Application of Geomechanics for Successful Drilling of Onshore Well with Multiple Challenges of Losses and Intense Gas Cut Mud in Naturally Fractured Zone.

2021 ◽  
Author(s):  
Bassey Akong ◽  
Samuel Orimoloye ◽  
Friday Otutu ◽  
Goodluck Mfonnom ◽  
Akinwale Ojo ◽  
...  
Keyword(s):  
Improve Performance ◽  
Comprehensive Review ◽  
Wellbore Instability ◽  
Safe Delivery ◽  
Instability Problem ◽  
Naturally Fractured ◽  
Lost Time ◽  
Multiple Challenges ◽  
Gradient Approach ◽  
Productive Time

Abstract Drilling of deviated development wells in O-field X has proven to be challenging. Drilling experience in several wells within the field has different issues of wellbore instability, most recent is when traversed through a pre-existing/naturally fractured intervals. Numerous lost-time incidents related to wellbore instability-related problems were experienced, ranging from tight hole (remedied by reaming) to Overpulls, pack-off followed by stuck pipe, fill on-bottom to difficulties in running casing, and tensile cavings to high gas associated with drilling breaks. These problems were observed particularly when drilling previous and current wells in the O-field X. Many of the wells in O-field X were drilled with water-based mud (WBM) for top-hole and POBM for intermediate hole section. However, drilling the most recent well became more challenging with issues of severe losses just below the 13-3/8inch shoe where an interbedded lignite formation characterized with pre-existing fractures was drilled through. Faced with continual non-productive time (NPT), the predrill GeoMechanical report was immediately reviewed coupled with the stress caging procedure adopted to further mitigate the loss circulation wellbore instability problem. The recommendations arising from the comprehensive review of the GeoMechanical window, stress caging and drilling experience analyses was immediately implemented to improve performance which has helped in drilling the well to final completion. This paper highlights the importance of integrating GeoMechanics, stress caging and with proper drilling practices which has helped in delivery of the candidate well. A full-scale GeoMechanical window review was proactively adopted considering the mid-line collapse gradient approach for unconsolidated, naturally fracture formations and critical depleted intervals. All the above strategies were adopted, which assisted in safe delivery of candidate well in O-field X.

Multi Well Analysis Data Processing for Event Analysis and Mitigation

2021 ◽  
Author(s):  
Vallet Laurent ◽  
Gutarov Pavel ◽  
Chevallier Bertrand ◽  
Converset Julien ◽  
Paterson Graeme ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Analysis ◽  
New Technologies ◽  
Early Stage ◽  
Mitigation Measures ◽  
Construction Process ◽  
Field Development ◽  
Drilling Data ◽  
Lost Time ◽  
Productive Time

Abstract In the current economic environment, delivering wells on time and on budget is paramount. Well construction is a significant cost of any field development and it is more important than ever to minimize these costs and to avoid unnecessary lost time and non-productive time. Invisible lost time and non-productive time can represent as much as 40% of the cost of well construction and can lead to more severe issues such as delaying first oil, losing the well or environmental impact. There has been much work developing systems to optimize well construction, but the industry still fails to routinely detect and avoid problematic events such as stuck pipe, kicks, losses and washouts. Standardizing drilling practice can help also to improve the efficiency, this practice has shown a 30% cost reduction through repetitive and systematic practices, automation becomes the key process to realize it and Machine Learning introduced by new technologies is the key to achieve it. Drilling data analysis is key to understanding reasons for bad performances and detecting at an early stage potential downhole events. It can be done efficiently to provide to the user tools to look at the well construction process in its whole instead of looking at the last few hours as it is done at the rig site. In order to analyze the drilling data, it is necessary to have access to reliable data in Real-Time to compare with a data model considering the context (BHA, fluids, well geometry). Well planning, including multi-well offset analysis of risks, drilling processes and geology enables a user to look at the full well construction process and define levels of automation. This paper applies machine learning to a post multi-well analysis of a deepwater field development known for its drilling challenges. Minimizing the human input through automation allowed us to compare offset wells and to define the root cause for non-productive time. In our case study an increase of the pressure while drilling should have led to immediate mitigation measures to avoid a wiper trip. This paper presents techniques used to systematize surface data analysis and a workflow to identify at an early stage a near pack off which was spotted in an automatic way. The application of this process during operations could have achieved a 10%-time reduction of the section 12 ¼’’.

