bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recognition and Mitigation of the BHA Lateral Vibration Chatter Mode
Authors: Bailey Jeffrey R. , Lathi Harshit , Prim Matthew T. , Carson Andrew D. , Tenny Matthew J. , Payette Gregory S. 
Published: November 2019

Abstract
Lateral vibration modeling of certain BHA (bottomhole assembly) designs has shown great sensitivity to the proximity of stabilizer blades. This paper will explore the nature of the vibrational dysfunction that we call BHA chatter. A frequency-domain model that has been field-proven shows how this dysfunction occurs, its rotary speed dependence, and mitigation methods and results.
A frequency-domain BHA lateral vibration model will be used to illustrate the role of the nodal point constraint in the determination of the dynamic side forces acting at stabilizer and LWD tool blade borehole contacts. These contact forces may be strong functions of rotary speed and BHA contact spacing, especially if the spacing is close.
The relationship between the dynamic contact forces and vibration index model results will be described in relation to the solution to the lateral vibration model. Examination of the dynamic contact side forces associated with these vibration indices reveals the nature of the dysfunction that the indices represent.
The contact forces that push a stabilizer blade to be constrained within a borehole include both static and dynamic components. The static forces are well understood. However, the dynamic forces are difficult to visualize as they are generated by the BHA in motion, and a well-formulated dynamic model is required to evaluate these forces.
Dynamic dysfunction at a particular location along the BHA is revealed by examining the underlying states of a dynamic model. Charts of the dynamic contact side force quantify the amount of dysfunction. Vibration indices comprising the integrated, length-averaged bending strain energy provide a good summary of the overall BHA response that is particularly useful in BHA design investigations, but it is the dynamics of the individual contact points that drive the dynamic response of the model.
Examples of field BHA designs illustrate both good and bad drilling results, generally in agreement with expectations based on the modeling. The literature is full of references to the whirl mode of lateral vibrations. This is commonly accepted. Chatter is a different mode that occurs primarily in response to the spacing of blade contacts. It is difficult for two blades that are close together to simultaneously serve as nodal points. A lateral vibration wave propagating along the BHA may generate alternating wall contact at the two blades, causing a dynamic chatter dysfunction.
Alleviation of Scaling Concerns and Controlling of Chemical EOR Under-Performance Risk for a Giant Sandstone Reservoir in North Kuwait
Authors: Al-Murayri Mohammed T. , Kamal Dawood S. , Khan Mohammad Y. , Al-Mayyan Haya E. , Abu Shiekah Issa , Shahin Gordon T. , Shukla Shunahshep R. , Bouwmeester Ron , de Kruijf Sander 
Published: November 2019

Abstract
An inverted 5-spot Alkaline Surfactant Polymer (ASP) pilot is planned for a giant sandstone reservoir in North Kuwait. Despite the development of a robust lab-optimized ASP formulation at reservoir temperature (90°C) and the execution of a successful Single Well Chemical Tracer Test (SWCTT), the combination of high temperature and divalent ion concentration (∼20,000 ppm) makes the implementation of a successful multi-well ASP pilot very difficult mainly due to the challenge of inorganic carbonate scale. This paper presents some unique challenges in connection with the design of an inverted 5-spot ASP pilot and discusses practical strategies to mitigate them.
Due to the high divalent ion concentration in the formation brine, the design basis for the planned chemical EOR pilot requires pre-flushing the reservoir using softened seawater prior to ASP injection. In the base-case scenario for the pilot, injection and production within the pattern were balanced to target a Voidage Replacement Ratio (VRR) of 1. However, it was realized that such a pre-flush strategy would still present significant carbonate scaling risk at the producers. In view of that, an extended softened-water pre-flush strategy (over-flush) was considered to alleviate the anticipated scaling concerns.
Simulations were carried out to explore various scenarios to work out the optimal over-flush strategy for the pilot to mitigate the potential for scale formation at the producers. It was realized that over-flushing the hot reservoir brine by large volumes of cooler surface water could result in significant cooling of the reservoir prior to ASP injection. This change in reservoir temperature compromises the performance the original lab-optimized formulation that was designed considering a reservoir temperature of 90°C. In view of that, careful re-tuning of the chemical formulation was necessary to make it robust for pilot conditions post softened water over-flushing.
Predict Oil Production from Geological and Petrophysical Data Before Hydraulic Fracturing Using an Improved Particle Swarm Optimization Based Least Squares Support Vector Machine
Authors: Feng Cheng , Li Jiahong , Feng Ziyan , Zhong Yuntao , Zhang Ning , Mao Zhiqiang 
Published: November 2019

