Integration of Cutting Spectroscopy Analysis and Open-Hole Logs to Increase Evaluation Certainty of Complex Clastic Formations – Advantages and Limitations

2021 ◽  
Author(s):  
Ali Alqunais ◽  
Charles Bradford ◽  
Khalid Qubaisi
Keyword(s):  
Real Time ◽  
Gamma Ray ◽  
Drilling Fluid ◽  
Major Elements ◽  
Driving Mechanism ◽  
Formation Evaluation ◽  
Xrf Analysis ◽  
Real Time Analysis ◽  
Open Hole ◽  
The Impact

Abstract This paper presents an approach by integrating advanced cutting analysis, such as x-ray fluorescence (XRF), and open-hole logs for enhanced formation evaluation of complex clastic formations in near real-time. To verify the methodology, results of surface cuttings analyses are compared to and validated with downhole elemental spectroscopy measurements. In general, when the formation contains clays, the minimum logging requirement to evaluate clastic formations is a triple combo (density, neutron and resistivity) with spectral gamma ray (SGR) logs. In addition to correcting the impact of the drilling fluid additives and properties such as the presence of k-formate in mud, SGR logs become very crucial to differentiate clay types present in the formation. In the absence of SGR, advanced cuttings measurements can be utilized to provide elemental data of major elements including SGR components from the cuttings in near real-time. A comparison was made to evaluate the cuttings analysis as a replacement for SGR. As a part of this work and to validate the petrophysical evaluation results, downhole wireline SGR and elemental spectroscopy data were acquired and compared to the analysis using advanced cutting measurements. This work was conducted in a siliciclastic formation containing abrasive sandstones of mixed clean quartz and clay minerals. The analysis of cuttings XRF was integrated with basic downhole logs to quantify the clay typing required for representative formation evaluation and well geosteering. Limitations of this approach are identified in drilling complex clastic formations including cutting sampling frequency and effects of drilling including drilling fluid contamination, mud additives, drilling parameters and drilling driving mechanism. Controlling these factors has led to good results from cuttings measurements. The advanced cuttings XRF analysis was benchmarked with wireline SGR and elemental spectroscopy logs. This approach of using cuttings XRF analysis and basic open-hole logs is a valid option for geosteering in a complex clastic mineralogy formation and providing a near real-time formation evaluation in the absence of spectral gamma ray or elemental spectroscopy. XRF has been proven to provide near real-time analysis with improved reliability across bad hole, wider spectrum of elements and eliminate critical operations risk. Recommendations to optimize the parameters for reliable measurements will be discussed in this paper.

Real-Time Integrated LWD Formation Evaluation to Maximize Injectivity

2021 ◽  
Author(s):  
Idabagusgede Hermawanmanuab ◽  
Rayan Ghanim ◽  
Enrico Ferreira ◽  
Mohamed Gouda
Keyword(s):  
Real Time ◽  
Water Injection ◽  
Holistic Approach ◽  
Geological Structure ◽  
Target Zone ◽  
Horizontal Section ◽  
Well Placement ◽  
Formation Evaluation ◽  
Real Time Analysis ◽  
Resistivity Inversion

