bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Torque and Drag Models to Prevent Real-Time Operational Problems
Authors: Rodrigues G. da Silva Fabio , De Souza Cruz Marcelo , Newmar Donatti Carlos , P. Moreira de Mello Otávio , Leibsohn Martins Andrá , Gandra Percy Joseir , Max de A. Panisset Curt 
Published: July 2020

Abstract
Real-time drilling data is an essential tool to increase performance and operational safety, especially when operating in challenging environments. In this scenario, it is highly attractive to use new tools that can anticipate possible risks to the operation, aiding in decision making in order to guarantee operational efficiency and safety. The present work aims to present the new technologies developed in a real-time monitoring software (GANDELMAN ET AL., 2013), which automatic diagnosis drilling problem, from the calculations of loads alongthe drill string and the contact of the column with the borehole wall.
Torque and drag models are used to support well planning. The aim is to ensure the feasibility of theoperation and to assist in the prediction and prevention of operational problems during drilling. Directional wells require even more attention, since, as their inclination increases, additional forces are observed due to the enhanced contact of the drill string with the borehole wall.
Since these forces are cumulative, the deeper the well, the larger will be the contact forces and, consequently, the torque and drag values. A comprehensive torque and drag model was implemented to estimate the wear level on the casing, in real-time, due its contact with the drillstring. The purpose of this development is to automatically warn when the calculated wear approaches the expected and / or permitted wear.
Still using the T&D model implemented in the real-time monitoring software (GANDELMAN ET AL., 2013), a module was developed for a more accurate detection of the tubular element that is passing through each of the BOP (blowout preventer) rams when drilling from floating vessels. The main objective of this new technology is to assist the operation in a possible emergency disconnection. The main focus would be to precisely define the moment to actuate a RAM, minimizing the risk of reaching a non-shearable component of the drillstring. Therefore, a logic of tracking each element of the column in front of the BOP rams was created, which takes into account the effect of axial elongation due to real-time tension and compression.
Incorporating Biot Poroelastic Coefficient on Pickett Plots
Authors: Olusola Bukola K. , Aguilera Roberto , Cinco Ley Heber 
Published: July 2020

Abstract
A method is presented for incorporating Biot poroelastic coefficient on Pickett plots. The method allows integration of petrophysical parameters such as water saturation, porosity and permeability with geomechanics through Biot coefficient.
Pattern recognition in Pickett plots have been used historically for quick petrophysical evaluation, particularly for determination of water saturation. The procedure involves a crossplot of porosity vs. true resistivity on log-log coordinates. The method presented in this paper allows determination of Biot coefficient from the Pickett plot in addition to determination of standard petrophysical parameters. The method uses a correlation developed for estimating Biot poroelastic coefficient as a function of process speed (the ratio of permeability and porosity) and pore throat aperture (rp35).
Results indicate that the proposed Pickett plots permits quick simultaneous estimation of different parameters of interest for a given interval including water saturation, porosity, permeability, pore throat aperture and Biot coefficient. The Biot coefficient correlation works for various lithologies including limestone, sandstone, shales, source rock, marble, granite, unconsolidated and oil sand reservoirs. Thus, the method has application in the case of both conventional and unconventional reservoirs.
Key observations based on the proposed Pickett plot include: (1) there is a general tendency for Biot coefficient to decrease as water saturation increases, (2) there is a general tendency for Biot coefficient to increase as porosity, permeability, process speed and pore throat aperture (rp35) increase.
It is concluded that the integration of petrophysical parameters and Biot coefficient provides a new valuable tool to assist in the solution of petroleum engineering problems such as hydraulic fracturing and estimation of in-situ closure stress on proppant.
The novelty of this work is the development for the first time of an integrated Pickett plot that incorporates petrophysical analysis and Biot poroelastic coefficient.
Bayesian Deconvolution of Rate Pressure Data Using Regularizing Priors
Authors: Ravikumar Arjun , Lee John 
Published: July 2020

