bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seismic Inversion of Reservoir Porosity with Neural Network Technology-A Case Study in Central Iraq
Authors: Xu Chao , Chen Chunqiang , Deng Jixin , Yang Tao , Yang Hong , Bai Hua 
Published: March 2022

AbstractUnderstanding the interwell distribution of the reservoir porosity is of great importance for well deployment to improve EOR. Seismic inversion with seismic and logging data is an efficient method to obtain the reservoir porosity. This study aims to demonstrate the spatial distribution of the reservoir porosity in an important formation in Central Iraq. 3D seismic attributes and logging data were combined to invert the reservoir porosity through neural network technology. The migrated 3D seismic volume, inverted P-wave impedance volume, seismic attributes and the logging data of 10 wells, were employed for training neural networks. Based on the training network, we generated the 3D porosity volume. To verify the accuracy of the inverted result, the inverted porosity were compared with those from the logging data of other 5 wells. Data slices were extracted with seismic horizons to show the lateral distribution of the reservoir porosity. The validation error shows the best multi-attribute pair is the pair of square root of P-wave impedance, quadrature trace, and instantaneous frequency. Neural network was trained with the three attribute pair. Analysis of the correlations between the predicted and the logging porosity showed the correlations from neural network training were higher than those achieved with multi-attribute regression. The porosity from the logging data of the 5 wells, which were not evolved in neural network training, coincided well with those from the inverted 3D porosity volume. That verified the accuracy of the inverted porosity volume from neural network inversion. Vertical sections and lateral slices of the inverted porosity volume were extracted to demonstrate the vertical and lateral distributions of the porosity, respectively. Data slices showed that the porosity were higher in the north and south area, and lower in the middle area. The study shows the porosity inverted from neural network technology is more reliable than that from muti-attribute regression. In addition, through this study, we demonstrate the porosity distribution in the project area. The new knowledge of the spatial distribution of reservoir porosity provides important guidance to the well deployment in the oilfield.
Using Data-Mining Crisp-DM Methodology to Predict Drilling Troubles In Real-time
Authors: Gharbi Salem , Al Majed Abdul Azeez , Abdulraheem Abdulazeez , Patil Shirish , Elkatatny Salaheldin 
Published: March 2022

Abstract
Drilling is considered one of the most challenging and costly operations in the oil and gas industry. Several initiatives were applied to reduce the cost and increase the effectiveness of drilling operations. One of the frequent difficulties that faces these operations is unexpected drilling troubles that take place and stops the operation, resulting in losing a lot of time and money, and could lead to safety issues culminating in a fatality situation. For that, the industry is in continues efforts to prevent drilling troubles. Part of these efforts is utilizing the artificial intelligence (AI) technologies to identify troubles in advance and prevent them before maturing to a serious situation. Multiple approaches were tried in the past. However, errors and significant deviations were observed when comparing the prediction results to the actual drilling data. This could be due to improper design of the artificial intelligent technology or inappropriate data processing. Therefore, searching for dynamic and adequate artificial intelligent technology and encapsulated data processing model is very essential.
This paper presents an effective data-mining methodology to determine the most efficient artificial intelligent technology and the applicable data processing techniques, to identify the early symptoms of drilling troubles in real-time. This methodology is CRISP-DM that stands for Cross Industry Standard Process for Data Mining. This methodology consists of the following phases: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation and Deployment. During these phases, multiple data-quality techniques were applied to improve the reliability of the real-time data.
The developed model presented a significant improvement in identifying the drilling troubles in advance, compared to the current practice. Parameters such as hook-load and bit-depth, were studied. Actual data from several oil fields were used to develop and validate this smart model. This model provided the drilling engineers and operation crew with bigger window to mitigate the situation and resolve it, prevent the occurrence of several drilling troubles. In addition to significant time and cost savings, CRISP-DM provided the artificial intelligent experts and the drilling domain experts with a framework to exchange knowledge and increase the synergy between the two domains significantly, leading to a common and clear understanding, and long-term successful drilling and AI teams collaboration.
The novelty of this paper is the introduction of data-mining CRISP methodology for the first time in the prediction of drilling troubles. It enabled the development of a successful artificial intelligence model that outperformed other models in predicting drilling troubles.
First Successful ESP-DST Well Test in Heavy Oil Unconsolidated Sandstone in Caspian Sea
Authors: Dosmukhambetov Issatay , Taubayev Bakhytzhan , Yesbolov Ualikhan , Sadykov Aikhan , Shmalin Muratbek , Akbayev Beibit , Kaipov Yermek , Ramatullayev Samat , Kuvatov Daniyar , Amanbayev Olzhas , Khaziev Bulat 
Published: March 2022

