bluuebunny/crossref_metadata_2025_split huggingface dataset:
LLMs, Embeddings and Indexing Pipelines to Enable Natural Language Searching on Upstream Datasets
Authors: Martin James Lee , Zanuri M Nur Arif , Sockalingam Muthu Kumar , Andersen Eric 
Published: February 2024

Abstract
Large Language Models (LLMs) are attracting an enormous amount of interest at the moment in many domains. Their general nature, and ability to "understand" natural language, has already stimulated multiple areas of research at our company. Here we successfully demonstrate a Natural Language querying system, which is able to search a large repository of unstructured exploration data. The system supports follow up querying on the returned results, plus automatic summarization of content.
The system is integrated into our novel end-to-end data-mining platform, which continuously mines our unstructured exploration data for new changes and indexes the results. Important in our method are the enrichment processes that occur prior to use of the LLM. Our approach avoids usual "chunking" techniques, which in our experience results in inferior results, especially in the multiple domain areas of Exploration. By integrating our novel ontology-model AI in the enrichment of the initial Index, we drastically boost the performance of search resulting from the LLM steps.
In order to perform the search, key parts of our unstructured data, plus the query itself, need to be transformed into a vector form. This is performed using the embedding feature of the LLM. For this work, we had around 500,000 embeddings to calculate. To improve performance these were indexed in a leading Analytics Engine as a vector object, allowing fast search via cosine or Euclidian similarity. A custom dashboard was made to allow fresh searches of the vector datastore to be returned for further analysis.
Our current search time across 500,000 embeddings is under 20 milli-seconds. Our custom dashboard returns the top matches for further interrogation and analysis. This includes follow-up Natural Language question support on the returned matches for summarization tasks and other customised querying. Since our exploration-specific, ontology model is able to tag each piece of data with over 40 exploration-specific labels, we are able to cross-examine the LLM returned results with the tags. Agreement on a range of queries - ranging from targeted, highly specific questions to general, open-ended queries - was surprisingly good.
Natural Language based querying of our unstructured data is opening a whole new approach to data discovery in our company. Tailoring it to the exploration domain has required specific domain expertise and a novel ontology-model be used to ensure relevant prompts and query results. Obtaining search results quickly has also required expertise and fine-tuning. Future directions include ingesting more data, scaling the support infrastructure and further capability enhancement.
Experimental Identification of Permeability Reduction Factors in the Danish North Sea During Produced Water Reinjection
Authors: Kurbasov Maksim , Feilberg Karen L. 
Published: February 2024

Abstract
Loss of formation permeability during reinjection of produced water is a challenge which occurs frequently in offshore and onshore oil and gas production. Because of this, production companies need to develop measures to increase the injectivity of wells, such as hydraulic fracturing and acid treatments, which incur additional operational costs of oil production. The risk of injectivity loss is higher in tight reservoirs such as chalk. This study presents laboratory experiments using pressure and temperature controlled core flooding techniques to demonstrate how complete blockage of the chalk core pore space can occur. An analysis of precipitates formed during the injection of mixtures of produced water and seawater into a chalk core from the Danish North Sea was carried out, and an experiment with synthetic produced water is presented to identify the processes in the pore channels as precipitation of salt crystals occurs.
The study includes an integrated approach for studying sediments formed during the reinjection of produced water and seawater, namely studying the solid material using a scanning electron microscope (SEM), identifying the type of chemical compounds using X-ray diffraction (XRD), building thermodynamic models based on Extended UNIQUAC, and determining the ionic composition of effluents using High Pressure Ion Chromatography (HP-IC).
As a result of the analysis of sediments obtained on cellulose filters and laboratory core flooding experiments, it was established that the main factor in reducing permeability is likely the formation of inorganic sediment in the form of the compound Fe3Si. Understanding this allows the industry to take a more targeted approach to the process of treating produced water before pumping it into wells and reduce costs during well operation.
Limitations of Language Models in The Oil & Gas Upstream Operations
Authors: Alsultan A. , Razak F. Abdul 
Published: February 2024