Abstract
For no natural productivity, hydraulic fracturing is widely used in unconventional reservoirs. Thus, oil production prediction before hydraulic fracturing is crucial. In general, it is usually obtained based on percolation theory and fracture geometrical model from engineering data. However, before hydraulic fracturing, the obtained data are mainly geological and petrophysical data. Hence, predicting oil production from them before hydraulic fracturing can make a lot of sense for guiding fracturing design. Although geological and petrophysical data have complex and nonlinear relation with oil production after hydraulic fracturing, least squares support vector machine (LSSVM) is very suitable for such high-dimensional and nonlinear problem with small datasets. As the performance of LSSVM highly depends on parameter selection, an improved LSSVR is designed based on particle swarm optimization (PSO). The selected study area is tight oil reservoirs of Chang 8 Formation, Triassic, Ordos Basin, China. In order to build a reliable data-driven oil production prediction model, a systematic formation evaluation workflow is proposed. Firstly, choose wells with similar hydraulic fracturing type in the study area, which is the base. Secondly, the oil production prediction problem is converted into a classification problem by dividing the oil production into four levels. Thirdly, the dataset of 24 geological, petrophysical and engineering parameters from 85 wells are selected and constructed, reflecting lithology, physical property, saturation, rock mechanics, thickness and facies. Fourthly, 8 parameters, including density, the difference of neutron and density porosity, permeability, water saturation, effective thickness, Poisson's ratio, interlayer stress difference and displacement amount, are optimized as sensitive ones by principal component analysis (PCA). Fifthly, the data from 85 wells are separated into two categories: training and testing data, according to the proportion of 70% and 30%, respectively. The former are used to train the model, while the latter are used for verification. Sixthly, the improved PSO based LSSVM and the LSSVM are trained and tested via the dataset respectively. The tested results present that the coincidence rate of the prediction of the two methods are 88.06% and 81.16% respectively. This work verifies that predicting oil production from geological and petrophysical data before hydraulic fracturing via an improved LSSVM is feasible and cost-effective, which can be important for guiding fracturing design and providing scientific basis for deployment of development program.
Selection of Barium Sulphate/Barite Dissolver Chemical through Establishment of Standard Laboratory Screening Protocols
Authors: Raja Sahar Raja Nor , W Mohamad Wan Amni , Rustam Ali Khan Ema Farima , Mohd Hatta Siti Aishah 
Published: November 2019

Abstract
Barium Sulfate (Barite, BaSO4) scale is the most difficult scale to remove due to its low inherent water solubility. After more than 10 years of production in Field A, barite scales are recently found deposited in the tubing and at the topside in one of the oil producer wells. In this case, barite scales are precipitated through mixing of formation water containing high concentration of barium ions and injection seawater with high sulphate concentrations. Successful method of removing barite scales is using chelant based chemicals i.e. EDTA/DTPA. The best possible way to reduce failure risks of the pilot removal application using these chemicals for Field A is through series of lab testing. This paper describes the selection of barite scales dissolver chemicals through establishment of standard laboratory screening protocols prior to field applications in PETRONAS.
In the industry, there are various experimental methods to study the effect of barite dissolver chemicals on barite scales dissolution. Since PETRONAS has just recently encountered barite scales deposition issues, it is crucial to have a standardized protocol to ensure the effectiveness of the chosen chemicals to remediate the issue immediately. The protocol developed was based on various references and citations from other operators and chemical service provider.
The protocols are divided into three (3) sections in series i.e. characterization of deposit samples mineralogy, barite dissolution and chemical compatibility testing. Prior to barite dissolution tests, deposit samples collected from the wells/topsides are characterized through XRD/XRF analysis, organic scale identification/analysis and acid solubility test. Finally, the most effective barite dissolver chemical will undergo chemical compatibility tests with production fluids, incumbent production chemicals and core samples.
Barite scales deposits collected from Field A were found to be radioactive. Testing procedures were in-line with precautions taken to prevent risks exposure to these materials. Scale characterizations indicated samples are dominated by barium sulfate containing some small percentage of calcium carbonate scales and organic contents. Static disintegration and dynamic dissolution tests carried out shows significant results differences where application of barite dissolver chemicals in the well may require coil tubing assistance. Compatibility studies of the dissolver chemical with incumbent production chemicals shows suitability of the different chemicals when the well is flow back after treatment.
Innovative Machine Learning Method to Locate the Root Cause of the Unreliable Data Coming from Intelligent Field Equipment
Authors: Wasfi Bayan , Alqasimi Mohammed , Al Kadem Mohammad , Alghamdi Abdullah 
Published: November 2019