Abstract
The Caspian offshore is a prolific area for hydrocarbon accumulation. Since it is an offshore, it is a challenging area in terms of strict environmental regulations and safety. At the early stage of the project it was clear, that formation properties of the exploration well require artificial lift assistance to produce during well testing. Therefore, designing proper DST string with ESP was crucial to the success of well testing.
This paper describes unique combination of technologies and techniques that enabled a DST with ESP in combination with the Y tool, that provides capabilities to run thePLT below the pump. Also, one of the main challenges of well testing operation was to handle heavy oil fluid at surface. Being in environmentally sensitive area, designing a surface well testing equipment in a limited footprint, that enables efficient separation and disposal of heavy oil was very critical. Another challenge was unconsolidated formation with the high risk of sand production under drawdown, therefore downhole testing string and ESP pump supposed to withstand large quantity of solids during the production.
The key technology that enabled testing was a new generation of abrasion resistant ESP pumps, that are designed to handle extensive solids production. The heavy oil also posed a number of risks. The surface equipment was specifically designed to heat oil in the tanks and if required to mix with diesel before flaring operations.
Local regulation does not permit production during the night time and allows limited number of days for well testing. Therefore, well testing design must enable to acquire all necessary information within short period of test duration. The real-time data transmission and interpretation was a key to achieve main goal of the testing in exploration well - to accurately characterize the reservoir.
This was the first successful ESP-DST in Caspian Sea. Despite of many challenges, the technologies that were selected for well testing operation was proven to be reliable. This allowed Operator to untap previously not accessible hydrocarbon reserves.
Digital Lighthouse: A Scalable Model for Digital Transformation in Oil & Gas
Authors: Cadei Luca , Rossi Gianmarco , Lancia Lorenzo , Loffreno Danilo , Corneo Andrea , Milana Diletta , Montini Marco , Purlalli Elisabetta , Fier Piero , Carducci Francesco , Nizzolo Riccardo 
Published: March 2022

Abstract
Energy companies are latecomers to digitization with respect to other business, but new technologies like Big Data, Cloud infrastructure and Artificial Intelligence offer great opportunities.
Here we present an integrated approach to the digitalization of an O&G plant aiming to offer operator safety enhancement, production optimization and reduction of the environmental impact to maximize the asset value. This has been accomplished by complex and continuous work powered by the people who are the engine and the real target of the digital transformation process.
In the key study hereby presented, an all-round effort has been made to empower the operator's everyday work with digital and innovative tools supporting reservoir, maintenance, production and HSE workflow. Starting from a number of various legacy systems, a single integrated dashboard was built: The Integrated Operation Centre (IOC). IOC is now available on PC and smartphones to all site personnel both at the operational and managerial level.
New innovative systems were developed and deployed into IOC to capitalize on the data acquired during years of plant activities. Machine learning and advanced analytics solutions provide new daily insight on how to efficiently schedule maintenance operations and avoid off-specs and downtime on critical equipment, while complex production optimizers help technicians react to unexpected situations and maximize production.
Via IoT (Internet of Things) and portable devices, new tools and workflows were deployed onsite to ease the work and enhance the safety of workers with focus on usage of PPE and providing rapid information to locate workers during emergency situations.
People from both site and company headquarters ensured the success of the digital transformation by working together in an Agile Method during the development phase and by coaching in the roll-out phase. New professional roles, like data scientist and big data engineers, joined effort with experienced operators to ensure the success of this journey. This cooperation was at the basis of a comprehensive change management effort, which ensured a smooth and constant change in the way the personnel thinks, acts and reacts. This, we believe, is at the very heart of any fundamental transformation, being it digital or not.
Experimental Study on the Impact of Protective Packages, Iron, Oxygen and Stainless Steel on Polymer Stability
Authors: Al-Maamari Rashid S. , Souayeh Maissa , Al-Busaidi Intisar K. , Mansour Ahmed , Al-Riyami Omaira , Al-Mjeni Rifaat 
Published: March 2022

