bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Delayed In-Situ Generated Acid System to Enhance Carbonate Acidizing
Authors: Bokkers Albert , Nazari Moghaddam Rasoul , Aaldering Koos , Kooijman Cees , Ameri Amin , Jankowski Szymon 
Published: February 2022

Abstract
Conventional acidizing of high temperature reservoirs is currently facing different challenges including high corrosion rate, face dissolution, rapid and uncontrolled reaction and formation damage. In this study, a new in-situ generated acid system is introduced to address the shortcomings of the conventional acid systems. This paper presents an acidizing fluid with delayed acidification properties that can be tailored to different reservoir conditions.
A new acidizing system based on sodium salt of monochloroacetic acid (SMCA) is developed and introduced to resolve the technical challenges that conventional acid systems usually fail to tackle appropriately. The hydrolysis rate (i.e., acidification rate) of SMCA, which brings the delayed properties to the acid system, was further optimized by addition of halogen salts. Furthermore, the dissolution capacities of the acid system were measured for different minerals using the main formulation as well as boosted acid by addition of an organic/inorganic acid. Also, the precipitation potentials of the by-products were also investigated after the acid was fully spent and cooled down. Several additives were tested to improve the solubility of the calcium salt. Finally, the performance of the acid system was investigated by performing several coreflooding experiments using Indiana limestone cores. The coreflood experiments were conducted at different injection rates and at various degrees of hydrolysis.
From the hydrolyzation experiments, it is found that addition of 1 wt% sodium iodide increases the SMCA hydrolyzation rate with a factor 1.7. It proved that fast hydrolysis can even be obtained at lower temperatures. It was shown that the reaction products from the calcite dissolution are fully soluble and chelation is the main responsible mechanism. In addition, it was found that scale inhibitors made from polymaleic acids, polyacrylic acids and copolymers thereof can also efficiently prevent solid precipitation. It was shown that the addition of hydrochloric acid in the range between 0.5 and 5 wt% can increase the dissolution capacity by at least 30%. From the coreflooding results, it was found that the new acid system can efficiently stimulate the limestone formations with no face dissolution under varying conditions in terms of temperature and injection rate. The CT-scan images confirmed the favourable wormhole propagation characteristics of the new acid system.
The new acid system introduced in this paper is an in-situ acid generator which releases an organic acid over time and as function of temperature allowing deeper penetration. The main ingredients in the acid system are solid which allow safe handling and onsite preparation for offshore applications.
Curing Losses: Lab Developments and Best Practices
Authors: Al-Yami Abdullah , Wagle Vikrant , Al-Anqari Khawlah , Aljohar Abdulwahab , Elkatatny Salah 
Published: February 2022

Abstract
Moderate to severe loss circulation problem encountered while drilling is a major economic burden that increases the total well construction cost dramatically in some cases. This study will focus on best practices to mitigate curing losses in terms of prevention of potential loss by pre-treatment, locating and identifying the losses, identify the mechanism of losses and severity, curing losses strategies and their best drilling practices. In addition, the study will detail typical curing losses materials and their limitations. Finally, selected examples of recent developments in curing losses materials are detailed. The examples are activated nanoparticles dispersed fluid, Epoxy polymer resins, and sodium acid soluble cement solutions.
Pre-treatment of loss circulation zone with proper size of bridging materials can reduce and eliminate mud losses into porous formations. The choice of bridging agents will depend on the formation characteristics. The moment of the occurrence (while drilling, circulating or tripping), the severity of the loss (seeping, partial or complete) and the exposed formations are the key factors to identify the best remedy for loss circulation. Losses to reservoir zones are handled differently than non-reservoir zones, wherein only acid soluble or non-damaging material is used in the pay-zone. Seepage losses occur in any formation type when the particle size distribution of the bridging agents is not optimum enough to create an effective seal. This paper describes three different types of novel loss circulation materials to control moderate to severe losses.
The paper describes the development of a novel nanoparticle-based chemical treatment composition for its potential use as a loss circulation material. The gelation times were evaluated at different temperatures up to 300°F. The effects of pH and different concentration of activators on gelation times of the new treatment fluid has also been studied. Second example of LCM described in this paper is a novel resin composition comprising an epoxy resin and chemical activator to treat moderate to severe losses. The effect of the chemical activator concentration on the setting time of the resin composition was investigated to accomplish a controlled and delayed polymerization. The third example of LCM described in this paper involves a formulation consisting of an acid soluble cement and a sodium silicate gel that has a high potential to control moderate to severe loss circulation problem. The objective of this acid soluble loss circulation system technology was to design a solution to cure lost circulation in reservoir zones. This is the first study to discuss and detail such topics related to curing losses.
Quantitative Research on Development Status of Heterogeneous Reservoirs in Offshore Oilfields
Authors: Guan Cuo , Zhang Jian , Li Xianjie 
Published: February 2022