Abstract
Analyzing large amounts of continuous real-time data along with sustaining its reliability is a challenging task for engineers. Low reliability of data can prompt off base data examination results and make it difficult to make critical decisions in the oil and gas business, especially for the cases where the processing of data is continuous real-time data. One example is the continuous real-time data coming from Intelligent Field equipment. Intelligent field equipment for upstream can be a combination of Wellhead sensors, ESP, PDHMS, MPFM, SWC, SPFM, MOVs and H2S sensors. Intelligent Field equipment data follows specific transmission nodes as it flows from each sensor or instrument to a Remote Terminal Unit (RTU), to the Supervisory Control and Data Acquisition (SCADA) system, to a Plant Information (PI) data historian, and after appropriate filtration into the Exploration and Production (E&P) Corporate Database (Oracle), and finally into Petroleum Engineering developed applications. The unreliability of data can occur at any transmission nodes along this path. To discover the root cause of the unreliability, the Engineer must go through an exhaustive and lengthy process. Therefore, this paper introduces a promising methodology that tackles this challenge, by utilizing machine learning methods, to develop pattern recognition algorithms that recognize the transmission nodes where the unreliability of data appeared. Therefore, this paper aims to tackle two main challenges:Estimating data reliabilityDetecting the error location of unreliable data
By utilizing Machine Learning methods to develop pattern recognition algorithms that recognizes the transmission nodes where the unreliability of data appeared. Two out of three machine learning algorithms were selected; Decision Tree and Gradient Boosting (GB). Decision Tree showed an accuracy of 94.6%, while Gradient Boosting showed higher accuracy of 96.4% when estimating data reliability and error location determination. The robustness of GB over decision tree is that GB construct and train trees all at once while the latter train each tree independently. Training all trees at once helps to learn faster and reduce the error dramatically.
Best Engineering Practices in Standardization of Offshore Wellhead Tower Design – EPC Contractor’s Experience
Authors: Singh Sunil Kumar , Wasnik Rakesh , Singh Harendra , Kamal Faris Ragheb , Takieddine Oussama 
Published: November 2019

Abstract
The wellhead tower facilities in Offshore are designed to receive well fluid from different oil fields and transport through pipelines for further processing. The functional requirements for any typical wellhead tower do not vary much; leading to similar design features in most of the Offshore facilities. This paper discusses the best practices applied in standardization of Offshore wellhead tower’s design and highlights its advantages in execution of EPC projects.
In the standardized design, the sizing of equipment and piping for a wellhead tower are normally pre-defined and fixed for all new projects. The pre-defined design specifications are finalized based on best engineering practices and field experiences. For example; the well flow line size of about 6" is found sufficient for typical oil production platforms as well as meets conventional line sizing criteria for most of the projects. Similarly, the material of construction for all piping and equipment can also be pre-selected as part of the standardized design for all new wellhead towers.
The execution of an EPC project from detailed design stage to commissioning, within a given schedule is essential for success of any project. In conventional design approach, various design activities for a wellhead tower such as engineering calculations, design verification and specialized engineering studies are repeated for each project even though the design is already pre-fixed. This is a time-consuming approach and takes significant amount of time without any value addition. This also delays the procurement activities leading to cascading effect on fabrication, installation and commissioning of the facilities. In the standardized approach, design details such as equipment/line sizes, layout is already finalized and EPC contractor is mainly required to update engineering deliverables based on the vendor design information/details. This approach significantly reduces the project schedule. The standardized approach provides an opportunity for fast-track execution of the projects. In addition, it leads to better management of material resulting in reduced maintenance and shutdown period during operational phase. The standardized design also provides flexibility to the operator for easy maintenance and operation of the similar facilities at other locations.
NPCC has recently successfully executed many wellhead tower projects involving standardized design approach. Based on the experience gained and the lessons learnt through these projects, NPCC proposes the best engineering practices that can be adopted for the execution of standardized offshore wellhead towers design providing benefits to all stakeholders.
Trend for Offshore Pipeline Installation Methodologies as a Result of Evolution in the Oil & Gas industry
Authors: Dai Xuexin , Goh Kia Hock , Ng Eng-Bin 
Published: November 2019

Abstract
The objective of the paper is to present the manner in which the Oil & Gas Industry has evolved and how this evolution has impacted the trend in pipeline installation methodologies.
The content for the paper is based on authors’ personal experience within the various installation contractors that he had worked for and observation in the industry spanning 4 decades, as well as research on the evolution of the design of production facilities and how this evolution has impacted the various installation methodologies. The research pertains to both on-line research as well as discussions with various experts working for the various installation contractors, including authors’ employer.
The findings from the study show that changes in design codes have been made to cope with increasing demands for deep-water facilities. The changes in design code has allowed for pipelines to be installed deeper, in particular for conventional S-Lay methods, as well as pave the way for other installation methodologies, such as Reel-Lay. Other novel methods have also been invented, such as the Controlled Depth Tow Method, although this method had evolved not as a result of the changes in code but innovative ideas that allow for deep-water installation with little impact on pipeline stresses.
The findings from the study shows that pipelines are being installed in deeper waters as a result of improvement in design such as shorter stinger radius, which allows for pipeline to leave the lay vessel almost vertically, increased lay tension capacities, advanced welding and NDT techniques and so on. Changes in design codes have contributed to the accomplishment of deep-water pipe-laying.
In addition, the trends for pipeline installation are discussed, as well as gaps and opportunities for future development.
Benchmark Primary Drainage Saturation Height Function: Theory, Methodology, Applications and a Carbonate Case Study in the Sultanate of Oman
Authors: Hadidi Shahab , Boya Ferrero Maria , Van Den Nouland Casper , Nicholls Christopher 
Published: November 2019

