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Collaborating Authors
Results
Sensitivity analysis of S-waves and their velocity measurement in slow formations from monopole acoustic logging-while-drilling
Ji, Yunjia (University of Electronic Science and Technology of China, Guilin University of Electronic Technology, Chinese Academy of Sciences) | Wang, Hua (University of Electronic Science and Technology of China, University of Electronic Science and Technology of China)
Monopole acoustic logging-while-drilling (LWD) enables the direct measurement of shear (S) wave velocity in slow formations, which has been corroborated by recent theoretical and experimental studies. However, this measurement is hampered by the weakness of the S-wave signal and the lack of techniques to amplify it. To address this challenge, we have analytically computed the monopole LWD wavefields, considering both centralized and off-center tools in various slow formations. Modeling analysis reveals that four parameters primarily influence the excitation of the formation S-wave: the formation S-wave velocity, the source-to-receiver distance, the radial distance from receiver to wellbore, and source frequency. S-wave signals can be enhanced by judiciously optimizing these parameters during tool design. Furthermore, our research suggests that the S-wave velocity can be accurately extracted through the slowness-time correlation method only when formation S-wave velocities are in a suitable range. This is because an overly high S-wave velocity causes shear arrivals to be interfered with the inner Stoneley mode, whereas an ultra-slow formation S-wave velocity results in S-wave signals too faint to detect. For the LWD model with an off-center tool, simulations demonstrate that tool eccentricity, especially large eccentricity, can amplify the shear wave and improve its measurement accuracy, provided that waveforms received in the direction of tool movement are used. In a very slow formation, we successfully extracted the S-wave velocity from synthetic full-wave data at that azimuth under conditions of large eccentricity, a task not achievable with a centralized instrument.
- Research Report > New Finding (1.00)
- Research Report > Experimental Study (0.87)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
LITHOCODIUM MOUND IDENTIFICATION USING LWD IMAGE LOG AND QUANTIFIED CUTTING ANALYSIS ย VALIDATION WITH ANALOGUES
Perrin, Christian (North Oil Company) | Pointer, Chay (North Oil Company) | Al-Mohannadi, Ghada (North Oil Company) | Sen, Shantanu (North Oil Company) | Buraimoh, Muse Ajadi (QatarEnergy)
Lithocodium mounds are early Cretaceous sedimentary structures described in the literature from outcrops, however, never described in the subsurface. The objective of this work is to identify and characterize Lithocodium mounds in the subsurface along a 25,000ft horizontal well. Drill cuttings sampled at a 100ft interval are observed in thin sections to define and quantify key sedimentary indicators (bioclasts, facies, and texture). Logging-while-drilling (LWD) GR, density, neutron, and resistivity logs are acquired along with the LWD high-resolution borehole image (BHI) log. Bedding dips from BHI data, interpreted along the horizontal well, enabled the reconstruction of the reservoir paleotopography. In particular, the alternation of dip azimuth combined with the facies interpretation from the thin sections supported the interpretation of eight distinct mound structures. An assessment of their overall geometry confirmed the mound shape to be subcircular, consistent with the subcircular geometries observed in Oman at the outcrop. The inferred dimensions of the mounds are comparable with the Aptian Lithocodium mounds in Oman (3040m), and their intermound organization resembles that of the Albian mounds in Texas. This work demonstrates the value of analyzing cuttings to complement image log interpretation and the value of outcrop analogs for interpreting sedimentary structures. For the first time, the subsurface identification and characterization of Lithocodium mounds and intermounds are achieved.