Abstract
Multi-layered reservoirs have unbalanced production levels due to the contradictions between layers in offshore oilfields. At present, there is a lack of rapid and effective methods to quantitatively analyze and evaluate the development status. In this paper, based on the B-L theory and the equivalent seepage resistance method in the water drive process, a relationship chart between the average saturation of a single layer and the seepage resistance between injection and production wells is established. Using the test results of single well pressure and production well profile, single layer seepage resistance can be obtained, combined with saturation-seepage resistance chart to obtain single layer average water saturation, and then the single layer recovery degree at the time of testing can be determined. In order to establish a Lorentz curve model describing the relationship between the cumulative single layer recovery ratio (or fluid absorption index) and the ratio of formation coefficient, the recovery degree (or liquid absorption index) of each single layer and its corresponding formation coefficient are counted. Based on that Lorentz curve model, it can effectively quantify and characterize the production equilibrium degree of multi-layer reservoirs. After using this method to backcalculate the development status of a certain well group in the Bohai Oilfield, the characteristics of the degree of production and the development of large channels in each layer can be obtained. it also quantifies that the imbalance index used by the well group has risen from 1.2 in 2014 to 2.1 in 2019. This paper proposes a new method for analyzing reservoir development dynamic characteristics, which can more objectively and truly evaluate reservoir development characteristics and quantitatively evaluate the effects of adjustment measures, and provide efficient and fast technical support for the efficient development of offshore fields.
GPU-Enabled Scalable Multiscale Solver for Reservoir Simulation
Authors: Manea Abdulrahman 
Published: February 2022

Abstract
As reservoir simulation models continue to grow in their size and complexity, the computational cost of reservoir simulation is constantly increasing. Since most of the reservoir simulation time is typically spent in the linear solver (being in the innermost part and the most challenging to parallelize and scale), efficient linear solvers are of utmost importance for reducing reservoir simulation turnaround times. In this work, we study the scalability of a versatile multiscale linear solver, namely the restriction-smoothed basis multiscale method (MsRSB) (Møyner and Lie (2016)) on the emerging massively parallel GPU architecture, and compare it to its performance on the multi-core CPU architecture.
MsRSB, unlike traditional multiscale approaches, uses iterative smoothing to adaptively compute multiscale basis functions, allowing it to handle a wide range of difficult grid orientations seen in real-world industrial applications. While MsRSB can be parallelized directly, its reliance on a smoother to determine the basis of functions results in unusual control and data flow patterns. To achieve effective scalability, these patterns must be carefully designed and implemented on massively parallel systems. We extend Manea et al. (2016) and Manea and Almani (2019) work on parallel multiscale methods to move the MsRSB special kernels to shared-memory parallel multi-core and GPU architectures.
Highly heterogeneous multimillion-cell 3D problems, adopted from the SPE10 Benchmark (Christie and Blunt (2001) have been used to illustrate the scalability of our parallel MsRSB development. The GPU implementation is benchmarked on a massively parallel architecture consisting of Nvidia Volta V100 GPUs, while the multi-core implementation is benchmarked on a shared memory multi-core architecture consisting of two packages of Intel's Haswell-EP Xeon(R) CPU E5-2667. For both the setup and solution stages, we compare the multi-core implementation versus the GPU implementation. The GPU-based MsRSB implementation shows great scalability, with over a 4-fold reduction in runtime when compared to the optimized multi-core implementation.
A Rapid Multi-Objective Intelligent Decision Method for Shale Gas Fracturing Parameters Based on Machine Learning: A Case Study in the Changning Reservoir
Authors: Wang Lian , Yao Yuedong , Wang Kongjie , Adenutsi Caspar Daniel , Zhao Guoxiang , Dong Peng 
Published: February 2022

