper presents the first implementation of vendor-neutral inversion approach applicable for any induction resistivity tool and enabling operators to standardize the efficiency of various geosteering services. The necessity of such universal inversion approach was inspired by the activity of LWD Deep Azimuthal Resistivity Services Standardization Workgroup initiated by SPWLA Resistivity Special Interest Group in 2016. Proposed inversion algorithm utilizes a 1D layer-cake formation model and is performed interval-by-interval. The following model parameters can be determined: horizontal and vertical resistivities of each layer, positions of layer boundaries, and formation dip. The inversion can support arbitrary deep azimuthal induction resistivity tool with coaxial, tilted, or orthogonal transmitting and receiving antennas. The inversion is purely data-driven; it works in automatic mode and provides fully unbiased results obtained from tool readings only. The algorithm is based on statistical reversible-jump Markov chain Monte Carlo method that does not require any predefined assumptions about the formation structure and enables searching of models explaining the data even if the number of layers in the model is unknown. To globalize search, the algorithm runs several Markov chains capable of exchanging their states between one another to move from the vicinity of local minimum to more perspective domain of model parameter space. While execution, the inversion keeps all models it is dealing with to estimate the resolution accuracy of formation parameters and generate several quality indicators. Eventually, these indicators are delivered together with recovered resistivity models to help operators with the evaluation of inversion results reliability. To ensure high performance of the inversion, a fast and accurate semi-analytical forward solver is employed to compute required responses of a tool with specific geometry and their derivatives with respect to any parameter of multi-layered model. Moreover, the reliance on the simultaneous evolution of multiple Markov chains makes the algorithm suitable for parallel execution that significantly decreases the computational time. Application of the proposed inversion is shown on a series of synthetic examples and field case studies such as navigating the well along the reservoir roof or near the oil-water-contact in oil sands. Inversion results for all scenarios confirm that the proposed algorithm can successfully evaluate formation model complexity, recover model parameters, and quantify their uncertainty within a reasonable computational time. Presented vendor-neutral stochastic approach to data processing leads to the standardization of the inversion output including the resistivity model and its quality indicators that helps operators to better understand capabilities of tools from different vendors and eventually make more confident geosteering decisions.

Abstract 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.

Abstract For conventional acoustic monopole sources in a logging-while-drilling (LWD) or wireline environment, shear slowness logs can be hard to obtain, particularly in slow formations where direct refracted shear-wave arrivals are often absent. For LWD dipole sources, formation flexural waves are often coupled with the lowest order of tool flexural waves, so the flexural mode does not approach shear wave slowness at low frequencies. A dispersion correction is required to extract shear slowness from LWD dipole data. Instead, a quadrupole firing, which generates screw waves, is considered the best LWD excitation mode for shear measurement. A fundamental feature of screw waves in an LWD environment is that their non-leaky cutoff frequency slowness is the formation shear slowness. However, slowness data near the cutoff frequency of LWD screw waves are often influenced by noise or the presence of other modes because of low excitation amplitude. To overcome these LWD data processing challenges, we propose a data-driven processing method that uses all useful dispersion responses of existing modes in the frequency domain. The process first generates a differential phase frequency-slowness coherence map and extracts the slowness dispersion vs. frequency. Then, it computes the slowness density log, referring to the intensity of the dispersion response along the slowness axis. Next, an edge-detection method is applied to capture the edge of the first peak associated with shear slowness on the slowness density map. To refine the shear slowness answer, this initial estimate of shear slowness serves as the input to another algorithm that minimizes the misfit between the screw slowness vector and a simplified screw dispersion model. The simplified screw dispersion model consists of a pre-computed base library of theoretical screw dispersion curves and two data-driven parameters. The two data-driven parameters are used by the measured data to stretch the base dispersion model in the frequency and slowness axes, respectively, to account for errors generated by alteration, anisotropy, or other parameters not included in the forward modeling. The method can also be applied to flexural waves, where the initial guess of shear slowness is picked from the slowness density map of flexural waves after dispersion-correction processing.This paper shows a case study of borehole flexural and screw waves processing in soft formations. A modified differential-phase frequency-semblance (MDPFS) approach is applied to extract the mode waves' full-frequency dispersion response from measured waveforms. The data-driven shear slowness processing is applied to the dispersion response. Both dipole flexural waves and quadrupole screw waves are processed. A combination of slowness density log from the flexural or screw wave slowness and the dispersion-corrected slowness is used as a QC metric of the final estimated shear. Results show that flexural and screw dispersions are well measured by the LWD sonic tool, even if the shear slowness is as large as 500 μs/ft. Shear slowness extracted from flexural waves and screw waves match well with each other and with wireline shear slowness logs, demonstrating that the processing is reliable and robust.