Abstract
The benchmark primary drainage Saturation Height Function (SHF) is a standardized dimensionless function that describes the expected saturation-depth profile for a specific rock type resulting from primary drainage. The paper's ambitious goal is to introduce the concept of creating an inventory of benchmark functions for every reservoir rock type. The benchmark function is the reference point to validate the fluid fill history and identify areas of primary drainage for a specific field. Furthermore, it can be used as a diagnostic tool to analyse changes in the reservoir rock type and pinpoint fluid fill variations. The benchmark function is a complementary model to constrain the SHF when there are insufficient data, especially in the transition zone. A key diagnostic criterion for a reservoir rock type is that it contains a consistent combination of pore types and hence has consistent (or predictable) capillary properties. Case studies on carbonate fields are presented from the Sultanate of Oman. The same concept is also applicable to clastic reservoirs.
The benchmark primary drainage function can be derived from the capillary pressure data. Conversion of this data into a normalized capillary pressure system is required. In this paper, we will introduce a workflow to utilize the saturation log data from different fields to build a benchmark function that is not influenced by reservoir fluids densities' and interfacial tension.
Benchmark primary drainage functions were created in different scenarios and rock types to aid saturation modelling in several fields. In one carbonate field, the saturation log data from an analogue field were used to constrain the transition zone due to data limitations. The benchmark function was also used to identify fluid fill variations and unlock a potential development.
The benchmark function of micro-porous rock, derived from several analogue fields, was the baseline for the saturation modelling workflow of a complex carbonate reservoir with a tilted contact and significant imbibition and it was a vital enabler in simplifying the saturation model.
Unmanned Facilities: The Way to $30bn Savings
Authors: Nevin Michael 
Published: November 2019

Abstract
In the Arabian gulf alone, there are an estimated 500+ wellhead towers, of varying designs, varying complexity, varying cost, currently installed.. Expand that to a global view and the number is estimated to be greater than 7000.
Consider the magnitude of life cycle cost savings and HSE performance improvements that would have been made if all those towers could have been designed differently, with significantly less topsides equipment and hence CAPEX, reduced maintenance requirements resulting in much lower OPEX, offshore visitation reduced to once per year, helicopter transportation eliminated – and yet the same basic function maintained. More importantly, as our industry faces up to the challenge of increasingly marginal field developments in an increasingly cost competitive environment, consider the potential to unlock previously non-economic projects through a new approach to this key element.
In this paper we demonstrate what the wellhead tower of today could look like, based on a case study of a recent project undertaken for a major operator. We discuss the technologies required and the approach to operations and maintenance to significantly reduce the life cycle cost, reduce offshore visitation and improve the HSE performance of future wellhead towers.
Finally, with an eye to the ever-evolving future, we project how a similar approach may be adopted not only for wellhead towers, but for more functionally complex processing facilities.
Optimizing Oil Rim Development in a Tight, Fractured Carbonate Field: Khuff Formation, Yibal Field, Sultanate of Oman
Authors: Knoerich Andrea , Dhahli Adnan , Lai Sonia , Habsi Sumaiya , Farsi Shadia 
Published: November 2019

Abstract
The Khuff formation in the Yibal field is currently undergoing one of the largest field development campaigns in PDO. While the main project driver is securing gas production (highly sour) at a stable plateau rate, maximizing oil rim recovery and production is the main objective of the presented study. This is challenging as all wells are pre-drilled as per FDP recommendation and any later development optimization is expected to be difficult and costly.
Newly available static (seismic, well log, borehole images) and dynamic (well test) data were utilized in a decision driven modelling approach to update existing static and dynamic models to confirm the robustness of subsurface development decisions, oil production promises and EUR. Updated structural and property modeling results were utilized to optimize placement of 2/3 of the remaining wells in order to improve drainage. Reservoir rock typing and fracture interpretation, along with cased-hole surveillance data acquired in all wells, were used to optimize production intervals and to confirm the productivity of the different intervals (dolostone/ limestone/ fractures); which were then integrated to confirm the perforation strategy going forward.
This study describes the first development of Khuff carbonates in Sultanate of Oman, with limited historical production data and no analogues in Sultanate of Oman. The study highlights the importance of continuous integration of new data in a decision driven modelling approach to ensure robustness of project decisions with timely project adjustments to prevent NPV erosion.