AbstractProper design of fracturing parameters does not only increase the productivity and profitability of shale gas wells but also reduce the damage fracturing fluids cause to fluid-sensitive formations. Unfortunately, fracturing parameters design methods developed so far rely heavily on simulation runs and experience of field engineers. To lessen the computational burden and decrease the risks during fracturing, this study proposes a simple-yet-rigorous rapid intelligent multi-objective decision (RIMOD) method for shale gas fracturing parameters. The proposed RIMOD method includes two key sections, the first one is the squares support vector regression (LSSVR) model for objective evaluation and the other is non-dominated sorting genetic algorithm-II (NSGA-II) for finding the best shale gas fracturing parameters. Meanwhile, the flowback ratio of fracturing fluid (FBR) and first-month gas production (PROD) were considered as the objectives while fracturing parameters such as number of fractured sections, proppant amount and fractured length were selected as the decision variables. According to the data from sixty-six fractured horizontal wells from the Changning shale gas reservoirs, the intelligence decision process was completed in less than ten seconds. Furthermore, the accuracy of optimal scenarios in the final Pareto front was tested with the numerical model includes the geological features of the Changning reservoir. It was found that for both FBR and PROD the mean relative errors were less than 4%. It was concluded that, compared with simulation and empirical methods, the proposed RIMOD method could obtain fracturing parameters with greater efficiency and reliable precision. A field engineer could choose a scenario from the final optimal solution set based on the demand of the company. This could be reduction in formation damage or increased single well production. More importantly, once the data of a fractured well is obtained, this approach can be used to immediately establish an intelligent decision model for designing the fracture parameters of newly drilled wells.
Novel Methods for Simulating Reservoirs with Tilted Fluid Contacts
Authors: Dow Eric , Kashinath Abishek , Jayasinghe Savithru , Middya Usuf , Dogru Ali 
Published: February 2022

Abstract
This paper introduces two new approaches for modeling reservoirs with tilted fluid contacts. We first introduce a method based on local capillary pressure adjustments, which uses adjustments of the capillary pressure near the oil-water contact to ensure that the contact surface does not move during production. The second approach uses hydrodynamic aquifer flow to support the oil-water tilt. A non-linear inverse problem is solved to determine the parameters that control the aquifer flow. Both approaches are implemented in a parallel reservoir simulator and applied to a synthetic reservoir case.
Integration of Engineering & Geomechanics Lead to a Successful Sidetrack, Drilling, and Completion
Authors: Al Dhamen Ali , Aleidhi Abdulaziz , Vossen Johannes H , Chakrabarti Prajit 
Published: February 2022

Abstract
A landing section of a well in newly developed area of a field had three challenges: the well trajectory cuts through shale intervals at high inclination; the well plan was limited to a certain trajectory window where weak bedding planes failure could not be ruled out by changing the plan; the previous section's casing was short landed due to wellbore instability challenges. An effort to initiate a sidetrack twice was not successful due to wellbore collapse, therefore a new sidetrack depth had to be identified. Geomechanics group collaborated with Drilling Engineering, and Drilling fluid services to successfully initiate the sidetrack, drill the well and land the liner casing safely to bottom.
A geomechanics model was built based on wireline logging data from offset wells. First, stress azimuth was constrained from oriented multi arm caliper of multiple wells around the field. Then, rock properties were derived from acoustic logging data, and the model was calibrated against drilling events and caliper enlargements. Finally, Geomechanical and petrophysical parameters were utilized to design fluids parameters and additives. A starting mud weight window was defined, and a sidetrack point was selected in strong rock interval. The well was monitored in real time where Logging while drilling, acoustic caliper, and azimuthal density image were utilized for breakouts onset monitoring. Furthermore, drilling parameters were monitored for hole cleaning and mud weight control.
The stress azimuth around the field demonstrates a rotation of 15° from the north toward the east which introduced uncertainty in defining MW in the well trajectory that could be affected by rotation. The sidetrack was successfully initiated as expected, the hole was drilled to bottom, and liner landed successfully. However, a significant increase of MW from its starting value was required, and the model was subsequently adjusted based on LWD data. Maintenance of high concentration of bridging while continuously nourishing the mud helped in stabilizing the wellbore. Unlike previous sidetracks, non-productive time was eliminated with significant cost reduction.
Well Integrity Challenges and Latest Responses to Abnormally High-Pressured Formations in Deep Gas Wells
Authors: Corona Mauricio , Franco Nata , Veloso de Oliveira Adriano , Moretti Fabricio , Alismail Ahmad Ali 
Published: February 2022

Abstract
Drilling through the deep and tight dolomitic interval is challenging due to significant pore pressure anomalies across a giant gas field in the Middle East, resulting in an increase of the drilling fluid density that on some occasions has exceeded the 20 ppg value.
Extensive offset well analysis and observed patterns in the sub-surface attributes can support the identification of abnormal high-pressure zones and selection of suitable well design. The sub-surface model is fed with the occurrence of these high geo-pressures and the attributes are re-processed to continue mapping the risk, seismic response versus actual high-pressure events.
Different studies have been performed in several years in attempt to understand and predict the behavior of the high-pressure zones. Due to field heterogonous stratigraphic and areal distribution, that correlation was not always able to identify them, and still drilling risks such as well control, downhole loss circulation and stuck pipe significantly impacting operations. Under well dynamic conditions, keeping the mud stable at high densities is just one of the important aspects in drilling and cementing operations, which small mistakes can compromise well integrity and, in worst-case scenarios, result in abandoning the well for not being able to reach the main reservoir target.
This paper describes the major operational and well integrity challenges faced during the well construction and latest innovative responses to safely handle abnormal and unexpected high-pressure zones. Mitigation measures in terms of well control, drilling and cementing fluids, drilling practices and contingency well design to counteract the challenges will be described in length in the paper.
Correcting Classified Activities with Natural Language Processing
Authors: AbouLaban Said , AlAwami Nassar , Herve Philippe , Amrite Jaidev 
Published: February 2022

