DETECTION OF OFFSET WELLS AHEAD OF AND AROUND AN LWD ULTRA-DEEP ELECTROMAGNETIC TOOL

2021 ◽  
Author(s):  
Nigel Clegg ◽  
◽  
Alban Duriez ◽  
Vladimir Kiselev ◽  
Supriya Sinha ◽  
...  

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.

2021 ◽  
Vol 6 (4) ◽  
pp. e005413
Author(s):  
Valeria Raparelli ◽  
Colleen M. Norris ◽  
Uri Bender ◽  
Maria Trinidad Herrero ◽  
Alexandra Kautzky-Willer ◽  
...  

Gender refers to the socially constructed roles, behaviours, expressions and identities of girls, women, boys, men and gender diverse people. Gender-related factors are seldom assessed as determinants of health outcomes, despite their powerful contribution. The Gender Outcomes INternational Group: to Further Well-being Development (GOING-FWD) project developed a standard five-step methodology applicable to retrospectively identify gender-related factors and assess their relationship to outcomes across selected cohorts of non-communicable chronic diseases from Austria, Canada, Spain, Sweden. Step 1 (identification of gender-related variables): Based on the gender framework of the Women Health Research Network (ie, identity, role, relations and institutionalised gender), and available literature for a certain disease, an optimal ‘wish-list’ of gender-related variables was created and discussed by experts. Step 2 (definition of outcomes): Data dictionaries were screened for clinical and patient-relevant outcomes, using the International Consortium for Health Outcome Measurement framework. Step 3 (building of feasible final list): a cross-validation between variables per database and the ‘wish-list’ was performed. Step 4 (retrospective data harmonisation): The harmonisation potential of variables was evaluated. Step 5 (definition of data structure and analysis): The following analytic strategies were identified: (1) local analysis of data not transferable followed by a meta-analysis combining study-level estimates; (2) centrally performed federated analysis of data, with the individual-level participant data remaining on local servers; (3) synthesising the data locally and performing a pooled analysis on the synthetic data and (4) central analysis of pooled transferable data. The application of the GOING-FWD multistep approach can help guide investigators to analyse gender and its impact on outcomes in previously collected data.


Geophysics ◽  
2011 ◽  
Vol 76 (4) ◽  
pp. F239-F250 ◽  
Author(s):  
Fernando A. Monteiro Santos ◽  
Hesham M. El-Kaliouby

Joint or sequential inversion of direct current resistivity (DCR) and time-domain electromagnetic (TDEM) data commonly are performed for individual soundings assuming layered earth models. DCR and TDEM have different and complementary sensitivity to resistive and conductive structures, making them suitable methods for the application of joint inversion techniques. This potential joint inversion of DCR and TDEM methods has been used by several authors to reduce the ambiguities of the models calculated from each method separately. A new approach for joint inversion of these data sets, based on a laterally constrained algorithm, was found. The method was developed for the interpretation of soundings collected along a line over a 1D or 2D geology. The inversion algorithm was tested on two synthetic data sets, as well as on field data from Saudi Arabia. The results show that the algorithm is efficient and stable in producing quasi-2D models from DCR and TDEM data acquired in relatively complex environments.


2021 ◽  
Author(s):  
Kyubo Noh ◽  
◽  
Carlos Torres-Verdín ◽  
David Pardo ◽  
◽  
...  

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.


2020 ◽  
Author(s):  
Valeria Raparelli Raparelli ◽  
Colleen M. Norris ◽  
Uri Bender ◽  
Maria Trinidad Herrero ◽  
Alexandra Kautzky-Willer ◽  
...  

Abstract Background: Gender refers to the socially constructed roles, behaviors, expressions, and identities of girls, women, boys, men, and gender diverse people. It influences self-perception, individual’s actions and interactions, as well as the distribution of power and resources in society. Gender-related factors are seldom assessed as determinants of health outcomes, despite their powerful contribution.Methods: Investigators of the GOING-FWD project developed a standard methodology applicable for observational studies to retrospectively identify gender-related factors to assess their relationship to outcomes and applied this method to selected cohorts of non-communicable chronic diseases from Austria, Canada, Spain, Sweden.Results: The following multistep process was applied. Step 1 (Identification of Gender-related Variables): Based on the gender framework of the Women Health Research Network (i.e. gender identity, role, relations, and institutionalized gender), and available literature for a certain disease, an optimal “wish-list” of gender-related variables/factors was created and discussed by experts. Step 2 (Definition of Outcomes): each of the cohort data dictionaries were screened for clinical and patient relevant outcomes, using the ICHOM framework. Step 3 (Building of Feasible Final List): A cross-validation between gender-related and outcome variables available per database and the “wish-list” was performed. Step 4 (Retrospective Data Harmonization): The harmonization potential of variables was evaluated. Step 5 (Definition of Data Structure and Analysis): Depending on the database data structure, the following analytic strategies were identified: (1) local analysis of data not transferable followed by a meta-analysis combining study-level estimates; (2) centrally performed federated analysis of anonymized data, with the individual-level participant data remaining on local servers; (3) synthesizing the data locally and performing a pooled analysis on the synthetic data; and (4) central analysis of pooled transferable data.Conclusion: The application of the GOING-FWD systematic multistep approach can help guide investigators to analyze gender and its impact on outcomes in previously collected data.