- North America > United States > Texas (0.48)
- Asia > Middle East > Oman (0.45)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (1.00)
- Geology > Sedimentary Geology > Depositional Environment (0.93)
- Geology > Geological Subdiscipline > Stratigraphy (0.66)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (0.48)
- Well Drilling > Drilling Operations (1.00)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
A fast algorithm for simulation and analysis of wavefields in acoustic single-well imaging of logging-while-drilling considering arbitrary types of sources
Xu, Jiaqi (Harbin Institute of Technology, Harbin Institute of Technology) | Hu, Hengshan (Harbin Institute of Technology) | Han, Bo (Harbin Institute of Technology)
ABSTRACT Acoustic single-well imaging (SWI) of logging-while-drilling (LWD) is an advanced logging method in reservoir exploration, which uses reflected waves to detect the around-borehole geologic structures and quickly determines the drilling direction for enhancing the drilling-encounter ratio and reducing the drilling risk. Forward acoustic modeling is a fundamental problem for SWI in LWD. Due to the complex structures, it is a challenge to simulate the wave propagation and investigate wavefield characteristics based on the forward model. Numerical modeling is a commonly used method for calculating wavefields; however, it is too computationally expensive. In this study, we develop a fast method for calculating the full reflected pressure and displacement waves (i.e.,ย P-P, SV-SV, SH-SH, and P-SV/SV-P) in SWI of LWD considering different types of sources such as arcuate, monopole, and dipole transmitters. The analytical algorithm is developed by applying the reciprocity relation between the virtual force (displacement) sources located at the receiver position and the outside-borehole virtual forces that are equivalent to the reflections from the formation interfaces. Numerical experiments indicate that the analytical solutions agree well with the reference solutions from the 3D finite-difference time-domain method, demonstrating the accuracy and high efficiency of the analytical method. Based on the analytical solutions, we find that LWD reflected waves are much more sensitive to the azimuth than those in the wireline case, indicating that the availability of LWD is important for identifying the reflector azimuth. Furthermore, to enhance the reception efficiency of reflected waves, the LWD parameters are optimized. For slow formations, we suggest using a dipole source with dominant excitation-frequency band being from 1ย kHz to 3ย kHz. For fast formations, a dipole with wider excitation-frequency band from 1ย kHz to 5ย kHz is recommended. For all formations, recording pressure signals indicates much higher reception efficiency than the displacement signals.
- Geophysics > Seismic Surveying (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
A fast algorithm for simulation and analysis of wavefields in acoustic single-well imaging of logging-while-drilling considering arbitrary types of sources
Xu, Jiaqi (Harbin Institute of Technology, Harbin Institute of Technology) | Hu, Hengshan (Harbin Institute of Technology) | Han, Bo (Harbin Institute of Technology)
ABSTRACT Acoustic single-well imaging (SWI) of logging-while-drilling (LWD) is an advanced logging method in reservoir exploration, which uses reflected waves to detect the around-borehole geologic structures and quickly determines the drilling direction for enhancing the drilling-encounter ratio and reducing the drilling risk. Forward acoustic modeling is a fundamental problem for SWI in LWD. Due to the complex structures, it is a challenge to simulate the wave propagation and investigate wavefield characteristics based on the forward model. Numerical modeling is a commonly used method for calculating wavefields; however, it is too computationally expensive. In this study, we develop a fast method for calculating the full reflected pressure and displacement waves (i.e.,ย P-P, SV-SV, SH-SH, and P-SV/SV-P) in SWI of LWD considering different types of sources such as arcuate, monopole, and dipole transmitters. The analytical algorithm is developed by applying the reciprocity relation between the virtual force (displacement) sources located at the receiver position and the outside-borehole virtual forces that are equivalent to the reflections from the formation interfaces. Numerical experiments indicate that the analytical solutions agree well with the reference solutions from the 3D finite-difference time-domain method, demonstrating the accuracy and high efficiency of the analytical method. Based on the analytical solutions, we find that LWD reflected waves are much more sensitive to the azimuth than those in the wireline case, indicating that the availability of LWD is important for identifying the reflector azimuth. Furthermore, to enhance the reception efficiency of reflected waves, the LWD parameters are optimized. For slow formations, we suggest using a dipole source with dominant excitation-frequency band being from 1ย kHz to 3ย kHz. For fast formations, a dipole with wider excitation-frequency band from 1ย kHz to 5ย kHz is recommended. For all formations, recording pressure signals indicates much higher reception efficiency than the displacement signals.