scholarly journals Building 1D Mechanical Earth Model for Zubair Oilfield in Iraq

2020 ◽  
Vol 26 (5) ◽  
pp. 47-63
Author(s):  
Aows Khalid Neeamy ◽  
Nada Sabah Selman
Keyword(s):  
Earth Model ◽  
Drilling Process ◽  
Suitable Alternative ◽  
Wellbore Instability ◽  
Drilling Operations ◽  
Mechanical Earth Model ◽  
Alternative Solutions ◽  
Drilling Time ◽  
Productive Time ◽  
Critical Limits

Many problems were encountered during the drilling operations in Zubair oilfield. Stuckpipe, wellbore instability, breakouts and washouts, which increased the critical limits problems, were observed in many wells in this field, therefore an extra non-productive time added to the total drilling time, which will lead to an extra cost spent. A 1D Mechanical Earth Model (1D MEM) was built to suggest many solutions to such types of problems. An overpressured zone is noticed and an alternative mud weigh window is predicted depending on the results of the 1D MEM. Results of this study are diagnosed and wellbore instability problems are predicted in an efficient way using the 1D MEM. Suitable alternative solutions are presented ahead to the drilling process commences in the future operations.

The Hard Case for Whole Drilling Optimization

2021 ◽  
Author(s):  
Carlos Damski ◽  
Sameh El Afifi
Keyword(s):  
Service Providers ◽  
Direct Calculation ◽  
Total Production ◽  
Holistic View ◽  
Operational Risks ◽  
Drilling Optimization ◽  
Lost Time ◽  
Unique Framework ◽  
The Right ◽  
Productive Time

Abstract Today every Oil & Gas company is searching for the elusive drilling optimization process. Authors argue that a global drilling optimization is only achieved calculating the actual ROI – based on money spent in drilling vs total production of the well. As this is impractical, this paper presents a framework to measure engineering and management aspects of this optimization. Engineering approach looks into "doing things right," while managerial attitude is "doing the right things." Drilling optimization is centered in using existing (and upcoming) data from rig and its analyses. Engineers look into hydraulics, WOB, etc., with the purpose to calculate ideal/best ROP parameters and eventually to avoid problems, such as stuck pipe. This is done by direct calculation and/or running simulated models to spot deviations. Management is concerned with relative efficiency of the process (KPIs) compared to a baseline (offset wells, planned durations, technical limits, etc.). They concentrate at comparisons and focus at how to mitigate operational risks (time, costs, HSE, etc.) while producing the "best well". Those two intertwined optimization processes are depicted and explained in the next sessions. Authors' experience has shown that TL (Technical Limit), ILT (Invisible Lost Time) and NPT (Non-Productive time) are façades from the engineering and management efforts in drilling optimization. For example, there is no unique way to describe "Technical Limit" in drilling. We will describe the technical components for it under physics and models, as well as under historical-coaching-KPI approach. Same for ILT and NPT. Under a unique framework, users can understand and clarify the confusion in the current marketplace to better data and data processing to achieve optimization. The so called "data analytics" is dissected and formalized so all parties involved: technicians, service providers, operators, equipment suppliers, managers, finances, etc., can fully understand where data can be used (also how they are collected and quality checked) and what processes are needed to achieve each step of the drilling optimization. Unlike any product or service available today, the framework described in this article looks in the drilling optimization with a holistic view. Efforts so far have been scattered and there is a lack of an overall framework. The best results come from the combination of those two approaches.