2021 ◽  
Author(s):  
Raja Azizah Raja Yeop ◽  
Sian Chin Tan ◽  
Ariff Irfan Zainai

Abstract This paper is to demonstrate the significance of structured planning, holistic assessment and synergies, as key value drivers in enabling and shaping decommissioning alternatives leading to sustainable decommissioning and circular economy. PETRONAS as the regulator of Malaysia's Upstream activities manage decommissioning obligations through Production Sharing Contracts, internal guidelines and other relevant procedures and standards. The Decommissioning Options Assessment (DOA) is the process used to land on the most feasible option. Throughout PETRONAS’ 18-year decommissioning journey thus far, decommissioning projects were successfully executed using various alternatives. The valuable learnings gained are applied to further strengthen our decommissioning processes in regulating, enabling and shaping future executions at the lowest cost with safety of life and protection of the environment as our utmost priority. Upon a decision to proceed with decommissioning, a gated technical review process is used as the governing process to ensure safety, protection to the environment and cost efficiency. It is during this gated technical review that DOA is conducted. The output from the DOA is deliberated within the ambit of five (5) key criteria, i.e. Health, Safety & Security, Environment, Society, Technical & Operational, and Economy. Upon completion of execution, lessons learnt coupled with findings from post-decommissioning surveys are analyzed and applied to future projects. Synergies and collaborations are key drivers in shaping sustainable and replicable alternative decommissioning solutions. PETRONAS continuously pursues strategic collaborations with all stakeholders, including but not limited to, government ministries/agencies, academia, and industry players to tap into global decommissioning solutions, scientific researches, technologies, and best practices. This key lever will be discussed in the paper. From actual experiences, supported by studies, it is evident that decommissioning alternatives, including Rigs-to-Reef, add value in terms of marine habitat protection, biodiversity enhancement, fish aggregation, etc. It has also contributed positively to the livelihoods and well-being of society. Re-using platforms for new field development maximizes value by extending the platform's useful life. In addition, PETRONAS also advocates the ‘design for decommissioning’ mindset during a field's development phase in achieving a robust life cycle cost. PETRONAS further believes the values gained from these decommissioning alternatives will contribute to the decommissioning ecosystem in Malaysia. Moving forward, PETRONAS aspires to elevate the sustainable decommissioning model with the mindset that, ‘no single piece of an abandoned structure goes to waste’. There is a need to mature studies, collaborations and supply chain readiness in realizing more options on the 3Rs (Reduce, Re-use and Recycle).


2019 ◽  
Vol 221 (1) ◽  
pp. 87-96
Author(s):  
S Malecki ◽  
R-U Börner ◽  
K Spitzer

SUMMARY We present a procedure for localizing underground positions using a time-domain inductive electromagnetic (EM) method. The position to be localized is associated with an EM receiver placed inside the Earth. An EM field is generated by one or more transmitters located at known positions at the Earth’s surface. We then invert the EM field data for the receiver positions using a trust-region algorithm. For any given time regime and source–receiver geometry, the propagation of the electromagnetic fields is determined by the electrical conductivity distribution within the Earth. We show that it is sufficient to use a simple 1-D model to recover the receiver positions with reasonable accuracy. Generally, we demonstrate the robustness of the presented approach. Using confidence ellipses and confidence intervals we assess the accuracy of the recovered location data. The proposed method has been extensively tested against synthetic data obtained by numerical experiments. Furthermore, we have successfully carried out a location recovery using field data. The field data were recorded within a borehole in Alberta (Canada) at 101.4 m depth. The recovered location of the borehole receiver differs from the actual location by 0.70 m in the horizontal plane and by 0.82 m in depth.


2020 ◽  
Vol 10 (9) ◽  
pp. 3024
Author(s):  
Italo Zoppis ◽  
Andrea Trentini ◽  
Sara Manzoni ◽  
Daniela Micucci ◽  
Giancarlo Mauri ◽  
...  

