Automated geosteering relies on logging-while-drilling data from offset wells to make inferences about the geological formation and help guide directional drilling of the subject well. When data from multiple offset wells are available, it is desirable to consistently combine data typelogs from these wells to better estimate the 3D geological formation around the drilling path. We develop a quantitative typelog alignment method based on a Bayesian approach, where the alignment map between pairs of typelogs are modeled as a random function with a prior distribution. A multi-stage penalized procedure is developed that optimizes this alignment map to minimize a misfit function, while taking the prior knowledge into consideration.

Development of autonomous drilling technologies requires the automated analysis and interpretation of Logging While Drilling (LWD) data to optimally land the well in the target formation and keep it in the pay zone. This paper presents a fully automated geosteering algorithm, which includes advanced LWD filtering, fault detection, correlation, tracking of multiple interpretations with associated probabilities and visualization using novel stratigraphic misfit heatmaps. Traditional geosteering uses manual stretch, compress and match techniques to correlate measurements along the subject wellbore against corresponding reference type logs. This results in a crude representation of strata by linear sections with offsets at fault locations. Instead of automating this manual process, we instead determine the possible interpretations as solutions of a geophysical inverse problem in which the total misfit between the subject and reference data is minimized. Interpretations are parameterized as discontinuous splines to accurately follow curved strata interjected by fault offsets. To account for ambiguities, multiple possible interpretations are continuously tracked in real time and assigned probabilities based on the misfit between the latest measurements and the reference data. Unrealistic solutions are suppressed by penalizing strong curvature and large fault offsets. Viable interpretations are simultaneously visualized in real time as paths on a novel stratigraphic misfit heat map, where they may be corroborated against valleys of minimal misfit between the subject and reference data. The user can guide the interpretation by setting control points on the heat map which the automated solutions must respect. The algorithm has been validated using wells from different regions across North America for which previous manual geosteering interpretations are available. The automated spline interpretations represent the actual curved strata more accurately than manual interpretations. Operationally, the automated interpretations can be provided within minutes compared to typical manual turn-around times of hours. Automation leads to more consistent and repeatable results, removing the subjectivity of manual interpretations.

Abstract Developing resources in congested fields requires precise drilling to keep the wellbore in the correct stratigraphic unit and avoid collisions with existing wellbores. Automated geosteering is an advantageous method because it eliminates subjective and lengthy manual interpretation. We present an algorithm that incorporates drilling dynamics data to estimate rock strength, correlates to nearby offset wells, and locates the drill bit in stratigraphy. This new method is faster and more objective than the traditional manual interpretation. During well planning, gamma ray intensity, sonic, and geologic logs from nearby wells are recovered and used to calculate the Confined Compressive Strength (CCS) of the stratigraphic column using empirical and physical formulas. While drilling, the algorithm receives gamma ray intensity and drilling dynamics data (e.g. weight on bit, rate of penetration, revolutions per minute, fluid flow, and differential pressure) from the subject well and calculates the Mechanical Specific Energy (MSE) of the penetrated rock. Finally, the real time MSE and gamma from the subject well are correlated automatically with the previously generated CCS and gamma logs of the offset wells to locate the drill bit in stratigraphy. This approach to automated geosteering was tested on a large database of subject wells and offset wells from multiple basins in North America. We find that the nearby CCS logs generated from sonic data are significantly correlated with MSE values from drilling dynamics data from the subject wellbore. CCS and MSE values can therefore be used as complementary rock strength parameters for each stratigraphic unit. Furthermore, the automated geosteering algorithm has been successful in estimating the drill bit position in the stratigraphic column during real-time drilling simulations of incoming drilling dynamics data. Incorporating rock strength estimation and matching is a complementary and valuable technique to the standard gamma log interpretation for steering a wellbore to a geologic target. The automated algorithm facilitates the simultaneous correlation, in conjunction with gamma ray intensity, against multiple offset wells. Traditionally, geosteering is accomplished by manual comparison of LWD (Logging While Drilling) gamma ray intensity with nearby gamma logs from existing offset wells. Our approach is a significant advancement because it incorporates gamma ray data and previously unused drilling dynamics data, while automating the geosteering removes laborious and subjective processes. Mature oil fields contain considerable information on rock strength and our automated geosteering algorithm makes optimal use of this information to improve wellbore positioning.