- Geophysics > Seismic Surveying (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
Abstract In the current scenario of project management, where the agility and optimization of operations have been prioritized, the practice of logging while drilling (LWD) has gained space compared to traditional wireline logging. In theory, acquiring quality petrophysical properties during drilling brings greater agility in decision making about completion and optimizes operation costs. However, regarding borehole image logs, due to limitations in transmission capacity, the actual available data in real time contain about 50% (for resistivity images) of the full azimuth information, being insufficient for the identification of critical geological structures capable of impacting the communication between production or injection zones or the quality of cementation, such as fractures, caves, and geomechanical collapse zones. The toolโs memory data with the full information may take a few days after the end of drilling to be delivered by the service company, which in some cases is not enough for fast decision making regarding completion. In this work, we tested models based on generative adversarial neural networks (GANs) to reconstruct the complete memory data based on real-time input. As in conventional GAN schemes, a generator is trained to receive a real-time input and create a โmemory-likeโ image, while a discriminator is trained to tell real and fake images apart. To regularize the convergence of training, we used an architecture known in the literature as CycleGAN, where another generator-discriminator pair is trained simultaneously to do the reverse process, recreating the real-time data. Variations of the training process and data sets were used to generate different CycleGAN models. They were trained using logs of presalt reservoirs in Buzios Field, and performance was assessed on logging intervals not seen by the algorithms during training. The results achieved so far have been very promising, as in certain intervals, resultant models were able to capture the presence of fractures and caves. This methodology represents a way of circumventing telemetry limitations, where missing information is added indirectly to the real-time data as the artificial intelligence (AI) algorithm learns the main characteristics of a field/reservoir. Therefore, previous knowledge from the field can be used to continuously optimize future operations, efficiently incorporating the available database into the workflow of petrophysicists for the recognition of geological and geomechanical structures in time to support decision making in completion operations.
- North America > United States (1.00)
- South America > Brazil > Rio de Janeiro > South Atlantic Ocean (0.24)
- Geology > Rock Type > Sedimentary Rock (0.93)
- Geology > Geological Subdiscipline (0.69)
- Geology > Structural Geology > Tectonics > Salt Tectonics (0.35)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Borehole Seismic Surveying (0.35)
- Information Technology > Sensing and Signal Processing (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
- Information Technology > Architecture > Real Time Systems (1.00)
Abstract This paper describes a proposed high-specification standard format that is ideally suited for the data management of definitive records of wellbore logs. For this reason, it is a good standard for data exchange between applications. The format is suitable for complex three-dimensional (3D) data, including those generated by deep azimuthal resistivity (DAR) and ultradeep azimuthal resistivity (UDAR) tools, acoustic borehole reflection images, vertical seismic profiles (VSP), borehole imaging tools, multifingered caliper logs, and array data with multiple depths of investigation. It is applicable for use with logging-while-drilling (LWD) and wireline-conveyed logging tools. The format also naturally collapses down when utilized to store simple conventional logs that contain one value per depth in the wellbore. The proposed format provides spatial details of every data point collected by or interpreted from a wellbore-logging tool. The position of each data point is defined by reference back to the measure point of the sonde, which in turn is defined by the wellbore deviation survey and its coordinate reference system (CRS). Each data point in space may have an unrestricted number of parameters. An example might be most likely horizontal and vertical resistivity, maximum value based on uncertainty, minimum value based on uncertainty, and flags indicating the data position with respect to depth of detection (DOD). The new proposed format is so versatile. It is suitable as an Open Group Open Subsurface Data Universe (OSDU) standard to store and exchange all data measured by logging tools in a wellbore and can possibly be extended to include all well data (for example, core, cuttings, and more). The proposed format requires a detailed definition so that computer scientists can implement it in applications used for subsurface modeling. The OSDU will also require this detailed definition in order to adopt it as a standard.
