bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling CO2 Sequestration in Deep Saline Aquifers – Best Practices
Authors: Alzayer Hassan , Zahrani Tareq , Shubbar Ahmed 
Published: February 2022

Abstract
Managing carbon emissions has become a major responsibility for the oil and gas industry in a drive to ensure sustainable energy and create a clean environment. Therefore, governments, research centers, IOC’s and NOC’s are actively adopting new guidelines and inventing new technologies to safely circulate carbons. In this paper, the process of modeling CO2 sequestration in a deep saline aquifer will be discussed.
Carbon dioxide can be safely stored indefinitely in subsurface geological formations by four trapping mechanisms; structural, residual, soluble, and mineral trapping. These four trapping mechanisms can take hundreds or thousands of years to happen. Furthermore, the oil and gas industry standard recommend that any technology used to store CO2 needs to demonstrate a storage capacity of 1000 years with less than 0.1 per-cent leakage potential per year. Therefore, modelling such process should capture any existing trapping mechanism, even if it happens after several hundreds of years, to ensure long-term secure storage of the CO2. Using our in-house simulator "GigaPOWERS", many sequestration scenarios were conducted to come up with a recommended guideline to maximize the volume of CO2 trapped in deep saline aquifers.
This study used a giant synthetic anticline model with a variation in geological properties. The residual and soluble trapping mechanisms were captured through relative permeability hysteresis and extended water PVT tables respectively. Injecting CO2 into water aquifers is a dynamic process where drainage and imbibition cycles are likely to happen. Such processes cause the CO2 to be trapped in the middle of the pores as an immobile phase, which can be a favorable phenomenon maximizing the security of CO2 sequestration. Since CO2 is soluble in water, when it contacts the water phase it will form a carbonated water that is denser than water itself and migrates downward in a phenomenon known as "CO2 fingering". The CO2 solubility in water depends mainly on the salinity and temperature which both need to be accurately captured in the simulation model. Depending on the long-term objective of the sequestration project, the development strategy can be altered to maximize the outcome using the detailed simulation model. In this paper, the simulation best practices for modeling CO2 sequestration for maximum secure long-term storage (1000+ years) are suggested.
Carbon dioxide, CO2, sequestration in deep saline aquifers is a well-known method to reduce carbon emissions. However, there is very little published literature on the simulation best practices for modeling the CO2 sequestration process. Therefore, this paper will be a pioneer to guide the industry for accurate simulation of such process.
Reservoir Characterization for Isolated Porosity from Multi-Frequency Dielectric Measurements
Authors: Jin Guodong , Ma Shouxiang , Antle Ryan , Al-Ofi Salah M. 
Published: February 2022

Abstract
Due to processes of geological diagenesis, pores in rocks can be isolated from the rest of the connected pore networks. The amount and spatial distribution of isolated pores can have direct effect on petrophysical properties and performance of the reservoir. This paper introduces a new methodology to quantify the isolated porosity of heterogeneous reservoirs from multi-frequency (dispersion) dielectric measurements. Based on numerical simulation studies, digital rock physics techniques are used to generate rock models with different isolated porosities. 3D dielectric dispersion modeling is then performed on the models to obtain the dispersion of rock’s dielectric constant. Dielectric dispersion behaves differently as the pore connectivity changes due to increase in isolated porosity. Dielectric constant is sensitive to frequency when pores are isolated, while insensitive to frequency when pores are connected.
Variation of dielectric constant is strongly related to the amount of isolated pores. For rocks having the same total porosity, their dielectric constant increases as the isolated porosity increases. This enhancement of dielectric constant is attributed to the increase in pore network tortuosity, resulting in increased accumulations of electric charges at the interfaces between solid and pores. Analytical relationships are developed to correlate isolated porosity with the rate of permittivity change and/or the permittivity ratio, derived from the dispersion of dielectric constants. The validity and applicability of the established method are demonstrated by the agreement of predicted isolated porosity with the true values used in building the rock models. Potentially, this method can be used for enhancing reservoir characterization with modern multifrequency dielectric logs.
Surface Modified Nanoparticles Based Novel Gelled Acid System - A Unique Formation Damage Free Well Stimulation Technology
Authors: Kalgaonkar Rajendra , Baqader Nour 
Published: February 2022