Abstract
The constant pressure production behavior of a reservoir system is a key component of reservoir diagnostics and production forecasting. Rate-pressure deconvolution is a technique that uses production data from variable rate-variable pressure production to calculate this constant pressure behavior. Regularization techniques are used to mitigate the instability inherent in the deconvolved result. In this work, we describe rate-pressure deconvolution in the time domain within the framework of Bayesian statistics, and obtain the deconvolved result by interpreting the posterior distribution.
We strategically parametrize the problem in terms of derivatives of the deconvolved solution to exploit the monotonic nature of the constant pressure behavior. We achieve regularization of the deconvolved solution using regularizing priors instead of conventional regularization methods. The regularizing prior is a probability distribution of the solution constructed using the prior knowledge of reservoir and fluid parameters from a variety of sources such as fluid samples, analogs, experience, and common sense. Finally, we obtain the deconvolved result using Markov chain Monte Carlo methods.
We show that conventional regularizing methods are a subset of the regularizing prior approach, by proving that, for specific choices of the prior, our method is equivalent to conventional regularization techniques. We establish the validity of our method using synthetic data with noise added. We analyze the sensitivity of the solution to the regularizing prior and discuss procedures for choosing an appropriate prior. We discuss methods to make the inference robust to outliers in the data. Finally, we demonstrate our deconvolution algorithm with field cases.
The constant pressure behavior of a reservoir is crucial to diagnostic and forecasting methods such as flow regime identification and decline curve analysis. Existing rate-pressure deconvolution techniques have no mechanism for including prior knowledge of the reservoir in the solution. Our framing of the problem incorporates this knowledge into the problem systematically. Our Bayesian approach also enables us to infer the uncertainty of the deconvolved solution directly from the posterior distribution.
Enabling WITSML Stream Analytics Through Open Source Big Data Technologies
Authors: Pisauri Federico , Escudero Fernando , Rodriguez Pedro Emilio 
Published: July 2020

Abstract
This work presents a set of interconnected open source big data technologies through an example case to demonstrate the processes used to generate, process, store, and consume real-time wellsite information transfer standard markup language (WITSML) data from drilling and completions (D&C) operations. The new proposed approach to manage real-time data is based on the use of distributed storage and processing technologies to simultaneously analyze large volumes of information, previously considered only on an individual well basis. This new approach leverages the open source technology available in the market to target the gathering of the data, its secure database storage, and its future processing in a single workflow, to obtain the most value added from the oilfield-generated data during D&C operations. This work presents a set of big data tools and their application.
For this case study, a dynamic, open, easily configurable, and fully scalable work environment was obtained. Open source big data technologies prove to be different when handling operations data, as compared to traditional technologies. Traditional technologies typically require several manual inputs and configurations to enter the data. Data models for these technologies are usually closed or proprietary, and the provided visualizations are limited either to single well analysis or to basic analytical dashboards. The technologies used for this case fully enable data input and storage, as well as allow the generation and real-time deployment of machine learning and data science algorithms and models.
As a different approach, this paper introduces the use of big data architectures for the D&C business to obtain better results for gathering, storing, and analyzing real-time information than the business has traditionally achieved.
Importance of the Hygienic Measuring of Levels of Exposure to Benzene and Its Derivatives in Production Activities, Focused on Preventing Occupational Diseases
Authors: Gómez Real Carlos , Cárdenas Villalobos Oscar 
Published: July 2020

Abstract
Since exposure to Volatile Organic Vapors (Benzene, Toluene and Xylene - BTX) produces serious short- and long-term neurotoxic and hematological effects in individuals, this work focuses on reducing both the incidence and prevalence of occupational diseases associated with exposure to organic vapors by implementing prevention programs.
Hygienic measurements are made periodically, the results of which are essential for establishing guidelines for the different controls, thus eliminating or substantially reducing exposure. The NIOSH 1501 and OSHA 7 methods for measuring exposure to BTX were employed for collecting information at the worksites and its subsequent analysis. This study was conducted at different petroleum production fields in the Llanos Orientales basin in Colombia, based on a prior characterization of the crude (semi-heavy crude oil) and for certain positions determined according to the degree of exposure.
The comparison between permissible limits, the range of exposure and the periodic medical examinations of those exposed determine the measures to be taken to reduce the risk to employees. Personnel exposed to BTX organic vapors in the production areas, laboratories and crude loading racks are classified in a minimum exposure range.
During the 4 years of studies there have been no cases of incidence or prevalence of associated occupational disease, nor have case studies been detected in the annual occupational medical exams.
Implementing engineering measures in the workplaces has helped to maintain control of this danger and lessen the likelihood of worker exposure. This shows that the prior engineering designs and implementation of procedures supported with hygienic measurements are the best prevention tools for a major risk in oil production.
Data Boosted Stuck Pipe Prevention: Integrating Machine Learning Models into the Mud Plan Design Workflow
Authors: Berdugo Arias Carlos Andrés , León Torrado Angie Tatiana , Llano Carvajal Juan Sebastián 
Published: July 2020