As development of the Barents Sea continues with new plays such as the Castberg, accurate specification of the local magnetic field is important to reliably infer the orientation of the bottomhole assembly (BHA) in horizontal drilling. Since magnetic fields at high latitudes vary spatially and temporally, one requires both spatial models and a way to capture temporal changes. Large temporal changes in the magnetic field can severly distort measured azimuths and therefore must be corrected for. This study, based on a report written for Petroleumstilsynet (Maus et al., 2017), shows that in regions of the Barents Sea within 50 km of a magnetic observatory, either the nearest observatory, interpolated infield referencing (IIFR), or the disturbance function (DF) method may be used for corrections in wellbore surveying to meet accuracy requirements. IIFR and DF will give better error reduction but are slightly more complicated to implement. At distances between 50 km and 250 km, the disturbance field (DF) method best meets accuracy requirements. In remote regions beyond 250 km, a local observatory must be deployed to meet the highest accuracy specifications, but the DF will still far outperform the other interpolated methods at such large distances from an existing observatory. Despite having focused on the Barents Sea region, this comparison of the accuracy of different spatial and temporal magnetic field mitigation methods for wellbore surveying is applicable to high latitude northern and southern regions across the globe.

Positional uncertainty is a critical component of managing collision risk while drilling. Ensuring that survey data meet the requirements of their uncertainty models has historically required complicated analysis. Most consumers of survey data are not experts and knowing when escalation is required in a high-risk situation can be unclear. This problem will increase as more data is evaluated by automated decision-making systems. Two novel methods are proposed to analyze sets of survey data against uncertainty models with the intent to answer the questions: "Is it safe to continue drilling" and "Does this wellbore need to be resurveyed?". The proposed methods evaluate a survey set using the error sources, error magnitudes, and error propagations contained in positional uncertainty models. A quality control error covariance matrix is constructed, and the set is evaluated against it. Two statistical outputs are generated: a statistical distance that explains how well an additional survey fits with the existing survey data, and an overall survey assessment that describes the likelihood of an error-model compliant system producing the observed dataset. The methods are used to evaluate downhole magnetic survey data that was flagged after evaluation by subject matter experts, but traditional quality control measures had failed to identify as problematic. Errors that do not fit the expectations of the error model are flagged in a way that is apparent to a non-expert user and can be integrated into an automated alert system. How to include these procedures in drilling workflows is discussed, including when escalation to a subject matter expert is required. A system is proposed where, with minor modification to existing error models, this analysis can be automated for wellbore surveys of all kinds. Additional discussion is included on how these methods will fit into the upcoming API recommended practice on wellbore surveying.

Abstract Drilling ultra-extended-reach (ultra-ERD) wellbores has redefined industry standards. Operators and service companies must fully assess the accompanying risks to maximize the overall productivity of an asset. New drilling technologies, such as improved drilling fluid design and geomechanics analyses, allow wellbores to be drilled to the lateral displacement of greater than 13 km. This requires improved absolute wellbore positioning, in conjunction with reduced uncertainties. When developing these drilling technologies, the economics must be considered so as not to exponentially increase the cost per barrel of oil. The increase in infill drilling of nearby offset wellbores requires developing improved methods that reduce wellbore position uncertainty when placing the wellbore in the reservoir, in addition to avoiding collisions. The proposed geomagnetic referencing technique is suitable for the application to the Sakhalin-1 project in eastern Russia. Here there is a predominance of ultra-ERD wellbores coupled with considerable knowledge of the varying depth of the basement rock structure. This paper presents a process used for creating a geomagnetic crustal field model that can be updated to the actual survey location with the date and time for real-time application. This process can also be used in the reprocessing of legacy measurement-while-drilling (MWD) data. The application of this process significantly improves wellbore position accuracy. The ability to have a greater understanding of the overall geomagnetic field, along with enhanced techniques in multistation algorithm processing, removes the effects of drillstring and the cross-axial interference due to mud shielding effects. Additional benefits of this application include reduced wellbore tortuosity for planned wells, improved anticollision separation factors, and improved torque and drag profiles. This new geomagnetic model, updated to the actual survey location, date, and time and incorporating realistic uncertainty determinations based on basement rock depth analysis, has resulted in a 50% improvement in the overall ellipse of uncertainty (EOU) when compared with previous definitive surveys, in addition to an accurate bottomhole location. Incorporating these advanced techniques reduces position uncertainty that improves overall 3D wellbore positioning. Other studies, such as a disturbance field study, evaluate the effects of the magnetospheric ring current, auroral electrojets, and secondary induced fields, and was conducted by analyzing the magnetic observatory data from the same magnetic latitude to quantify the maximum and minimum declination variations during a magnetic storm.