- Europe (1.00)
- North America > United States (0.92)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
- Information Technology > Information Management (0.35)
- Information Technology > Modeling & Simulation (0.34)
- Information Technology > Data Science > Data Integration (0.34)
- Information Technology > Artificial Intelligence > Representation & Reasoning (0.34)
Abstract It is a standard workflow for oil and gas service companies to deliver the acquired logging data in standardized manner to owner companies. With digital transformation programs becoming popular and Petro-Technical experts adopting digital workflows, it hugely impacts the capability to turn around quicker and prompter deliverable generation. Acquired logging data is generally processed using interpretation methodologies and Interpretated copied delivered to client organization. Being continuous activity among service providers, any time saving achieved for generating such deliverables, has a multiplier effect in terms of efficiency and productivity for the resources. Digital workflow adopted for selection of pretest types for while drilling formation testing job consisted of processing of basic open hole logs and applying cut offs. Such cut off methodology has been adopted previously as well, but our process gives more flexibility to the user were based on the variations observed in petrophysical properties from experience could be utilized to come up with best possible test type. This increased the chances of success for formation testing operations while drilling. Another application discussed in this paper is Logging while drilling formation testing deliverable generation. Formation pressures and mobilities are output of the logging operation which are reported along with few pressure time curves and picks being made on the memory data for accuracy of the results. This is a continuous process for various clients where formation testing services are utilized during drilling. So deliverable generation process demands significant amount of time and effort, and it is a laborious and time-consuming process, primarily due to the repetitive nature of the deliverables. So, automation of such deliverable was carried out where significant number of efforts were saved, and quicker turnaround time was achieved saving man hours required. Introduction In today's oil and gas drilling industry, the challenges and costs associated with well drilling and completion have escalated. The utilization of the LWD Formation Pressure While Drilling (FPWD) tool service effectively addresses the uncertainties related to formation pressure during drilling, thereby diminishing risks and cost burdens. LWD measurements, particularly resistivity and sonic measurements, to anticipate pore pressure trends along the wellbore, play a crucial role in hazard management. These measurements, which serve as qualitative indicators for pore pressure prediction, necessitate calibration points.
- North America > United States > Texas (0.29)
- Asia > Middle East > UAE (0.28)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Formation test analysis (e.g., wireline, LWD) (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
- Information Technology > Artificial Intelligence > Machine Learning (1.00)
- Information Technology > Data Science (0.94)
Real-Time Rock-Properties Estimation for Geosteering: Statistical Rock-Physics-Driven Inversion of Seismic Acoustic Impedance and LWD Ultradeep Azimuthal Resistivity
Ciabarri, Fabio (Eni S.p.A (Corresponding author)) | Tarchiani, Cristiano (Eni S.p.A) | Alberelli, Gioele (Eni S.p.A) | Chinellato, Filippo (Eni S.p.A) | Mele, Maurizio (Eni S.p.A) | Marini, Junio Alfonso (Eni S.p.A) | Nickel, Michael (Schlumberger Stavanger Research) | Borgos, Hilde (Schlumberger Stavanger Research) | Dahl, Geir Vaaland (Schlumberger Stavanger Research)
Summary This work describes a statistical rock-physics-driven inversion of seismic acoustic impedance (AI) and ultradeep azimuthal resistivity (UDAR) log data, acquired while drilling, to estimate porosity, water saturation, and facies classes around the wellbore. Despite their limited resolution, seismic data integrated with electromagnetic resistivity log measurements improve the description of rock properties by considering the coupled effects of pore space and fluid saturation in the joint acoustic and electrical domains. The proposed inversion does not explicitly use a forward model, rather the correlation between the petrophysical properties and the resulting geophysical responses is inferred probabilistically from a training data set. The training set is generated by combining available borehole information with a statistical rock-physics modeling approach. In the inversion process, given colocated measurements of seismic AI and logging-while-drilling (LWD) electromagnetic resistivity data, the pointwise probability distribution of rock properties is derived directly from the training data set by applying the kernel density estimation (KDE) algorithm. A nonparametric statistical approach is used to approximate nonsymmetric volumetric distributions of petrophysical properties and to consider the characteristic nonlinear relationship linking water saturation with resistivity. Given an a priori facies classification template for the samples in the training set, it is possible to model the multimodal, facies-dependent behavior of the petrophysical properties, together with their distinctive correlation patterns. A facies-dependent parameterization allows the effect of lithology on acoustic and resistivity responses to be implicitly considered, even though the target properties of inversion are only porosity and saturation. To provide a realistic uncertainty quantification of the estimated rock properties, a plain Bayesian framework is described to account for rock-physics modeling error and to propagate seismic and resistivity data uncertainties to the inversion results. In this respect, the uncertainty related to the scale difference among the well-log data and seismic is addressed by adopting a scale reconciliation strategy. The main feature of the described inversion lies in its fast implementation based on a look-up table that allows rock properties, with their associated uncertainty, to be estimated in real time following the acquisition and inversion of UDAR data. This gives a robust, straightforward, and fast approach that can be effortlessly integrated into existing workflows to support geosteering operations. The inversion is validated on a clastic oil-bearing reservoir, where geosteering was used to guide the placement of a horizontal appraisal well in a complex structural setting. The results show that the proposed methodology provides realistic estimates of the rock-property distributions around the wellbore to depths of investigation of 50 m. These constitute useful information to drive geosteering decisions and can also be used, post-drilling, to update or optimize existing reservoir models.