Abstract
Gelled acid systems based upon gelation of hydrochloric acid (HCl) are extensively used in both matrix acidizing and fracture acidizing treatments to prevent acidizing fluid leak-off. The gelled-up fluid system helps retard the acid reaction to allow deeper wormhole propagation. Conventional in-situ crosslinked gelled acid systems consist of a polyacrylamide polymer, a crosslinker (such as iron-based crosslinker), a chemical breaker, other additives, along with acid. However, these systems can lead to damaging the formation due to several reasons including unbroken polymer residue or scaling, resulting in lowering of hydrocarbon productivity. To mitigate these drawbacks, we have developed a self-breaking, formation damage-free, novel nanoparticles based gelled acid system to replace the polymer based gelled acid system. The new gelled acid system is based on, surface modified nanoparticles to make them compatible in acidic environment, a gelation activator, acidizing treatment additives along with HCl to overcome the challenges the conventional systems face. The new system can work with up to 28& of HCl up to 300°F with low viscosity at surface, making it easy to be pump. As the acid spends due to reaction with the formation the pH of the fluid transitions from acidic to basic pH. The gelation phenomenon of the new system is controlled by the increasing pH. As the pH increases beyond pH 1 gelation of the nanoparticles occurs thus gelling up the acidic fluid. As the pH further continues to rise beyond pH 4 the nanoparticles lose their capability to gel up and the fluid viscosity decreases to pre-gelation level, facilitating easy post treatment flow back.
A systematic experimental protocol was followed to develop the new system that is documented in this paper. It is shown that the gelation properties are pH dependent phenomenon providing the critical control over the gelation time and avoiding any premature gelation during pumping the treatment. The effectiveness of the system by not damaging the formation was investigated using regain permeability studies. The new system showed excellent regain permeability. The obtained data confirmed several advantages of the new system over conventional polymer based gelled acid systems. Gelation experiments were performed to gather a better understanding of the gelation mechanism and also to get effective control on the gelation and break properties.
The uniqueness about the new system is that, it is formation damage free without the need to use polymers or iron based cross-linkers that may lead to potential damage mechanisms.
Balanced Injection and Production Technique for Horizontal Wells Based on Inter-Well Connectivity
Authors: Zhang Yanhui , Zhang Hongyou , Liu Yingxian , Wang Shaomeng , Wang Chengcheng 
Published: February 2022

Abstract
Because of the long horizontal length and the reservoir heterogeneity, the water production and injection are different along different locations of a horizontal well. So the conventional water injection string are not suitable for horizontal wells. Besides, the conventional models for inferring interwell connectivity between directional wells are not suitable for horizontal wells. In this paper, a new model for inferring interwell connectivity between horizontal wells is built and a new water injection string for horizontal injector is presented which can meet the demand of water injection of different locations for a horizontal well.
Based on the conventional water injection string, a new packer was installed at water injection string with the location's deviation less than 60 degrees. A Water distributor working cylinder was installed to respectively distribute water to root and toe of a horizontal well. Inorder to characterize different sections of a horizontal well, a horizontal well can be considered as several directional wells with different physical properties such as permeability and porosity and so on. Based on this, the reservoir is characterized as a coarse model consisting of a number of interwell units which is controlled by any two directional wells. Injection and production data were used to infer interwell connectivity and geological characteristics.
The results obtained from the new proposed model are in consistent with the oxygen activation of injectors. Interwell connectivity coefficient of each injector were calculated and the preponderance flow paths were found. Based on this, profile control were conducted. After profile control, the water injection efficiency of horizontal injectors obtained by this model improved and water cut of produces was reduced by 9% ~ 10%.
This technique has been used in nearly 100 wells of Bohai oilfields. With the inter-well connectivity method and the balanced injection string for horizontal wells, the development effect of reservoir with horizontal wells improved significantly.
CO2 Storage Capacity Prediction In Deep Saline Aquifers: Uncertainty and Global Sensitivity Analysis
Authors: He Xupeng , Zhu Weiwei , AlSinan Marwa , Kwak Hyung , Hoteit Hussein 
Published: February 2022

Abstract
Geological CO2 sequestration (GCS) has been a practical approach used to mitigate global climate change. Uncertainty and sensitivity analysis of CO2 storage capacity prediction are essential aspects for large-scale CO2 sequestration. This work presents a rigorous machine learning-assisted workflow for the uncertainty and global sensitivity analysis of CO2 storage capacity prediction in deep saline aquifers. The proposed workflow comprises three main steps: 1) dataset generation — we first identify the uncertainty parameters that impact CO2 storage in deep saline aquifers and then determine their corresponding ranges and distributions. We generate the required data samples by combining the Latin Hypercube Sampling (LHS) technique with high-resolution simulations. 2) surrogate development — a data-driven surrogate is developed to map the nonlinear relationship between the input parameters and corresponding output interests from the previous step. The implementation of Bayesian optimization accelerates the tunning process of hyper-parameters instead of traditional trial-error analysis. 3) uncertainty and global sensitivity analysis — Monte Carlo simulations based on the optimized surrogate are performed to explore the time-dependent uncertainty propagation of model outputs. Then the key contributors are identified by calculating the Sobol indices based on the global sensitivity analysis. The proposed workflow is accurate and efficient and could be readily implemented in field-scale CO2 sequestration in deep saline aquifers.
Smart Predictive Maintenance Framework SPMF for Gas and Oil Industry
Authors: Alameldin Magdi 
Published: February 2022