Conscious and functional use of online social spaces can support the elderly with mind cognitive impairment (MCI) in their daily routine, not only for systematic monitoring, but to achieve effective targeted engagement. In this sense, although social involvement can be obtained when elder’s experiences, interests, and goals are shared and accepted by the community, an important subsistence for aging depends on the compelling information, users’ co-operation, and resource reliability. Unfortunately, applications aimed at optimizing the information content and the reliability of online users are still missing. Within the SystEm of Nudge theory-based ICT applications for OldeR citizens (SENIOR) project, an advanced social platform will be created in which the elderly with MCI will be involved in “optimized” social communities, where suggestions for general well-being will be recognized as useful by users and shared by care providers. We report the results of our study addressing this issue from a theoretical perspective: we propose a computational problem and a heuristic solution where “expert users” can engage and support the elderly by suggesting available services and facilities for their conditions. The numerical experiments on synthetic data are of interest when considering large communities, which is the most natural situation for online social spaces.


2020 ◽  
Author(s):  
Jianbo Qi ◽  
Donghui Xie

<p>Three-dimensional (3D) radiative transfer (RT) modeling and simulation of the transport of radiation through earth surfaces is a challenging and difficult task. The difficulties lie in the complexity of the landscapes and also the intensive computational cost of 3D RT simulations. Current models usually work with abstract landscape elements to reduce complexity or only consider relatively small realistic scenes. In this study, a new 3D RT modeling framework (called LESS) is proposed. It employs a forward photon tracing method to simulate bidirectional reflectance factor (BRF) or flux-related data (e.g., downwelling radiation) and a backward path tracing method to generate sensor images (e.g., fisheye images) or large-scale (e.g. 1 km<sup>2</sup>) spectral images from visible to thermal infrared band. In this framework, a graphic user interface (GUI) and a set of tools are also provided to help to construct the landscape and set parameters, e.g., extracting tree crowns from airborne LiDAR data, which makes it more accessible to common users. The accuracy of LESS is evaluated with other models and field measurements in terms of directional BRF and pixel-wise comparisons. It shows that the accuracy of LESS is consistent with the reference models from RAMI model inter-comparison website (http://rami-benchmark.jrc.ec.europa.eu/HTML/Home.php) as well as field measurements. LESS has also been extended to simulate atmosphere, LiDAR and in-situ sensors. It provides as a useful tool for studying the radiative transfer process over complex forest canopies from leaf to canopy scales. The simulated datasets can be used as benchmarks for validating other physical remote sensing inversion algorithm and developing parameterized models for retrieving bio-geophysical variables of canopy. LESS can be accessed from http://lessrt.org.</p>


Geophysics ◽  
1995 ◽  
Vol 60 (6) ◽  
pp. 1805-1818 ◽  
Author(s):  
Tong Xu ◽  
George A. McMechan ◽  
Robert Sun

A full‐wavefield inversion algorithm for direct imaging of a 3-D compressional wave velocity distribution is based on the full 3-D scalar wave equation and operates on common‐source data recorded by areal arrays. For each source, the method involves reverse‐time extrapolation of the residual wavefield. Application of the image condition by crosscorrelation with the source wavefield at each time step produces a 3-D image whose amplitude at each point is proportional to the required velocity update at that point. Convergence to local minima is mitigated against by gradually increasing the wavenumber bandwidth in the estimated 3-D velocity distribution as iterations proceed, starting from the smallest wavenumber. The algorithm is illustrated by successful application to synthetic data for a multilayered monocline, and for a multilayered structure with the geometry of the standard French model. The latter demonstrates good performance with noisy, unequally spaced data with significant elevation statics.


Geophysics ◽  
2009 ◽  
Vol 74 (2) ◽  
pp. R1-R14 ◽  
Author(s):  
Wenyi Hu ◽  
Aria Abubakar ◽  
Tarek M. Habashy

We present a simultaneous multifrequency inversion approach for seismic data interpretation. This algorithm inverts all frequency data components simultaneously. A data-weighting scheme balances the contributions from different frequency data components so the inversion process does not become dominated by high-frequency data components, which produce a velocity image with many artifacts. A Gauss-Newton minimization approach achieves a high convergence rate and an accurate reconstructed velocity image. By introducing a modified adjoint formulation, we can calculate the Jacobian matrix efficiently, allowing the material properties in the perfectly matched layers (PMLs) to be updated automatically during the inversion process. This feature ensures the correct behavior of the inversion and implies that the algorithm is appropriate for realistic applications where a priori information of the background medium is unavailable. Two different regularization schemes, an [Formula: see text]-norm and a weighted [Formula: see text]-norm function, are used in this algorithm for smooth profiles and profiles with sharp boundaries, respectively. The regularization parameter is determined automatically and adaptively by the so-called multiplicative regularization technique. To test the algorithm, we implement the inversion to reconstruct the Marmousi velocity model using synthetic data generated by the finite-difference time-domain code. These numerical simulation results indicate that this inversion algorithm is robust in terms of starting model and noise suppression. Under some circumstances, it is more robust than a traditional sequential inversion approach.


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