Abstract
The main objective of this project is to develop a model that, based on the data of previously drilled wells, allows the user to evaluate the mud plan and identify the probability of a stuck pipe event occurrence. This is done, by using statistical predictive models, particularly in this case, neural network models.
The proposed model takes the input data from the Volve’s dataset. The process starts with the pre-processing of more than 24.000 rows of data from the daily drilling operation reports of 30 wells. The pre-processing of the data consists of identifying the cases where the operation ran across a section successfully or when it resulted in a stuck pipe event. Depending on whether there is or not a stuck pipe event, each row will be classified indicating the chance that a stuck pipe event occurs based on the geological and the operational conditions.
In order to ease the processing of the 24.000 rows, the project workflow implements a Natural Language Processing model, which, based on an initial dataset of 1.200 rows, reads the remaining 22.800 identifying whether the row content is relevant or not for stuck pipe identification. Once all the rows are processed, the rows which represent a stuck pipe event, and those who identify a clean operation run are selected and integrated into the final dataset.
Once the data is processed, the resulting dataset consists of around 600 rows. After some data transformation, this dataset will be the input for the neural network model in the training and validation phases. Once the model is built, the model is tested with the validation dataset in order to evaluate its accuracy.
The trained model shows high accuracy, higher than 84% on the test data. After the model is trained and validated, it’s implemented into a frontend which will serve as the front user interface where he can upload the mud plan parameters, and obtain a stuck pipe event chance evaluation. Having these results, the user can improve the mud plan in order to reduce the chance that an event of this type occurs.
The main advantage of this methodology is that it allows to include historical data from the other drilled wells, this way, boosting the mud plan design with real data and reducing the chances that a stuck pipe event, that account for a high percentage of NPT’s during drilling operations occur. Also, by the use of these statistical models, applied to a specific field, it will allow to intrinsically take into account variables such as geomechanics properties in the model.
Evaluation of the Performance of Thermal EOR Processes in Fractured Shale Oil Formations
Authors: Sarkar Prakhar , Moridis George J. , Blasingame Thomas A. 
Published: July 2020

Abstract
The objective of this study is to analyze and describe quantitatively the effectiveness of thermal EOR processes in increasing production from multi-fractured unconventional resources such as shale oil and tight sand reservoirs. The study evaluates the efficacy of circulation of hot fluids at different temperatures through dedicated unperforated wells in a process that involves direct heat injection without the concurrent injection of fluids that could cause problems of excessive pressures and adverse relative permeability regimes in these ultra-low-permeability (ULP) systems.
In this numerical simulation study, a modified version of the TOUGH+ compositional simulator is used to represent (a) the flow of heat by all possible transport mechanisms and (b) the flow of the three phases routinely involved in these ULP reservoirs. The simulation domain is a stencil, i.e., the minimum 3D repeatable element of a hydraulically-fractured unconventional reservoir, and is discretized using a high-definition (to a mm-scale) grid. The solutions associated with different thermal treatments are compared to a reference case that involves a simple, non-isothermal depressurization-induced production. The rate and composition of the production stream, as well as the spatial distributions of pressure, temperature, phase saturations, viscosities and relative permeabilities is continuously monitored during the simulation process.
This high-resolution 3D study simultaneously considers all thermophysical processes that are affected by the changes in pressure and temperature involved during these thermal EOR operations in ULP reservoirs, as well as their evolution over time: fluid flow, heat flow and transport by conduction and advection, phase density and viscosity, gas solubility in the liquid phases, phase changes and phase production rates. The study captures in detail phenomena that can be easily attenuated in coarser grids. An important contribution of this study is a detailed analysis of the various aspects of production affected by a thermal process as well as the quantification of mass and energy balance, as well as the associated losses. The results of the study indicate that thermal processes (even ones that involve long heating periods) lead to increases in hydrocarbon recovery that (a) are practically negligible to minor even under ideal conditions (under which heat losses are disregarded) and (b) cannot even begin to compensate for the significant energy needs of these methods. The major contribution of this study is that it provides documented evidence of, and sufficient quantitative information on, the ineffectiveness of thermal processes as possible EOR methods, thus reducing them in priority (if not eliminating them from further consideration altogether) as a viable EOR option.
Pressure Behavior During Injectivity Tests - A Composite Reservoir Approach
Authors: L. F. Bittencourt Neto Jessica , Vieira Bela Renan , Pesco Sinesio , Barreto Abelardo 
Published: July 2020