Abstract
The O&G industry is facing big challenges which consequently raise the necessity for reforming its traditional business model and integrating digital disruptive technologies such as Digital Twins, Artificial Intelligence and Blockchain. A Digital Twin(DT) is defined as a dynamic intelligent digital replica/model of the physical system/process/service/people which enables just-in-time informed decision making and root-cause analysis using AI. DTs are implanted at different levels such as Equipment/Asset Level Twin, System Level Twin, System of Systems (SoS) Level Twin.
This research introduces a novel framework which is based on a Smart Secure Digital Twin (S2DT) to bridge the development gap compared to other leading industries such as manufacturing and automotive. The proposed model relies on Tiny Machine Learning (TinyML) to implement edge intelligence and solve the problems of transfer latency and data overload and consequently achieves low carbon footprint. Edge Intelligence (EI) reduces energy consumption and enhances security and perspective maintenance. The Blockchain Technology is used to solve the privacy, and cybersecurity problems [4]. The Extended Reality (XR) will be used to ensure proper training of operators, and industry 5.0 to boost collaboration between human and machine. At the component level, security is maintained by integrated the locally generated intelligence on a blockchain to insure immutability, and enhance security.
An Experimental Investigation of the Effect of Oil/Gas Composition on the Performance of Carbonated Water Injection CWI
Authors: Castañeda Jaime Orlando , Alhashboul Almohannad , Farzaneh Amir , Sohrabi Mehran 
Published: February 2022

Abstract
The objective of this research is to analyze, for the first time to the author's best knowledge, how an oil and solution gas composition affects oil recovery and differential pressure when a whole core, saturated with live crude oil, is exposed to carbonated water injection.
In the past, many authors independently conducted micro-model or small-diameter core floods to understand how carbonated water injection could affect the recovery of dead or live oil. However, only one author initiated a simple identification of the dominant role that hydrocarbon composition could play in the recovery factor of the system by using micro-models, which led to the development of this research. However, despite having partially identified the importance of this variable, and being a pioneer in this type of study, the author's analyses were limited to the mixture of methane with either C6, C10, C16, or C17, which is far from reality.
Therefore, for the first time to our best knowledge, a new series of whole core flood experiments was performed, which involved the use of two types of crude oils, combined with three types of solution gases, two of which were multicomponent, to identify how compositional variability could affect oil recovery and differential pressure behavior when a whole core is exposed to carbonated water injection to displace these live crude oils.
The obtained results led to the conclusion that the amount of formation of the new gas phase depends mainly on the molar percentage of the C1–C7 components in the live crude oil, which result in an increase in the oil recovery factor; more importantly, it will result in a higher differential pressure. It was also concluded that slight changes in the composition of the live crude oil do not have a significant effect on oil recovery but do have a significant effect on the behavior of the differential pressure. To our best knowledge, this significant impact has not yet been identified. Further analysis led to the conclusion that the impact on the differential pressure is not mainly due to the methane content but depends more on the content of C2–C7 components.
Considering that the composition of the live crude oil is relevant for the formation of the new gas phase, and that the new gas phase can be considered as the dominant production mechanism for carbonated water injection in live crude oil, it was observed that the new gas phase has a significant effect on the oil effective permeability value, even reducing it by as much as half.
In addition, the author proposed a new correlation to calculate the saturation of the new gas phase in scenarios of secondary injection of carbonated water in strongly water-wet environments.
Finally, the system in which the highest recovery is achieved is the one with the richest gas, i.e., with the highest molar percentage of C1–C7 components, together with a non-water wet rock.
Quantification of Our Carbon Footprint while Drilling
Authors: Johnson Ashley , Mäkinen Anna , Fahim Syed , Arevalo Yezid 
Published: February 2022

Abstract
Reducing our operating carbon dioxide emissions is a critical step in mitigating the impact of our well construction operations. In order to bring a quantifiable benefit, we need a starting point. We need to measure our current emissions and identify the main drivers for the footprint. We can then identify best practices to reduce the impact and quantify how changing our drilling systems can reduce the CO2 generation.
Analysing the data available from two modern rigs we have measured the CO2 released for drilling different wells in different basins. We have also segmented the emissions by the rig systems using the power they consume. We show that the mud pumps are the biggest culprit for the CO2 release. The top drive draws less power; and while the draw works have a very high-power capacity, they only draw this for a very short period so overall their footprint is much less significant.
In order to make this work relevant for more than a small number of high specification modern rigs, we have built and validated an emissions model. Whereby we can calculate the CO2 released from measurements of the surface drilling parameters. As such, in real time we can generate a carbon emissions log quantifying the footprint and the split to major systems on any rig where we have access to these surface data.
Using the same model, integrated with our well planning processes, we can accurately predict the footprint from a particular well construction scenario and quantify the benefits which changes to the BHA, the drilling practices or the well design would bring. In the same manner, based solely on the surface drilling data, we can compare the environmental impact of all of our drilling operations at the same granularity we record the rig data. This lets us identify opportunities to reduce emissions and less efficient operations rapidly.
Artificial Intelligence for Plant Panel Operator Advisory
Authors: Macri Andrea , Smith David 
Published: February 2022