Rotation of the Earth in its own geomagnetic field sets up a primary corotation electric field, compensated by a secondary electric field of induced electrical charges. For the geomagnetic field measured by the Swarm constellation of satellites, a derivation of the global corotation electric field inside and outside of the corotation region is provided here, in both inertial and corotating reference frames. The Earth is assumed an electrical conductor, the lower atmosphere an insulator, followed by the corotating ionospheric E region again as a conductor. Outside of the Earth's core, the induced charge is immediately accessible from the spherical harmonic Gauss coefficients of the geomagnetic field. The charge density is positive at high northern and southern latitudes, negative at midlatitudes, and increases strongly toward the Earth's center. Small vertical electric fields of about 0.3 mV/m in the insulating atmospheric gap are caused by the corotation charges located in the ionosphere above and the Earth below. The corotation charges also flow outward into the region of closed magnetic field lines, forcing the plasmasphere to corotate. The electric field of the corotation charges further extends outside of the corotating regions, contributing radial outward electric fields of about 10mV/m in the northern and southern polar caps. Depending on how the magnetosphere responds to these fields, the Earth may carry a net electric charge.

Abstract We present a study conducted to develop and validate new capabilities for offshore geomagnetic surveying that employs the autonomous marine vehicle (AMV) to map the crustal magnetic field and monitor disturbance fields surrounding offshore drill sites. Knowledge of geomagnetic field direction and strength in the wellbore are essential parameters needed for directional drilling. To compute wellbore azimuth, the directional driller compares the magnetic field measurement provided by the measurement-while-drilling (MWD) tool with the geomagnetic field reference data to position the wellbore in real time while drilling. Correction for variations in the disturbance field is essential for accurate mapping of the crustal geomagnetic field. Unfortunately, land-based stations are not ideal for mapping the disturbance field in the offshore because of the distance of the station from the measurement site and the different electrical conductivity of the subsurface. To address the need for improved measurement of the disturbance field in offshore surveys, this study also investigated whether the new-generation, hybrid, wave- and electric-thruster powered AMV is suitable for use as a "base station" to monitor time variations of the geomagnetic disturbance field. To conduct the study, we equipped two hybrid AMVs with towed marine magnetometers. Highly sensitive sensors established the minimum required separation between the AMV's electric thruster and the magnetic sensor payload. For validation as a base station, data collected by the vehicles from May 11 to May 14, 2015, was analyzed and compared with data obtained from the USGS Honolulu Geomagnetic Observatory (HON). To then evaluate the survey measurement system offshore, we compared data from a previous 2013 wave-powered AMV geomagnetic survey (Poedjono et al., 2015) with repeat data of the main, tie, and perimeter lines newly collected by the AMVs in this 2015 study. Our results show that the AMV is ideally suited to carry out geomagnetic surveys in offshore remote locations, and a second AMV circulating at a fixed location provides a more accurate base station than a land-based station. The hybrid AMV offers distinct advantages for geomagnetic data collection in offshore environments. The low cost compared to a seaborne or airborne vehicle allows AMVs to be deployed in tandem and collect data repeatedly over predefined areas, yielding accurate measurements to determine the disturbance and crustal magnetic fields. Use of the AMV solves the long-standing problem of how to accurately map the previously unknown geomagnetic reference field in offshore locations.

Plasmaspheric rotation is known to lag behind Earth rotation. The causes for this corotation lag are not yet fully understood. We have used more than 2 years of Van Allen Probe observations to compare the electric drift measured below L ~ 2 with the predictions of a general model. In the first step, a rigid corotation of the ionosphere with the solid Earth was assumed in the model. The results of the model‐observation comparison are twofold: (1) radially, the model explains the average observed geographic variability of the electric drift; (2) azimuthally, the model fails to explain the full amplitude of the observed corotation lag. In the second step, ionospheric corotation was modulated in the model by thermospheric winds, as given by the latest version of the horizontal wind model. Accounting for the thermospheric corotation lag at ionospheric E region altitudes results in significantly better agreement between the model and the observations.

Standard directional surveying practices are subject to numerous error sources which can cause inaccurate placement of the wellbore. This is problematic because inaccurate wellbore placement increases collision risk, reduces reservoir drainage, and impacts subsurface models. Web-based software was developed to provide rig site personnel with a simple interface to transfer survey data in real-time to survey analysts in a remote operations center. The web interface is easily accessible via standard web browsers and enables users to upload data in any format without the need to manually configure or manipulate data fields. Independent survey quality analysis by remote operating centers is the most effective way to validate directional survey accuracy and to ensure it is free from gross or large systematic errors that exceed the assumptions of the positional error model. Furthermore, by applying multi-station analysis corrections and using in-field referencing geomagnetic models, the positional uncertainty of the wellbore trajectory can be reduced by 50 percent or greater. These methods improve wellbore placement substantially at a low operational cost, thus significantly increasing the value of the wellbore.