- North America > United States > Texas (0.28)
- Europe > Austria (0.28)
- Research Report > New Finding (0.48)
- Research Report > Experimental Study (0.48)
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.31)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic processing and interpretation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Seismic modeling (1.00)
- (3 more...)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.87)
A fast algorithm for simulation and analysis of wavefields in acoustic single-well imaging of logging-while-drilling considering arbitrary types of sources
Xu, Jiaqi (Harbin Institute of Technology, Harbin Institute of Technology) | Hu, Hengshan (Harbin Institute of Technology) | Han, Bo (Harbin Institute of Technology)
Acoustic single-well imaging (SWI) of logging-while-drilling (LWD) is an advanced logging method in reservoir exploration, which uses reflected waves to detect the around-borehole geological structures and quickly determines the drilling direction for enhancing the drilling-encounter ratio and reducing the drilling risk. Forward acoustic modelling is a fundamental problem for SWI in LWD. Due to the complex structures, it is a challenge to simulate the wave propagation and investigate wavefield characteristics based on the forward model. Numerical modeling is a commonly used method for calculating wavefields, however it is too computationally expensive. In this study, we propose a fast method for calculating the full reflected pressure and displacement waves (i.e., P-P, SV-SV, SH-SH, and P-SV/SV-P) in SWI of LWD considering different types of sources including arcuate, monopole and dipole transmitters. The analytical algorithm is proposed by applying the reciprocity relation between the virtual force (displacement) sources located at the receiver position and the outside-borehole virtual forces which are equivalent to the reflections from the formation interfaces. Numerical experiments show that the analytical solutions agree well with the reference solutions from 3D finite-difference time-domain method, demonstrating the accuracy and high efficiency of the analytical method. Based on the analytical solutions, we find that LWD reflected waves are much more sensitive to the azimuth than those in the wireline case, showing that the availability of LWD is important for identifying the reflector azimuth. Furthermore, to enhance the reception efficiency of reflected waves, we present the optimized LWD parameters: For slow formations, we suggest using a dipole source with dominant excitation-frequency band being from 1 kHz to 3 kHz; For fast formations, a dipole with wider excitation-frequency band from 1 kHz to 5 kHz is recommended; For all formations, recording pressure signals shows much higher reception efficiency than the displacement signals.
- Geophysics > Seismic Surveying (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management (1.00)
Abstract Real time lithology information can tremendously impact drilling by providing input for geo-steering, casing shoe positioning, and subsurface hazards detection. Conventional logging while drilling (LWD) tools typically predict and provide lithology related information at a lag distance behind the drill bit. On the other hand, the sound of the drill bit is generated right at the bit position where it is cutting through the formation rocks. In theory, the sound generated when drilling through different rocks should change in accordance with the stiffness of the rocks. Hence, recording the sound of the drill bit and analyzing its characteristics, such as frequency and amplitude, can reveal information about lithology in real time. A system, hardware and software, is developed to record and process the drill bit sounds in real time. The key challenge in utilizing the sound of the drill bit is minimizing the noise effects generated due to drilling activities especially the rotation rate of the drill bit. We develop methods to minimize the rotation effects and test the methods in the lab settings to determine the optimum method. We then validate the findings from the lab testing with gathered data from a field trial.
- Geology > Rock Type (1.00)
- Geology > Geological Subdiscipline > Geomechanics (0.89)
- Well Drilling > Drill Bits (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (1.00)
- Well Drilling > Drilling Measurement, Data Acquisition and Automation > Logging while drilling (0.89)