In the current business environment, operators are increasingly striving to reduce logging expense when possible, while maintaining safety of the drilling operations. Mudlogging has been remarkably successful through the oil industry downturn due to the value of information derived from the analysis as well as the relatively low cost. Information about the lithology and fluid content of the borehole during drilling is important for drilling optimization and qualitative petrophysical assessment. This paper takes mudlogs a step further to quantify net pay and estimate reserves in low permeability reservoirs where traditional log analysis is challenging. Methods will be described for estimating gas-in-mud based on characterized gas measurement systems and obtain bulk volume of gas per volume of rock drilled. Corrections are discussed for mud gas systems based on their mechanical operating parameters of mud flow into the gas extractor, gas sample suction rate out of the gas extractor, recirculated gas, and estimated gas extraction efficiencies. Applying these corrections yields normalized bulk gas volume and gas-oil ratio which is calibrated with the petrophysical assessment from wireline logs and PVT samples. Finally, correlations between bulk hydrocarbon volume and permeability are used to estimate volumetrics. Case studies presented show that the calibrated mudlogs can be used for quantitative assessment of bulk volume of hydrocarbons in high-angle/horizontal-wells where conveying wireline logs might be challenging. Pay flags computed from the mudlog interpretation can be used to guide completion decisions. Additionally, GOR estimates derived from mudlogs can be used for fluid typing and optimizing the fluid sampling program in deepwater development wells. Results presented clearly show that mudlogs can provide continuous, real-time, and quantitative petrophysical assessments. INTRODUCTION Mudlogs continue to be the most important petrophysical data source available before wireline and logging while drilling (LWD) runs. Continuous gas monitoring service involves extraction of gases from the returning mud stream and analysis of volatile hydrocarbons. Commonly, the gas chromatography analysis is logged in real-time at drill depth and plotted with rate of penetration (ROP) and cuttings sample log (Whittaker, 1991). Therefore, the mudlog provides a unique dataset integrating drilling, geology, and petrophysics. However, the data is subject to uncontrolled variables in measurement technology as well as the dynamic borehole environment (Kyllingstad et al., 1993).

Full geological interpretation is now possible from logging-while-drilling (LWD) in oil-based mud following the advent of high-resolution acoustic borehole imaging technology. The new service provides acoustic amplitude images of the borehole wall, in addition to borehole shape in a resolution that greatly surpasses previous capabilities in oil-based mud. The measurements include acoustic amplitude (this response is a mixture of petrophysical properties and borehole shape) and acoustic travel-time (showing the stand-off of the borehole wall from the sensor). From the travel-time measurement, we calculate the borehole profile which is shown in a tube plot and is used to project borehole shape properties. In water-based mud, the acoustic imaging tool can be run in combination with the existing high-resolution electrical imager. This combination is particularly useful for characterizing fractures with the dual resistivity and acoustic properties for a more confident interpretation. We show examples from wells with a range of geological complexity, including fractures, faults, geomechanical features, sedimentological variation and changes in borehole shape. Contrast between lithologies and structural features and the background is similar to that seen in electrical measurements in the same environments. Fractures with a high acoustic amplitude response show a marked contrast with the background lithology. In many cases, they reveal the processes of formation including cataclasis, intersections, age-determining relationships and impact on reservoir connectivity. The inclusion of borehole shape with the acoustic amplitude image gives a new value to fault interpretation, where post-drilling stress release can be interpreted from the shape of the borehole surrounding a fault. In this example, micro-slippage along a fault can be seen directly in the protrusion into the borehole of one side of the fault. Amplitude images are detailed enough to allow full image facies characterization similar to that possible from wireline image equivalents, but with the benefit of measurement of the formation before the build-up of mudcake. We show examples in clastic and carbonate lithologies that include primary sedimentary structures, secondary remobilization processes and diagenetic overprints. Sedimentary detail in coal beds is unprecedented, including bedding and variation in mineralogical components. Applications based on borehole shape are shown, including geomechanical features, borehole stability, time-lapse logging and hazard mitigation. INTRODUCTION Borehole image logs have been evolving continually for several decades. This has been marked by advances in measurement physics, measurement sampling density, sensor resolution and changes in acquisition mode, such as wireline/LWD and acquisition in water-based mud/oil-based mud (Pöppelreiter et al. 2010, Ritter et al. 2005). Within the realm of the LWD acquisition mode, there has also been a continual evolution, culminating with the recent introduction of high-resolution acoustic measurements that now rival the quality of existing wireline services.