The pace of scientific discovery is being transformed by the availability of ‘big data’ and open access, open source software tools. These innovations open up new avenues for how scientists communicate and share data and ideas with each other and with the general public. Here, we describe our efforts to bring to life our studies of the Earth system, both at present day and through deep geological time. The GPlates Portal (portal.gplates.org) is a gateway to a series of virtual globes based on the Cesium Javascript library. The portal allows fast interactive visualization of global geophysical and geological data sets, draped over digital terrain models. The globes use WebGL for hardware-accelerated graphics and are cross-platform and cross-browser compatible with complete camera control. The globes include a visualization of a high-resolution global digital elevation model and the vertical gradient of the global gravity field, highlighting small-scale seafloor fabric such as abyssal hills, fracture zones and seamounts in unprecedented detail. The portal also features globes portraying seafloor geology and a global data set of marine magnetic anomaly identifications. The portal is specifically designed to visualize models of the Earth through geological time. These space-time globes include tectonic reconstructions of the Earth’s gravity and magnetic fields, and several models of long-wavelength surface dynamic topography through time, including the interactive plotting of vertical motion histories at selected locations. The globes put the on-the-fly visualization of massive data sets at the fingertips of end-users to stimulate teaching and learning and novel avenues of inquiry.

Abstract Optimal wellbore placement and collision avoidance requires accurate real-time steering of directional wells. Uncertainties in the wellbore position are accounted for by industry standard error models. However, these error models are only valid if the directional surveys are quality controlled and gross error is prevented by appropriate procedures. Particularly effective quality control is achieved by independent validation. A novel real-time web application was developed for the transfer of directional survey data between the rig site and a remote operations center. Surveying professionals at the rig site upload or import survey data into the web application in real-time. The survey measurements are then automatically validated through independent quality checks to identify gross error. Remote survey analysts can access the pre-qualified survey data and evaluate it for systematic or random error that would indicate non-compliance with the instrument performance model. Surveys can also be corrected in real-time when systematic error is identified and provided back to the rig site personnel for accurate steering and wellbore placement. This web service has been implemented and refined on over 50 rigs in North America. Examples for common types of errors that were prevented and/or corrected are incorrect magnetic declination, wrong north reference, excessive drillstring interference, poor instrument calibration, sensors misaligned with the wellbore and incorrect survey order. The impact of these errors if not prevented could easily cause 100 ft. or more in positional error at the bottom hole location. Real-time survey quality analysis provides higher confidence in wellbore placement, reduces risk of collision, and maximizes reservoir drainage.

Currently, there are several published end-member plate models that describe the evolution of Iberia during the Mesozoic. We review key geological and geophysical data sets previously used as constraints on these models including (1) geological interpretations of Pyrenean geology; (2) end-member interpretations of magnetic anomalies along the West Iberian and Newfoundland margins and Bay of Biscay; (3) the paleomagnetic data set of Iberia; and (4) seismic tomography models, which have previously been used to support Cretaceous subduction between Iberia and Eurasia. From this review we identify key constraints and argue that a reasonable plate kinematic model of Iberia should satisfy all of these. Instead, we determine inconsistencies between these key constraints and several published end-member plate models through a kinematic analysis using the GPlates software. We also analyze published seismic tomography models, not previously considered, across northern Africa and Iberia, and identify no slab preserved within the mantle supposedly linked to Cretaceous subduction between Iberia and Eurasia. A lack of published geological evidence along the Pyrenees supporting this subduction history also casts doubt on this scenario. Our kinematic analysis highlights that, first, the cessation in transtensional motion between Iberia and Eurasia by the Albian cannot be kinematically reconciled with the concurrent breakup between Iberia and Newfoundland in the Atlantic when reconstructing existing continent-ocean boundary interpretations along their respective margins. Second, either fit of the contentious end-member M-0 interpretations (similar to 120.6 Ma) between Iberia and Newfoundland implies plate velocities of Iberia that results in its undocumented transpressional or compressional motion relative to Eurasia until C-34.

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A new version of the World Digital Magnetic Anomaly Map, released last summer, gives greater insight into the structure and history of Earth's crust and upper mantle.