Abstract
Oxidative degradation of polymers is caused by combination of Fe2+ and O2 resulting in viscosity loss. During lab tests, synthetic brine without Fe2+ is commonly used. However, most lab and field set-ups are made of stainless steel (SS) which is a possible source of Fe. Therefore, this study investigates the impact of Fe2+ and O2 contents on polymer stability with/without contact of SS in presence/absence of protective packages (ITW and oxygen scavenger).
Polymer stability tests were conducted for 1 week at ambient temperature under different O2 concentrations. Four polymer systems were evaluated (without additives, with ITW, with oxygen scavenger and with ITW+oxygen scavenger). Samples were stored in SS and glass bottles. Different Fe2+ concentrations were added to the solutions in the glass bottles. The viscosity of the polymer solutions was measured at anaerobic conditions at different intervals.
Viscosity results for polymer samples aged in glass bottles showed that ITW alone or in combination with oxygen scavenger is able to maintain polymer stability up to Fe2+ and O2 levels of 2.5 ppm and 1500 ppb, respectively. At atmospheric condition, these systems were found efficient as the maximum obtained viscosity loss was &lt; 14%. While samples containing only oxygen scavenger maintained polymer stability up to Fe2+ and O2 levels of 2.5 ppm and 500 ppb, respectively, but experienced severe degradation when exposed to atmosphere. Similarly, blank samples experienced severe degradation after exposure to atmosphere and the stability was maintained up to Fe2+ and O2 levels of 0.5 ppm and 500 ppb, respectively.
Polymer solutions stored in SS cells experienced noticeable viscosity loss indicating that Fe is released from the SS and contribute to polymer degradation. The blank samples and samples containing oxygen scavenger were stable up to O2 level of 500 ppb. Addition of ITW into these polymer solutions boosted its viscosity stability up to O2 level of 1500 ppb. Exposing polymer samples containing either ITW or oxygen scavenger to atmosphere resulted in severe degradation of around 42% which is higher than the viscosity loss of the blank sample (28%). However, when both ITW and oxygen scavenger were added to the polymer solution and exposed to atmosphere, the viscosity loss was reduced to 26%.
This study showed that polymer stability in presence/absence of protective packages can be maintained at initial O2 level of 500 ppb. These findings are directly related to polymer stability during polymer preparation which needs to be considered in any polymer flood design. As protective packages might come handy for maintaining polymer stability in the reservoir, this study can aid in selection of the most feasible protective packages and water treatment requirements.
3D Enhanced Subsurface Data Visualization and Integration for Effective Horizontal Well Multi Transverse Fracture Development on a Clastic Tight Gas Field in Oman
Authors: Al-Suleimani Ahmed Abdullah , Chavez Juan Carlos , Abbass Hazim , Smaoui Radouan , Abassi Ahmed , El Hamal Bachir , Bachir Aissa , Poludasu Srichand , Yi Mi Chin , Attia Bilel , Ouenes Ahmed 
Published: March 2022