Abstract
Several refinery units are subjected to frequent changes in feed composition forcing panel operators to spend hours guiding the plant back to stable condition. Cumulatively, the plant loses multiple days of production per year with substantial economic losses.
Artificial intelligence algorithms can be trained and deployed to advise the panel operators on how to perform the best operation between different plant operating conditions.
An AI agent, via a deep R-L algorithm, is trained by trying thousands of combinations of actions to find the best possible sequence to stabilize the unit after a change in the feed. It is not feasible to use the real plant as the training platform. Instead, the AI agent can be trained safely and more efficiently using a first-principles dynamic simulation of the process. The dynamic simulation can be accelerated to run faster than real time, and it can be cloned to run multiple cases in parallel allowing to generate the equivalent of centuries of operation in just few hours. As described in this paper, replication of simulation instanced via cloud enhances the value of the simulation for this purpose.
The trained AI agent it is then deployed in the plant to give the panel operators a real-time view of when their actions deviate from the best possible operation [Figure 1].
This approach aims to reduce the time to complete the transition between different plant conditions resulting in higher revenue for the plant. The identified sequence of actions also minimizes the number and criticality of the alarms and it reduces the environmental impact by letting the AI agent determine the best approach to reduce emissions.
Solutions for Reduced Carbon Emissions and Advances In Power Generation
Authors: Verhoef Richard 
Published: February 2022

Abstract
Huge power consumers provide many opportunities for huge savings.
Floating rig saving 8000 liters of diesel per day? Saving 17 tonnes of CO2 per day? Those numbers are now realistic figures and not some far away dream.
Reducing emissions, the industry cannot escape from taking this message to heart and so the search for the right technology, specifically for the Oil industry, has started. In fact the search started quite a while ago and many companies have used their scarce R&D budgets to develop the solution that helps the industry achieve its goals. Budgets for developing ‘green’ technologies during an all-time low in the industry, with as bonus a global pandemic on top of it, has been challenging. But isn't it that in hard times the creative minds step up to come with the best ideas? If pressure makes diamonds, then developing ideas into products without proper budgets and resources, must have led to some breakthrough technology to save the earth. Together with our customers, NOV certainly has risen to the challenge and now has a wide range of technologies that provide a solution to a part of the puzzle. Combined these solution show the complete picture of what is possible. So what was the approach?
As with many technical challenges, there is not a single solution providing the answer, so when focusing on the issue at hand; ‘how can we help reduce emissions on drilling rigs’, NOV took on a big challenge and approached it at a granular level; breaking down the problem into smaller problems, then breaking down the smaller problems in manageable challenges. To start this all, that in order to reduce emissions, you need to know what causes these emission, where do they come from and how are they affected by location, type of operation, equipment used, people operating the drilling equipment, etc, etc.
To tackle the problem three major areas are focused on; what are the consumers for the drilling package (consumption), how efficient are these consumers being operated and what technology can be applied to lower fuel consumption
Formation Damage in the Hollín Sandstone: Diagnosis, Evaluation, and Stimulation Practices from Laboratory to Field Implementation, Sacha Field, Ecuador
Authors: Izurieta Alvaro , Squires Scott , Padilla Wilson , Peñaherrera Luis , Ruilova Mayra 
Published: February 2022

Abstract
This study describes different laboratory tests used to identify formation damage mechanisms associated in the Hollín sandstone. Traditionally Hollin sandstone is divided into two zones: Lower Hollin or Main Hollin and Upper Hollin, each one with unique characteristics as well as formation damage mechanisms.
Laboratory experiments for fluid customization (salinity sensitivity, completion brine sensitivity, regained permeability and relative permeability modifiers (RPM)) are performed to support the different techniques applicable to each reservoir.
Acid stimulation was proposed as the main stimulation technique since core flow tests demonstrate improvements up to 400%. Aditional treatments were tested to increase time between interventions such as fines stabilization blends and effective stimulation near water zones (RPM) or as chemical diverters.
A workflow for ranked candidate selection is describedwhich includes well, reservoir and mineralogy information available to categorize possible formation damage mechanisms as well as to recommended treatment type, volume and expected productivity post stimulation.
Job results from 2016 to August 2021 are included to support the overall investigation. Finally, additional treatment combinations are proposed to improve productivity and to extend the productive life of the well.