Abstract Optimizing lateral well spacing is a challenging problem that has significant economic consequences. The intent is to drill the fewest number of horizontal wells that will effectively maximize reservoir drainage. Successful field development requires spacing horizontal wellbores at an optimum distance that minimizes overlapping drainage areas without stranding reserves. There are many variables that must be considered when determining lateral spacing such as hydraulic fracture geometry and reservoir properties. However, a variable that is often overlooked is wellbore positional uncertainty. It is common to ignore the contribution that inaccurate directional surveying has on lateral wellbore spacing. The purpose of this paper is to demonstrate how inaccuracy in standard directional surveying methods impacts wellbore position and to recommend practices to improve surveying accuracy for greater confidence in lateral spacing. Standard directional surveying by measurement while drilling (MWD) is subject to numerous error sources which can be estimated by the Industry Steering Committee on Wellbore Survey Accuracy (ISCWSA) error model (Grinrod 2016). These error sources are quantified and modeled as three dimensional Ellipsoids of Uncertainty (EOUs) which provide drillers a mechanism for measuring positional uncertainty associated with the wellbore trajectory. The ISCWSA error model can be used to predict the statistical distribution of wellbore positions in order to gain an understanding of how far actual well paths might deviate from the surveyed position. Furthermore, some of the greatest error sources represented in the error model can be significantly reduced using In-Field geomagnetic Referencing (IFR) and Multi-Station Analysis (MSA) in order to improve the accuracy of the MWD surveys (Maus 2015). Performing advanced survey management analysis to raw MWD data and correcting identified systematic errors in real-time improves the accuracy of the well placement as the wellbore is drilled. In order to reliably determine the most optimal lateral well spacing, positional uncertainty should be considered and applied to reservoir simulations and production models. Furthermore, applying IFR and MSA survey corrections to standard MWD surveying can improve horizontal wellbore positional accuracy by 50 to 60 percent (Maus 2015), thus leading to better decisions for optimizing field development and maximizing wellbore value.

The 12th generation of the International Geomagnetic Reference Field (IGRF) was adopted in December 2014 by the Working Group V-MOD appointed by the International Association of Geomagnetism and Aeronomy (IAGA). It updates the previous IGRF generation with a definitive main field model for epoch 2010.0, a main field model for epoch 2015.0, and a linear annual predictive secular variation model for 2015.0-2020.0. Here, we present the equations defining the IGRF model, provide the spherical harmonic coefficients, and provide maps of the magnetic declination, inclination, and total intensity for epoch 2015.0 and their predicted rates of change for 2015.0-2020.0. We also update the magnetic pole positions and discuss briefly the latest changes and possible future trends of the Earth’s magnetic field.

The day-time eastward equatorial electric field (EEF) in the ionospheric E-region plays a crucial role in equatorial ionospheric dynamics. It is responsible for driving the equatorial electrojet (EEJ) current system, equatorial vertical ion drifts, and the equatorial ionization anomaly (EIA). Due to its importance, there is much interest in accurately measuring and modeling the EEF for both climatological and near real-time studies. The Swarm satellite mission offers a unique opportunity to estimate the equatorial electric field from measurements of the geomagnetic field. Due to the near-polar orbits of each satellite, the on-board magnetometers record a full profile in latitude of the ionospheric current signatures at satellite altitude. These latitudinal magnetic profiles are then modeled using a first principles approach with empirical climatological inputs specifying the state of the ionosphere. Since the EEF is the primary driver of the low-latitude ionospheric current system, the observed magnetic measurements can then be inverted for the EEF. This paper details the algorithm for recovering the EEF from Swarm geomagnetic field measurements. The equatorial electric field estimates are an official Swarm level-2 product developed within the Swarm SCARF (Satellite Constellation Application Research Facility). They will be made freely available by ESA after the commissioning phase.

The orientation of a spacecraft in Low Earth Orbit can be determined accurately from either magnetic field measurements or star camera images. Ideally, the independently computed spacecraft attitudes should agree. However, we find that the German CHAMP and European Space Agency triple-satellite Swarm geomagnetic satellites exhibit consistent misalignments between the stellar and geomagnetic reference frames, which oscillate with the local time of the orbit. Having an amplitude of 20 arcsec, these oscillations are more than an order of magnitude larger than the stability of the optical bench, which cohosts the magnetometers and star cameras. The misalignments could originate either from the magnetometer or star camera measurements. On one hand, as-yet-unknown external magnetic field contributions could appear as a rotation of the geomagnetic reference frame. On the other hand, the observed misalignments agree in amplitude and phase with the effects of stellar aberration, caused by the movement of the star cameras relative to the light rays emitted by the stars. This is surprising because stellar aberration is allegedly already corrected for by the star image processing system. Resolving these mysterious misalignments is key to fulfilling the measurement accuracy requirements and science objectives of the ongoing Swarm mission. If caused by stellar aberration, fully correcting for this effect could significantly improve the attitude accuracy not only of CHAMP and Swarm, but also of several other past and ongoing scientific satellite missions.