Abstract
Horizontal wells with multiple transverse fractures were defined as the key well architecture and completion strategy oriented to develop clastic tight gas accumulation otherwise impossible to be developed with vertical wells. However, a detailed evaluation during early deployment indicates the need for an integrated subsurface platform (ISP) covering geophysics, geology and geomechanics, to support well placement, well orientation and hydraulic fractured design.
Detailed subsurface characterization was used to build the ISP. Geomechanical logs estimated using the drilling data, as wells as, wireline logs are used to define engineered completion strategies. The ISP provide us with three dimensional properties maps capturing lithogical, petrophysical and geomechanical properties distribution, this allow the identification of the properties anisotropy coveing key variables including, elastic properties, in-situ stress variation, stress rotation across the field and stress anisotropy, thecombination of the predicted stimulated reservoir volume and the dynamic model, both part of the ISP, were used to access potential production forecast for selected well locations.
The ISP support the identification of geological sweet spot to definelanding zones and optimizing the hydraulic fracturing to improve the production performance. We will discuss how the geomechanical evaluation provides us the spatially varying stress magnitude and stress orientation and strain across the tight reservoir units. The use of the geological and geomechanical data within the ISP can be used to estimate geomechanical half lengths that are used to improve fracture design. We will also discuss how completion optimization and number of perforation clusters can be defined to maximize gas production based on a better understading of the special variation of petrophysical, geomechanical and lithological properties across reservoir units.
The described integrated subsurface platform can be used to help optimize horizontal well placement, well orientation and fracture completion design. It will be discussed the procedures and process of integration geophysical, geological and geomechanical reservoir properties into the ISP, as well as, how this was used to support the continuous development of these tight gas accumulation in Oman.
Reproducing Core Wettability in Laboratory Core Restorations and the Influence of Solvent Cleaning on Carbonate Wetting
Authors: Piñerez Torrijos Iván Darío , Puntervold Tina , Strand Skule , Hopkins Paul , Aslanidis Panagiotis , Yang Hae Sol , Sundby Kinn Magnus 
Published: March 2022

Abstract
With the current reservoir engineering technology, it is not possible to measure wettability at downhole conditions. Therefore, laboratory work is necessary to correctly assess this parameter. Countless efforts have been made by reservoir engineers to obtain decent estimates of reservoir wettability. However, in many cases this objective remains elusive. This means that the current special core analyses (SCAL) protocols have not overcome this hurdle, and new approaches must be tested.
In this work, the effects on wettability of two different sets of organic solvents are studied in carbonates, and a new cleaning and restoration protocol is tested to reproduce wettability in carbonate core samples. Two water-wet chalk core plugs were restored with the same initial formation water saturation (Swi=10%), and then were saturated and aged in crude oil to create an initial wetting. Spontaneous imbibition (SI) experiments confirmed the reproducibility of the restoration process used.
After spontaneous imbibition, the two cores were cleaned with different methods, the first core plug was subjected to a mild cleaning process (kerosene-heptane) and the second one was cleaned with a harsh method (toluene-methanol). It was found that the mildly cleaned chalk core was slightly water-wet, and the harshly cleaned core appeared to have changed to a more water-wet state. Therefore, the solvent pair, kerosene-heptane, preserved more polar components at the carbonate surface than the toluene-methanol pair, the latter, was more effective in solvating and removing polar components from the rock surface, showing increased capillary forces in the SI test with heptane.
The last stage of the study aimed to reproduce the first induced wettability, this was carried out in two cores after a mild cleaning process. It was possible to closely reproduce the initial wetting of these cores. This was accomplished by controlling the injected amount of mild cleaning solvents and crude oil during the second restoration process. These results represent a successful first phase of research towards wettability reproduction and improved reservoir wettability evaluation. Furthermore, it represents a solid and modern alternative to the traditional SCAL approach.
An Iterative Approach to Enhance Frac Design and Economics While Developing Tight Gas Reservoirs
Authors: Yilmaz Koray , Umul Burc , Madha Moosa 
Published: March 2022