Abstract
Language models has powered a lot of applications and developments in the past years in different domains. One language model that became popular in the recent years is BERT which is used as a base for many different natural language processing tasks such as classification and question answering. We wanted to apply BERT on some upstream oil and gas related text and study its performance on this domain. We decided to choose classification as a task to experiment with it. We tried a mix of domain adaptation and transfer learning to understand the potential of language models in general and BERT in specific on our domain. Our results emphasized the need to create domain-specific datasets for the oil and gas world and subsequently build models using them.
Balancing Surface Facilities & Well Design to Comply with Cap-Rock Integrity in CO2 Storage Projects: Experience from UAE
Authors: Xu Siqing , Vantala Aurifullah , Ali Imtiaz , Baslaib Mohamed , Al Keebali Aaesha , Perumalla Satya , Samy Ayman , Concilio Luciana , Singh Hemant , Mascagnini Carlos , Pandya Shekhar , Kasekar Hiren 
Published: February 2024

Abstract
CO2 injection is different than oil and gas injection, where CO2 phase changes are very likely to occur inside tubing at various operating conditions, especially in depleted gas reservoirs during early stages where reservoir pressure is low, and CO2 can change from supercritical to gas phases at various depths inside tubing when flow approaches perforation intervals. This is a dynamic and transient behavior, and modelling wellbore pressure and temperature during the life of the well (early, mid and late) is essential and can provide better understanding of the potential risks that are associated with CO2 injection and the appropriate actions and mitigation plans. Severe cooling due to phase changes and Joule Thomson effects inside tubing, as well as cycling of cooling and heating conditions, can negatively impact well and reservoir integrity including cap rock.
This paper presents a case history of a CCUS project in the Middle East where wellbore pressure and temperature modelling showed a significant impact on surface facility design, and a geomechanical model was constructed to investigate cap rock integrity as well as the safe operating envelope for CO2 injection. The workflow included modelling of seven time-steps to represent CO2 injectivity performance and pressure/temperature profiles inside tubing from start to the end of the project. In addition, sensitivity analysis was considered for CO2 impurities at each time step. The results feed the geomechanical study to ensure reservoir and caprock integrity during injection as well as surface facility design and mitigation plans.
The results showed that high purity CO2 can yield significantly higher injection rates compared to a low purity scenario. During early stages of injection, low bottomhole injection temperature was observed. Injection under low temperature may jeopardize reservoir and caprock integrity. Potential solutions to mitigate such issues are to consider heating CO2 at surface at early stage or to use smaller tubing size which may impact the injection capacity. Early stage during injection is the most critical period and may impact completion design and reservoir/cap-rock integrity. Hydrate risk assessment was conducted and showed that surface conditions are close to the hydrate risk zone. The operational philosophy has been modified to consider a surface heating unit to be used during the early stage of injection until reservoir pressure builds up.
This paper presents the importance of detailed wellbore pressure and temperature modelling during CO2 injection and how this can impact the integrity of the project as well as the operational philosophy. Workflow and risk assessment are also presented.
Sun Powered Green Hydrogen - A Comparative Analysis From The Kingdoms of Morocco and Saudi Arabia
Authors: Szemat-Vielma Waldemar , Scheibz Jurgen , Kasraoui Nihad , Al-Omar Faisal 
Published: February 2024

Abstract
The renewable energy sector, particularly the solar PV generation, is to play a key role in the energy transition and decarbonization process and the green hydrogen production is a subsequent element of this decarbonization process as a clean energy carrier. When power output from these renewable installations exceeds the grid requirements, instead of stopping the energy generation, that power surplus can be used to produce hydrogen by electrolysis process.
Despite being a technically simple process to produce via electrolysis, fuel cost and equipment are the two most significant economical elements to consider as part of the LCOH equation and act as economical boundary conditions. Combining an in-depth analysis while applying the financial modeling toolbox, this project has evaluated specific conditions for solar PV installations in Morocco and Saudi Arabia markets in terms of a techno-economic analysis for a potential investment for green hydrogen production in 2021 as well as near future projections in 2023 and 2025.
The most potential application of green hydrogen production and usage is to decarbonize heavy industries (e.g., cement and steel) that cannot be electrified but this will require an extensive transport infrastructure with low-cost incidence for the green hydrogen to be an economically viable solution. Near future projects will require public funding in the form of grants or tax redemption to scale up to economical maturity.
After carrying out a detailed financial modeling and a discounted cash flow valuation model, the resulting LCOH for Morocco is $3,2695/kg while Saudi is $1,5757/kg as of the end of 2021 with a projected reduction to reach $2,3678/kg and $1,4417/kg respectively in 2025, which means that by 2025 both countries will be below the $1,5-2,5/kg green hydrogen threshold, on a competitive level with fossil fuels, enabling both countries to grasp unique commercial opportunities to lead the implementation of a green business models towards a hydrogen economy, and eventually a net zero world.
The paper will elaborate on the rational driving the need for green hydrogen, will elaborate on the geopolitical framework supporting this emerging business and dives in with the techno-economic analysis while creating a 2023-2025 look-ahead.
Strategies to Design Fit for Purpose EOR Pilots by Integrating Dynamic and Static Data in a Highly Heterogeneous Oolitic Carbonate Reservoir
Authors: Khan Mohammed Yunus , Al-Murayri Mohammed Taha , Eadulapally Satish Kumar , Al-Mayyan Haya Ebrahim , Alrukaibi Deema , Al-Kharji Anfal 
Published: February 2024