Electromagnetic (EM) inversion processing of ultradeep resistivity data has advanced from one-dimensional (1D) to three-dimensional (3D). These advances have helped improve the quality of inversion results and provided additional reservoir information. The large depth of investigation of ultra-deep LWD azimuthal EM tools (100 to 225 ft) means that distant boundaries might not be detected by any other sensor in the tool string, making it difficult to verify the results. As inversion results represent a model of the subsurface resistivity distribution, and are not a direct measurement, it is important to have high confidence in the results. With the multi-frequency, multi-component data used in 3D inversion, it is possible to directly compare the component data measured by the tool to the modelled component data. If the data shows a good fit across multiple frequencies, this provides confidence in the resultant model. However, as measurement sensitivities decrease with distance, it is possible to create an apparently good match between the measured and modelled component data with a model that is geologically unrealistic. Increased confidence in the results can be achieved when it is possible to verify them independently, such as by mapping a particular zone from multiple wellbores. This paper details results from a tri-lateral well in an injectite reservoir wherein the sand distribution and the associated resistivity distribution were very complex. 1D inversions showed the vertical distribution of the sand, but the results were sometimes distorted by lateral resistivity variations. Ultra-deep azimuthal resistivity images showed the resistivity distribution around the wellbore, but it was 3D inversion of the data that allowed the structures to be resolved clearly. These results can be corroborated by direct comparison with the azimuthal resistivity images, but the position of major sand bodies near the start of the laterals allows a further step to be taken to help increase confidence in the 3D results. The laterals all diverged from the same main bore and remained close together initially in an area containing major sand injectites. 3D inversions from two of the wells overlap and define similarly shaped structures, providing high confidence that the 3D inversion produces a good representation of the sand distribution. The third lateral diverged quickly, but the 3D inversion results from it still showed a major sand unit that could be traced back to the first lateral. In complex geobodies, such as the injectites described, significant lateral variation in the reservoir distribution is expected, which is not captured by 1D inversion. Understanding the shape of these structures and their potential connectivity using 3D inversion provides a major increase in reservoir understanding that is critical to completion design. Independent verification, by overlaying inversion results from adjacent wells, provides an additional proof beyond the verification methods available in a single wellbore.

Logging measurements in high-angle wells are often complicated by various geometric effects and generally require correction before use in accurate petrophysical evaluation. The geometric effects include, but are not limited to, shoulder beds, proximity to beds that may or may not have been crossed, polarization horns, laminations and non-uniform invasion. A case study demonstrates how log property modeling was applied using a fast and practical workflow to improve petrophysical answers. The wells studied are located in the Norwegian sector of the North Sea and penetrate a sequence of fairly thin sand and shale layers. The well trajectories range from deviated pilot holes through high-angle tangents. In the wells studied, both propagation and laterolog resistivity measurements and their associated wellbore images were acquired as well as azimuthal GR, density and neutron porosity logs. The difference between the laterolog and propagation resistivity measurements highlights the challenges of using the logs directly. A new workflow was used to quickly model the high-angle logs and cross-validate the responses. Although the largest geometrical effects were observed on the resistivity logs, the nuclear measurements were also affected to a lesser degree, and new fast forward models were applied in the same workflow to obtain the GR, density and neutron porosity log properties. The combination of the resistivity responses, and the ability to quickly and efficiently model the logs, provided improved confidence in the derived formation properties which were subsequently used for saturation computations. An example of the effect of thin laminations on high-angle well resistivity logs is shown. In addition, an example of asymmetric fluid invasion caused by gravity segregation of mud filtrate demonstrates how resistivity images aid interpretation in complex geometries. To help visualise these geometries a three-dimensional display tool is applied that allows for more intuitive understanding of the complex azimuthal and radial information provided by multi-depth of investigation resistivity images.