An Integrated Approach to Efficient Drilling through Unstable Coal Intervals Using Different Types of Mud in the Yamal Region

2021 ◽  
Author(s):  
Alexander Viktorovich Kabanov ◽  
Aydar Ramilevich Galimkhanov ◽  
Andrey Borisovich Kharitonov ◽  
Alexander Mikhailovich Matsera ◽  
Valery Viktorovich Pogurets ◽  
...  
Keyword(s):  
Drilling Fluid ◽  
Integrated Approach ◽  
Drilling Mud ◽  
Wellbore Instability ◽  
Engineering Approach ◽  
Well Design ◽  
Drilling Muds ◽  
Productive Time ◽  
Nenets Autonomous ◽  
Selection Of

Abstract This article is a description of an integrated engineering approach to solutions selection for efficient and safe drilling of unstable intervals represented by interbedded coal and argillite layers. Due to specific features of these formations, any significant mechanical stress, as well as penetration of drilling fluid filtrate, may lead to wellbore instability regardless of the drilling mud type used. The paper presents a description of the features of drilling in unstable intervals with various types of drilling muds (WBM/OBM) in Yamalo-Nenets Autonomous Okrug (YNAO). Experience has shown that drilling through coal intervals prone to instability may cause significant non-productive time (NPT). Such wells should be designed with an integrated engineering approach, which covers the entire cycle: starting with the well path planning, casing setting depths selection, BHA design and drilling regimes of the risk interval. No less important, detailed development of solutions for drilling muds. During the study the main causes of issues in wells drilled through the interbedded formations of coal and argillites in two fields were identified. As a result, a set of measures was developed to minimize risks for each type of mud (OBM and WBM): – Revision of the initial well design solutions. Selection of optimal mud weight based on the experience gained and the geomechanical model – Revision of chemicals concentrations together with the use of additional additives – Placement of stabilizing pills across unstable intervals – Well path optimization – Development of safe drilling procedures. The measures developed for various types of drilling muds allowed minimizing the NPT and successfully completing the wells on time. The experience gained formed the basis for recommendations to prevent issues associated with the coal layers instability in the region.

Drilling in Slips: Strategies to Measure the Invisible Lost Time, Technical Limits Definition, Using Standard Analytics and Machine Learning Algorithms

2021 ◽  
Author(s):  
Silvia Mora ◽  
Damian Martinez
Keyword(s):  
Machine Learning ◽  
Machine Learning Algorithms ◽  
Base Line ◽  
Depth Range ◽  
Learning Mechanisms ◽  
Data Set ◽  
Lost Time ◽  
The Cost ◽  
Productive Time ◽  
The Invisible

Abstract Drilling is probably the most critical, complex, and costly operation in the oil and gas industry and unfortunately, errors made during the activities related are very expensive. Therefore, inefficient drilling activities such as connection duration outside of optimal times can have a considerable financial impact, so there is always a need to improve drilling efficiency. It is for this fact, that the measure of different behaviors and the duration of the drilling activities represent a significant opportunity in order to maximize the cost saving per well or campaign. Reducing the cost impact and maximizing the drilling efficiency are defined by the way used to calculate the perfect well time by the technical limit, non-productive time (NPT), and invisible lost time (ILT), in an operating company drilling plan. Different approaches to measure the invisible lost time that could be present in the in slips activity on the drilling operation are compared. Results show the differences between multiple techniques applied in real environments coming from a cloud platform. The methodologies implemented are based on the following scenarios, the first one use a combination of a custom technical limit based on technical experience, the historical data limit using standard measures (mean, average, quartiles, standard deviation, etc.), and a depth range variable (phases) differentiation, initial, intermediate, and final hole sizes is used. A complexity comparison uses the rig stand and phase footage variables for base line (count and duration) definition per phase, the non-productive time activities exclusion and data replace techniques mixing with an out of standard time detection in slips behavior (motor assemblies, bit replacing, bottom hole assembly (BHA), etc.) using standard and machine learning mechanisms. A final methodology implements an in slip ILT by technical limit definition using machine learning. The results using the same data set (set of wells) and coming from the different methods has been evaluated according to the total invisible lost time calculated per phase, percentage of activities evaluated with invisible lost time per phase and the variation of ILT considering the activities defining the technical limit. Finally, the potential implementation by any operator can be evaluated for these methodologies according to their specific requirements. This analysis creates a guideline to operating companies about multiple techniques to calculate ILT, some using innovative procedures applied on machine learning models.

scholarly journals The Effect of Invisible Lost Time on Drilling Performance of Geothermal Wells