Abstract
Injectivity testing is a procedure used by the oil industry whose purpose, when injecting a fluid, is to obtain information about the characteristics of an oil reservoir. Such characteristics can be estimated from the pressure response obtained during the test. This work presents a solution to the well pressure during an injectivity test, considering a piston flow, using a radially composed reservoir model. It is considered that the reservoir may have a two-phase flow with two regions (water and oil) or three regions. In this case it is considered that the region near the well represents a damaged zone (skin zone). From the known analytical solution for pressure in the Laplace space, it is possible to use a matrix representation of the problem the well pressure calculation. With the aid of Stehfest algorithm, it is possible to perform the numerical inversion of the solution to the real field. From this problem, it was possible to develop a code that simulates the injectivity test and the pressure behavior over time.
Innovative Technologies Drive Benchmark Performance Drilling Challenging Caipipendi Block in Bolivia
Authors: Bertarelli Mario , Duran Romulo , Tocantins João Pedro , Mendoza Diego , Bijai Rahul , Trunk Philip , Villegas Cesar , Ramos Aldo 
Published: July 2020

Abstract
As part of an exploration campaign in the Sub Andean region in Bolivia, Repsol faced a unique challenge to reduce well construction costs while drilling through harsh and abrasive Caipipendi Block formations. The Caipipendi Block poses several drilling challenges that often lead to premature bit and underreamer cutting structure damage. Two main points were targeted as fundamental to accomplish this objective: reduce the number of runs to drill the Carboniferous section and improve borehole enlargement efficiency. A multidisciplinary group comprising a service company and Repsol team members conducted a detailed and thorough investigation of previous failure modes to identify an integrated approach to improve the performance. Along with offset history, the team was able to identify lithology characteristics to accurately diagnose the underlying root causes. To tackle the hard and abrasive Upper Carboniferous section, a customized polycrystalline diamond compact (PDC) drill bit was equipped with 3-D cutter (3DC) technology and powered by a combination of an enhanced power section and a robust rotary steerable system (RSS) tool with a new specific steering pad feature. A new reamer concept was also applied in this well to mitigate the anticipated drilling shock and vibration associated with underreaming through the challenging strata—without compromising drilling efficiency. To achieve the desired performance goals, 3DC elements were applied to the drill bit, along with a robust RSS designed with a pioneering steering pad developed to sustain performance in high levels of formation abrasiveness. To increase borehole enlargement efficiency in the Devonian section, a new cutter block was designed. An advanced 4D transient drillstring dynamics modeling package was used to analyze failure modes, design the reamer and drill bit cutting structures, predict the drilling dynamics of drill bit and reamer, and recommend drilling parameters for the run. The objective was successfully achieved where Repsol was able to set a new benchmark for the block, drilling the programmed depth of the well in 350 days, 17% less than AFE curve and 25% less compared with the best result in the block even with a significant change in lithology sequence from the program. The innovative 3DC technology boosted overall drilling performance. The new PowerDrive* rotary steerable system pads enabled the customized drill bit to drill farther and avoid unexpected bottomhole assembly (BHA) trips. The use of a new cutter block equipped with 3DC technology enhanced stability and reduced lateral displacement and vibration.
Establishing Limits for Brine Discharge Dispersion in Offshore Operation
Authors: Mota Pedro Henrique , Damasceno Marcelo Maia , Da Silveira Neto Aristeu , Vedovoto João Marcelo , Marinho Leonardo , Pamphili Cristiano , Samsoni Umberto , Waldmann Alex , Martins André Leibsohn 
Published: July 2020

Abstract
A study of saline fluids discharge from offshore activities was performed through the modeling and numerical simulation of the advective and diffusive transport of discharged brines. In order to solve the fluid dynamic equations, the turbulence closure model used was the dynamic subgrid-scale (SGS) model of Germano, a Large Eddy Simulation (LES) method, implemented in the MFSim software. In addition, the scalar transport equation was considered to obtain a spatial and temporal distribution of salinity in the ocean after brine discharge. Furthermore, the adaptive mesh refinement (AMR) method was considered to refine regions of interest and, consequently, reduce numerical costs. The effects of brine discharge were evaluated considering the brine content, discharge flow rate and different scenarios of ocean currents. The methodology assisted in achieving precise results of the advective and diffusive transport of the plume under different operating conditions and observing detailed aspects of this phenomenon. The results were analyzed considering restrictions imposed by environmental protection agencies. As a result, the importance of evaluating operating conditions was observed in order to control environmental impacts since different operating conditions could lead to different fluid dynamic characteristics at farther distance from the discharge point.