Abstract
These are exciting times for unconventional resource development across North America. This success has proven to be a driver for the rest of the world to attempt to emulate the game-changing results found in the industry. As a consequence, improved horizontal drilling and hydraulic completion technology are currently being disseminated to the rest of the world, where operators are seeking to replicate the North American success in tight reservoirs and shale plays of interest. This being further fueled by higher gas prices than are awarded in North America.
This paper introduces a work-flow process to describe how tight gas-sand potential was discovered in the Mezardere Formation in the southern part of the in Thrace Basin in NW Turkey. The process began with the development of an improved understanding of geology and reservoir characterization followed by the application of North American drilling and completion technologies to commercially extract hydrocarbons from previously uneconomic resources.
Design of hydraulic fracturing, including pad volumes, proppant and gel concentrations, stage volumes and typical pressure profiles, production profiles and well design parameters are established. The content also presents how completion designs can be improved in a vertical well application in existing wellbores as a means to mitigate capital risk in a horizontal development plan.
The paper concludes by showing how the successful extraction of commercial gas production from heretofore uneconomic portions of the Thrace basin has the potential to change the energy future in Turkey via dramatically improved production results over previous conventional completions. When results were made public, the basin garnered attention from many large E&P Operators. The results proved that improved economic enhancement of deep basin unconventional resources as possible; thereby changing and accelerating development plans for this type of play.
Deterministic Approach Towards Well Intervention Candidate Selection & Quantification of Parameters in Esp & Jet Pump Wells
Authors: Varma Nakul , Koshatwar Yash , Kumar Manish , Savelyev Anatoly , Jha Aneesh , Kumari Rekha , Nagar Ankesh , Srivastav Preyas , Srivastav Pranay , Nekkanti Satish , Bohra Avinash , Veermani Sanjeev 
Published: March 2022

Abstract
This paper aims to describe a model created to determine various important parameters to monitor oil producer wells with different artificial lift types: Jet Pump (JP) and Electric Submersible Pump (ESP) of Mangala & Aishwarya fields. The fields contain medium gravity viscous crude (10-40cp) in high permeability (1-5 Darcy) sands. In order to overcome adverse mobility ratio and improve sweep efficiency, polymer flooding was adopted. As the Polymer flooding proceeded, polymer breakthrough in producer wells was observed. The major challenges faced in producer wells is polymer/scale depositions realized during well interventions. This issue has surfaced in field due to polymer breakthrough in oil producers and mixing of produced polymer concentration in well fluid with scales, wax or other bivalent ions. Major concerns due to polymer deposition included, fouling of artificial lift system, decrease of well uptime, jet pump (type of artificial lift) & ESP efficiency decrease.
ESP & Reverse jet pumping are the major artificial lifts for the field, where power fluid is pumped through annulus and production is taken through tubing. With continued jet Pump fouling due to Polymer, wax & scale agglomerate, well uptime decreased. During jet pump redressing, polymer deposition has been observed in the body X-over (reservoir liquid path), check valve assembly, throat and spacer nozzle to throat inside jet-pump. Thus, a necessity was felt to address the issue with a proactive approach. Continuous chemical dosing method was tried and proven successfully, but it was not cost effective. Hence empirical based modelling was required which can quantify these parameters to plan for well intervention & well clean-up jobs. The developed model is "intelligent" and determines various parameters like – Productivity index(PI) of jet pump well without having suction pressure data, jet pump nozzle loss coefficient, ESP pump efficiency (ESP wear), annulus deposition & debris deposition in tubing reducing effective ID of annulus & tubing respectively. The model calculates from every newly logged Multiphase flowmeter rates, water cut, Annulus pumping pressure & tubing head pressure (THP) events and determines its approach of marking the risk levels of a well. With continued JP/ESP fouling, tubing deposition & PI drop due to Polymer, wax & scale agglomerate, well uptime & production rate is decreased.