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Fernandez Sabar Hasudungan Pangaribuan ◽  
Sugiatmo Kasmungin ◽  
Suryo Prakoso
Keyword(s):  
Performance Indicator ◽  
Night Shift ◽  
Drilling Performance ◽  
Open Hole ◽  
Geothermal Wells ◽  
Lost Time ◽  
Geothermal Drilling ◽  
The Cost ◽  
Productive Time ◽  
Better Than

<em>Drilling activity has been focused in time on each activity to reach target depth (TD) immediately and efficient in cost. The priority also aimed to Geothermal drilling by doing specific measurement on Invisible Lost Time (ILT) as new focus to perform. Time becomes main aspect which it would affect the cost, therefore it is important to complete the well in time manner. The research was done to analyze the offset well of well A, B, C and D in order to identify Productive Time and Non Productive Time. Key Performance Indicator (KPI) has been identified from each activity also targeted from two wells of well B dan Well D due to time efficiency used during operation. The method used by comparing offset wells then continue to identify each KPI by measuring each activity based on ASCII time and Daily Drilling Report (DDR). The result from offset wells showed inefficiency in time with Flat time 49%, Drilling 42% and non-flat time (NPT) 9% from 28 days without completion. KPI based on the crew performance has confirmed that day shift crew performed better than night shift crew. KPI on rate of penetration (ROP) on day shift crew at 6 m/hr and night crew at 3 m/hr. KPI on Weight to Weight on day shift crew at 28.43 minute/stand faster than night shif crew at 34.65 minute/stand. KPI on Tripping in cased hole on day shift crew at 4.5 minute/stand faster than night crew shift at 4.6 minute/stand. KPI on Tripping in open hole on day shift crew at 2.7 minute/stand faster than night shift crew at 3.7 minute/stand. KPI on Tripping out open hole on day shift crew at 3.0 minute/stand slower than night shift crew at 2.8 minute/stand. KPI on Tripping out cased hole on day shift crew at 3.36 minute/stand faster than night crew shift at 3.74 minute/stand. ILT from both wells to 20 % or 5 days inefficiency on each well. It detects of potential savings to 10 billion rupiah from both wells.</em>

scholarly journals Core Competencies of Truck Drivers Responding to Emergencies during Transportation of Hazardous Materials

2020 ◽  
Vol 10 (27) ◽  
pp. 200909
Author(s):  
Adnan Fazal Manzoor
Keyword(s):  
Core Competencies ◽  
Truck Drivers ◽  
Middle Income ◽  
Safe Delivery ◽  
Emergency Responders ◽  
Study Protocols ◽  
Effective Manner ◽  
Financial Interests ◽  
Hazmat Transportation ◽  
Multiple Challenges

Background. Hazardous material (HAZMAT) transportation drivers are responsible for safe delivery of consignments and face multiple challenges carrying out their duties. Drivers are also the first to respond to emergencies and accidents. Objectives. The purpose of the present study was to identify the essential competencies needed by HAZMAT transportation drivers to deal with emergencies. Methods. Three rounds of focus groups were conducted using expert panels comprised of HAZMAT specialists, health, safety and emergency representatives, security experts and transportation advisors from June to July 2019. The panel discussed competencies, gathered from a literature review, for emergency responders. Results. The panel identified six (6) core and 23 sub-competencies of HAZMAT drivers. This is the first study in low- and middle-income countries (LMIC) to identify core competencies of HAZMAT truck drivers. Conclusions. The integration of these competencies into a development and training program for drivers will better enable drivers to handle emergencies in an efficient and effective manner. Participant Consent. Obtained Ethics Approval. The Graduate Advisory Committee of Comsats University approved study protocols. Participant Consent. Obtained Competing Interests. The authors declare no competing financial interests.

Wellbore Instability of Directional Wells in Laminated and Naturally Fractured Shales

2009 ◽  
Vol 12 (2) ◽  
pp. 119-130 ◽  
Author(s):  
Talal M. Al-Bazali ◽  
Jianguo Zhang ◽  
Chris Wolfe ◽  
Martin E. Chenevert ◽  
Mukul M. Sharma
Keyword(s):  
Wellbore Instability ◽  
Naturally Fractured
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