Abstract The main objective was to drill a power water horizontal injector within the sweet spot of a thin fractured and heterogeneous reservoir to achieve pressure stabilization in this producing field and an optimized sweep at the bottom of reservoir to maximize and prolong production. A traditional triple-combo logging while drilling (LWD) portfolio cannot fulfill these challenging reservoir navigation and formation evaluation (FE) objectives simultaneously because of the limited number of measurements. Hence, a more holistic approach is required to optimize the well placement via the integration of real-time LWD FE measurements to maximize the injectivity. An integrated LWD assembly was utilized and offset well FE data were studied to select the best zone for well placement to provide the best injectivity and production of the remaining oil towards the base of the reservoir. Extensive pre-well modeling was performed, based on offset well data with multiple scenarios reviewed to cover all eventualities. Another challenge was to place the wellbore in a relatively low resistive zone (water wet) in contrast to normal development wells where the wellbore is navigated in high resistive hydrocarbon bearing zones, so conventional distance to bed boundary mapping methodology was not applicable. To overcome this challenge; advanced Multi Component (MC) While Drilling resistivity inversion was proposed in conjunction with deep azimuthal resistivity technology. The benefit of this technique is in providing the resistivity of each layer within the depth of detection along with thickness and dip of each layer. Resistivity inversion results were correlated with nuclear magnetic resonance (NMR) porosity and volumetric data to identify the best zone for well placement. As MC inversion was able to map multiple layers within ~7 ft radius depth of detection, changing thicknesses and dip of each layer; the geosteering team was able to make proactive recommendations based on the inversion results. These proactive trajectory adjustments resulted in maintaining the wellbore within a thin target zone (1-3 ft in thickness) also confirmed by NMR and Formation Testing Service (FTS) in real-time, achieving excellent net-to-gross, which otherwise would not have been possible. The hexa-combo LWD assembly supported optimum well placement and provided valuable information about the geological structure through the analysis of high-resolution electrical images identifying the structural events which cause compartmentalization, confirmed by FTS results. This integrated LWD approach enabled proactive well trajectory adjustments to maintain the wellbore within the optimum porous, permeable and fractured target zone. This integrated methodology improved the contact within the water-injection target of the horizontal section, in a challenging thin reservoir and achieved 97.5 % exposure. Using an integrated LWD hexa-combo BHA and full real-time analysis the objective was achieved in one run with zero Non-Productive Time (NPT) and without any real-time or memory data quality issues.

Case Studies for the Successful Deployment of Wells Augmented Stuck Pipe Indicator in Wells Real Time Centre

2021 ◽  
Author(s):  
Meor M. Meor Hashim ◽  
M. Hazwan Yusoff ◽  
M. Faris Arriffin ◽  
Azlan Mohamad ◽  
Tengku Ezharuddin Tengku Bidin ◽  
...  
Keyword(s):  
Real Time ◽  
Case Studies ◽  
Drilling Fluid ◽  
Drill String ◽  
Drilling Operation ◽  
Cost Impact ◽  
Drilling Parameters ◽  
The Impact ◽  
Productive Time ◽  
Specific Challenge

Abstract The restriction or inability of the drill string to reciprocate or rotate while in the borehole is commonly known as a stuck pipe. This event is typically accompanied by constraints in drilling fluid flow, except for differential sticking. The stuck pipe can manifest based on three different mechanisms, i.e. pack-off, differential sticking, and wellbore geometry. Despite its infrequent occurrence, non-productive time (NPT) events have a massive cost impact. Nevertheless, stuck pipe incidents can be evaded with proper identification of its unique symptoms which allows an early intervention and remediation action. Over the decades, multiple analytical studies have been attempted to predict stuck pipe occurrences. The latest venture into this drilling operational challenge now utilizes Machine Learning (ML) algorithms in forecasting stuck pipe risk. An ML solution namely, Wells Augmented Stuck Pipe Indicator (WASP), is developed to tackle this specific challenge. The solution leverages on real-time drilling database and supplementary engineering design information to estimate proxy drilling parameters which provide active and impartial pattern recognition of prospective stuck pipe events. The solution is built to assist Wells Real Time Centre (WRTC) personnel in proactively providing a holistic perspective in anticipating potential anomalies and recommending remedial countermeasures before incidents happen. Several case studies are outlined to exhibit the impact of WASP in real-time drilling operation monitoring and intervention where WASP is capable to identify stuck pipe symptoms a few hours earlier and provide warnings for stuck pipe avoidance. The presented case studies were run on various live wells where restrictions are predicted stands ahead of the incidents. Warnings and alarms were generated, allowing further analysis by the personnel to verify and assess the situation before delivering a precautionary procedure to the rig site. The implementation of the WASP will reduce analysis time and provide timely prescriptive action in the proactive real-time drilling operation monitoring and intervention hub, subsequently creating value through cost containment and operational efficiency.

scholarly journals Monitoring and characterization of vibration and shock conditions aboard high-performance marine craft

2018 ◽  
Vol 233 (4) ◽  
pp. 1068-1081
Author(s):  
Manudul Pahansen de Alwis ◽  
Karl Garme
Keyword(s):  
Real Time ◽  
High Speed ◽  
High Performance ◽  
Severity Index ◽  
Irregular Waves ◽  
Vibration Exposure ◽  
Data Set ◽  
Real Time Analysis ◽  
Impact Acceleration ◽  
The Impact