AbstractUmm Gudair Minagish Oolite is a heterogeneous carbonate reservoir with random intermittent micritic units forming low permeability barriers to fluid flow. The facies, permeability variations and barriers have limited lateral extension. Therefore, different strategies need to be designed to implement accelerated fit-for-purpose polymer injectivity pilots without compromising the proper assessment of key parameters such as polymer injectivity, polymer adsorption, resistance factor, in-situ rheological properties, volumetric sweep efficiency, incremental oil gains, and polymer breakthrough.The field is divided into geological sub-regions based on reservoir scale heterogeneities by integrating static and dynamic data. The pilot location for each region is selected such that it shows minimal variations in reservoir properties in terms of facies, permeability, and extension of barriers. Simulation results were analyzed for each considered pilot area based on injectivity, pilot duration, oil peak rate, overall polymer performance and economics. Using these parameters, pilot design and locations are ranked while emphasizing the need to reduce the number of additional required wells to de-risk polymer flooding as a precursor for commercial development.Based on time-lapse saturation logs different sweep zones are identified and correlated with the facies. The maximum oil swept is observed in clean Grainstones. The facies characterization along with production data were used for defining the geological sub-regions. The pilot performance was analyzed using high-resolution numerical simulation for each geological sub-region, using high-salinity produced water. Thereafter, pilot design and locations were ranked based on dynamic performance. The best performing polymer injectivity pilot, with limited well requirements, was selected for field implementation including one injector and one producer with an inter-well distance of 80m. The envisioned pilot duration is 6 months showing promising incremental oil gains from polymer injection compared to water injection. Besides incremental oil gains, the utilization of produced water for polymer injection improves operational efficiency and cost optimization.
Far Field Petrophysics Utilizing Deep Resistivity High Definition and Ultra-Deep Resistivity 3D Inversion in Thin Laminated Reservoirs
Authors: Manuaba Ida Bagus Gede Hermawan , Ghanim Rayan Adil , Bikchandaev Eduard , Taher Ahmed 
Published: February 2024

Abstract
Resistivity measurement is a fundamental tool for evaluating reservoir fluid and rock properties. This technology has evolved over the past few decades to address different challenges. It has been utilized widely as the primary geo-steering measurement given its large depth of investigation compared to other logging measurements. Near wellbore resistivity measurements are used for evaluating the saturation and identifying the borehole fluid while deep and ultra-deep resistivity tools are used for well placement.
Conventional deep azimuthal resistivity tools can map resistivity at a distance with limited depth of investigation and a limited number of contrasting layers. In contrast, ultra-deep resistivity technologies see deeper but don't generally detect thin layers. Recent development of new deep resistivity high-definition technologies, with associated inversions, has resulted in higher depth of detection with better definition of the thin layers. This is due to improved antenna design, better signal-to-noise ratio, and multi-frequency transmission. 3D inversion of ultra-deep resistivity has enabled reduction of near wellbore cell size for mapping thin zones. This helps define more formation detail while reducing the uncertainty in the resistivity values mapped for these layers.
An innovative workflow for far field saturation has been developed based on acquired resistivity data, combining multiple sources from near wellbore measurements, offset logs and inverted resistivity data. The workflow has been tested on conventional deep resistivity data, and while this provides a good indication of the saturation away from the wellbore it doesn't provide a detailed definition of the thin layers further away from the well trajectory. Deep resistivity high-definition inversion and 3D inversion of ultra-deep resistivity with reduced near wellbore cell size has been tested in multiple wells and clearly provides improvement in the detection of multiple layers away from the wellbore, including with thin layers. It has been used as an input to generate far field saturation maps and has provided analysts with a better definition of the reservoir properties at a distance, which is key to current and future development plans.
This paper demonstrates the improvement in far field saturation mapping utilizing the high-definition deep resistivity inversion and 3D inversion of ultra-deep resistivity with reduced near wellbore cell size. This represents a step change in far field petrophysics.
Comparing Product Performance Through Time of Silicone Based Defoamer and Polyalcohol Based Defoamer in Aqueous Fluid
Authors: Bu Khawwah M. A. , Alrammah S. A. 
Published: February 2024