Abstract
For Drilling Contractors and Oil & Gas operators, daily drilling activity reporting is crucial to understand the underlying efficiency of the drilling process, identify risks and uncertainties at the well level and field level, look for opportunities to improve average rate of penetration and to be within the target drilling budget and target time. All the previous while increasing the safety of the people and assets and have the lowest impact in the environment.
Daily drilling reports help drilling contractors and operators to understand what, where and when an activity was performed, helps managers to understand teams and contractors performance, and helps executives have a holistic view of the drilling process, and how it meets predefined Key Performance Indicator targets. Analysis does not only look into visible non-productive time, but extends into invisible non productive time. Examples of visible non productive time include drilling borehole assembly failure, critical rig equipment failure, etc. Examples of non visible non productive time include premature pulling out of hole of drilling equipment assuming high bit wear, variations between crew experience during drilling resulting in lower rate of penetration, etc.
The challenge the industry faces is that daily drilling activity reporting; along with real time reporting, provides the foundation for drilling analytics. And inaccuracies in reporting the drilling activity, such as reporting the wrong activity, would lead to inaccurate analytics and insights. To overcome this challenge, operators standardize drilling activities reporting by defining drilling codes and subcodes that are used by Drillers, Tool Pushers and Company men to map a drilling activity to a usable code and subcode, and in turn, those codes and subcodes can be used to extract structured data out of the drilling reports for reporting purposes.
A Data Driven Method to Predict and Restore Missing Well Head Flow Pressure
Authors: Huang Ruijie , Wei Chenji , Li Baozhu , Xiong Lihui , Yang Jian , Wu Suwei , Gao Yan , Liu Shuangshuang , Zhang Chenjun , Lou Yuankeli , Li Zhengzhong 
Published: February 2022

Abstract
With the rapid development of oilfield exploration and development technology and the continuous improvement of automation and informationization, the petroleum industry has entered the era of digitalization and intelligence. Surveillance data including pressure and saturation play increasingly role of reservoir development machine learning modelling. A large amount of high-quality data can enhance the accuracy and robustness of the neural network model. However, during actual reservoir development, not all data are easily available. Data acquisition is limited to high-cost tests techniques, pressure bulid-up test, reservoir saturation test, and production logging test etc. In this study, we develop a novel workflow to forecast and restore missing well head flow pressure (WHFP) by utilizing Random Forest (RF) algorithms based on the actual dataset obtained from the middle east carbonate reservoir. To evaluate the effect of prediction pressure results, we employed predicted WHFP into production prediction neural network model. With the support of predicted WHFP, the quality and accuracy of neural network production prediction model is much improved. This study provides a low-cost and high-precision WHFP prediction and restoration method for reservoir engineers in decision making.
A Systematic Approach to Leak-Off Pressure Prediction in Unconventional Resources –A Case Study from Junggar Basin, China
Authors: Jiang Zhibin , Sima Liqiang , Zhou Wei , Wang Xiaoguang , Xu Hanbing , Ding Kun , Qi Lisha , Zheng Sheng , Xie Dan , Lian Liming , Qian Chuanchuan , Wang Jie , Bai Zhiwen 
Published: February 2022

Abstract
Mud loss is one of the most severe incidents encountered while drilling. As the focus of exploration has moved to the deeper and more complicated formations, mud loss happens more frequently, causing safety incidents and lowering the drilling efficiency. The lost mud invades into formations, makes harm to the reservoir and affects the accuracy of formation evaluation. Large numbers of studies have proved that the key strategy to deal with mud loss is to prevent it and follow with remedial action. The prerequisite of such measurements is locating the formation of mud loss. Loss pressure is the highest pressure that formation can hold before mud loss happens. It is important for deciding mud weight and critical for fractured formations. Therefore, an innovative ring-cracking loss model is created by integrating minimum horizontal principal stress loss model, statistical loss model, and critical crack width loss model after analyzing the loss mechanism of fractured formation. These four models are applied to the fractured formation of block X, and the results are compared to the actual downhole pressure.The result from ring-cracking-based loss model is less than the actual downhole pressure. This model is suitable for field application and can guide the design of mud density.