The stochastic environmental conditions together with craft design and operational characteristics make it difficult to predict the vibration environments aboard high-performance marine craft, particularly the risk of impact acceleration events and the shock component of the exposure often being associated with structural failure and human injuries. The different timescales and the magnitudes involved complicate the real-time analysis of vibration and shock conditions aboard these craft. The article introduces a new measure, severity index, indicating the risk of severe impact acceleration, and proposes a method for real-time feedback on the severity of impact exposure together with accumulated vibration exposure. The method analyzes the immediate 60 s of vibration exposure history and computes the severity of impact exposure as for the present state based on severity index. The severity index probes the characteristic of the present acceleration stochastic process, that is, the risk of an upcoming heavy impact, and serves as an alert to the crew. The accumulated vibration exposure, important for mapping and logging the crew exposure, is determined by the ISO 2631:1997 vibration dose value. The severity due to the impact and accumulated vibration exposure is communicated to the crew every second as a color-coded indicator: green, yellow and red, representing low, medium and high, based on defined impact and dose limits. The severity index and feedback method are developed and validated by a data set of 27 three-hour simulations of a planning craft in irregular waves and verified for its feasibility in real-world applications by full-scale acceleration data recorded aboard high-speed planing craft in operation.

NOAA'S Hurricane Intensity Forecasting Experiment: A Progress Report

2013 ◽  
Vol 94 (6) ◽  
pp. 859-882 ◽  
Author(s):  
Robert Rogers ◽  
Sim Aberson ◽  
Altug Aksoy ◽  
Bachir Annane ◽  
Michael Black ◽  
...  
Keyword(s):  
Life Cycle ◽  
Tropical Cyclone ◽  
Real Time ◽  
Doppler Radar ◽  
Multiple Scales ◽  
Statistical Prediction ◽  
Intensity Change ◽  
Turbulence Scale ◽  
Real Time Analysis ◽  
The Impact

An update of the progress achieved as part of the NOAA Intensity Forecasting Experiment (IFEX) is provided. Included is a brief summary of the noteworthy aircraft missions flown in the years since 2005, the first year IFEX flights occurred, as well as a description of the research and development activities that directly address the three primary IFEX goals: 1) collect observations that span the tropical cyclone (TC) life cycle in a variety of environments for model initialization and evaluation; 2) develop and refine measurement strategies and technologies that provide improved real-time monitoring of TC intensity, structure, and environment; and 3) improve the understanding of physical processes important in intensity change for a TC at all stages of its life cycle. Such activities include the real-time analysis and transmission of Doppler radar measurements; numerical model and data assimilation advancements; characterization of tropical cyclone composite structure across multiple scales, from vortex scale to turbulence scale; improvements in statistical prediction of rapid intensification; and studies specifically targeting tropical cyclogenesis, extratropical transition, and the impact of environmental humidity on TC structure and evolution. While progress in TC intensity forecasting remains challenging, the activities described here provide some hope for improvement.

scholarly journals Multi-resolution characterization of the COVID-19 pandemic: A unified framework and open-source tool

2021 ◽  
Author(s):  
Andy Shi ◽  
Sheila M. Gaynor ◽  
Corbin Quick ◽  
Xihong Lin
Keyword(s):  
Open Source ◽  
Real Time ◽  
Linear Models ◽  
Time Frame ◽  
Reproduction Rate ◽  
Time Data ◽  
Unified Framework ◽  
Real Time Analysis ◽  
Multiple Metrics ◽  
The Impact

Amidst the continuing spread of COVID-19, real-time data analysis and visualization remain critical to track the pandemic's impact and inform policy making. Multiple metrics have been considered to evaluate the spread, infection, and mortality of infectious diseases. For example, numbers of new cases and deaths provide measures of absolute impact within a given population and time frame, while the effective reproduction rate provides a measure of the rate of spread. It is critical to evaluate multiple metrics concurrently, as they provide complementary insights into the impact and current state of the pandemic. We describe a unified framework for estimating and quantifying the uncertainty in the smoothed daily effective reproduction number, case rate, and death rate in a region using log-linear models. We apply this framework to characterize COVID-19 impact at multiple geographic resolutions, including by US county and state as well as by country, demonstrating the variation across resolutions and the need for harmonized efforts to control the pandemic. We provide an open-source online dashboard for real-time analysis and visualization of multiple key metrics, which are critical to evaluate the impact of COVID-19 and make informed policy decisions.

scholarly journals The ECMWF Ocean Analysis System: ORA-S3

2008 ◽  
Vol 136 (8) ◽  
pp. 3018-3034 ◽  
Author(s):  
Magdalena A. Balmaseda ◽  
Arthur Vidard ◽  
David L. T. Anderson
Keyword(s):  
Real Time ◽  
Sea Level ◽  
Bias Correction ◽  
Seasonal Forecasts ◽  
Ocean Reanalysis ◽  
Historical Representation ◽  
Real Time Analysis ◽  
Sea Level Anomalies ◽  
Analysis System ◽  
The Impact

Abstract A new operational ocean analysis/reanalysis system (ORA-S3) has been implemented at ECMWF. The reanalysis, started from 1 January 1959, is continuously maintained up to 11 days behind real time and is used to initialize seasonal forecasts as well as to provide a historical representation of the ocean for climate studies. It has several innovative features, including an online bias-correction algorithm, the assimilation of salinity data on temperature surfaces, and the assimilation of altimeter-derived sea level anomalies and global sea level trends. It is designed to reduce spurious climate variability in the resulting ocean reanalysis due to the nonstationary nature of the observing system, while still taking advantage of the observation information. The new analysis system is compared with the previous operational version; the equatorial temperature biases are reduced and equatorial currents are improved. The impact of assimilation in the ocean state is discussed by diagnosis of the assimilation increment and bias correction terms. The resulting analysis not only improves the fit to the data, but also improves the representation of the interannual variability. In addition to the basic analysis, a real-time analysis is produced (RT-S3). This is needed for monthly forecasts and in the future may be needed for shorter-range forecasts. It is initialized from the near-real-time ORA-S3 and run each day from it.

Machine Learning Prediction of Formation Evaluation Logs in the Gulf of Mexico

2021 ◽  
Author(s):  
Brian LeCompte ◽  
Tosin Majekodunmi ◽  
Mike Staines ◽  
Gareth Taylor ◽  
Barry Zhang ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Gulf Of Mexico ◽  
Real Time ◽  
Network Architecture ◽  
Gamma Ray ◽  
Risk Mitigation ◽  
Seismic Inversion ◽  
Log Data ◽  
Formation Evaluation

Abstract The objective of the paper is to describe the application of artificial intelligence software to predict formation evaluation logs (compressional sonic, shear sonic and density) using only gamma ray, and resistivity log data and drilling dynamics data as received by the electronic drilling recorder (EDR). The software was applied real-time as a well was being drilled in deepwater Gulf of Mexico. Thorough examination and conditioning of EDR and wireline data give way to a training model construction for the artificial neural network (ANN) using full suites of log-data in offset wells. Next, a neural network architecture and associated hyperparameters are chosen and tested. The fully trained and validated model is applied to the gamma ray, resistivity and EDR of the target well while drilling. Real-time EDR and wireline data flow via WITSML from rig to cloud and data is delivered to the client. The results of the study indicate the simulated log data were comparable to those measured from conventional logging tools over the study area. In both blind well tests the density agreed with the conventional log results within 1.1 % and the compressional within 2.51 % (Figure 1). Each of these is well within the range of variance expected of repeat runs of a conventional logging tool. A primary driver for near real-time logs was to confirm structural depth of the target sands along the well bore. There was a depleted sand below the expected TD of the well that, if encountered, could have led to total losses and possible loss of the wellbore. It was critical to have real-time logs to characterize the sands above the depleted sand, using every possible petrophysical and geologic character to refine the log correlation. This integration of all the logs provided the best interpretation of the sand quality and led toward the completion decision. AI-based logs are a highly cost-effective alternative to LWD logging. It presents an environmentally friendly approach as there is no logging personnel on-site and no expensive and potentially dangerous nuclear sources in the hole The deployment of this patented, machine learning-driven, real-time simulation of formation evaluation logs is unique in using only gamma ray, resistivity and drilling data. It is particularly useful in the overburden section where formation evaluation tools are often not run for cost reasons, in side-tracks, in HP/HT settings and operational risk mitigation. It provides additive data for other petrophysical/QI/rock property analyses including seismic inversion, shale content, porosity, log QC/editing, real-time LWD, drilling optimization, etc.

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