Abstract
Foaming in water based mud is considered a major issue that drilling operations might encounter that causes several issues such as decreasing in mud weight and makes the assessment of the fluid volumes very difficult, and complicated while fluid mixing process at the correct rate and at the required density. During operation, lower gel strength reduces the degree of foaming encountered, but will often compromise the cutting support and removal properties of the mud. The addition of the defoaming and/or antifoaming agents such as polyalcohol based, and silicone-based products is used to eliminate the foam. Alcohol based defoamer composition is hydrocarbon chain and oil carrier fluid, and silicone-based defoamer composition is silica-based material with the organic solvent then coating the material with polydimethylsiloxane (PDMS). Two generic water based mud formulations were mixed where foam was guaranteed then, two different types of defoamers were added separately to eliminate the foaming. Antifoam timing and amount were observed during the addition. The process included examining the defoamer performance with brine contaminated formulations.
In this study, comparison of results between polyalcohol based and silicone based defoamers in two types of salts provided an evaluation of the behavior of defoamer through comparing antifoam timing and amount were studied by conducting performance tests within laboratory conditions.
Zwitterionic Surfactant as Shale Swelling Inhibition Additive in Water-Based Drilling Mud
Authors: Gbadamosi Afeez , Murtaza Mobeen , Patil Shirish , Kamal Muhammad Shahzad , Hussain Syed Muhammad Shakil 
Published: February 2024

Abstract
Shale swelling occasioned by the interactivity of clay minerals and water-based mud (WBM) remains a major source of concern during drilling for hydrocarbons. This is because the interaction has the tendency for causing formation damage, wellbore instability, and well blowout if not properly managed. Herein, novel synthesized carboxybetaine zwitterionic surfactant was investigated as a shale swelling inhibition additive in WBM. Firstly, the effect of the surfactant on the electro-kinetic and dispersion stability of the WBM was determined. Moreover, the surfactant effect on the rheological property of the WBM was measured. Subsequently, linear shale swelling test was conducted to evaluate the clay hydration inhibition potential of the surfactant using an OFITE dynamic linear tester. Experimental result depicts that the carboxybetaine zwitterionic surfactant reduced shale swelling by ≈ 42% compared to the conventional WBM. Moreover, rheological test indicates that the WBM containing surfactants exhibited lower shear stress compared conventional WBM. Finally, the surfactant-stabilized drilling mud displayed high colloidal and dispersion stability compared to conventional WBM. The mechanism of zwitterionic surfactants for clay hydration and shale swelling inhibition additive was perused. Overall, this study indicates that betaine-type zwitterionic surfactants are suitable as shale swelling inhibition additive in WBM.
Post-Match Ensemble Analytic Techniques to Investigate Posterior Forecast Uncertainties
Authors: Forte S. Lo , Rossa E. Della , Aly M. Amr. , Grilli F. , Radice E. , Vecchio E. 
Published: February 2024

Abstract
Ensemble history matching is an effective tool which allows for uncertainty quantification, but it could be very time consuming. We show that some basic techniques can be used to reduce involved workflows complexity and computational time. The objective is to present how the statistical analysis techniques, commonly used for initial ensemble quality check, can be applied to the ensemble of matched models to highlight the major source of uncertainty and post-match forecast impact.
With ensemble history matching an initial set of different models is conditioned to production history. To create the initial ensemble, all relevant uncertainty parameters are selected after sensitivity and included using a workflow, which can become very complex and time-consuming, inside a geo-modeler. More realizations are requested until the initial ensemble passes quality check analysis. An iterative algorithm, requiring a preset number of iterations, has been used to match the ensemble of model realization. The matched models are then used to determine the forecast production profile range. Different methods are then applied to understand the most impacting parameters on forecast outcomes.
The uncertainty analysis workflow is applied to a tight gas field with some years of production history (early development phase) that is going to be integrated with other fields as a part of an LNG project. Initial sensitivity analysis helped to reduce the included uncertainty parameters preserving the original forecast uncertainty range but reducing the workflow complexity and the needed computational time. All updated ensemble realizations have been used for further analysis on the forecast. Analyses performed on matched ensemble (including correlation analysis and clustering) were used to highlight the most impacting parameters on forecast outcomes and to select most representative cases to be inserted in integrated asset models. The choice of the cases has been guided by the most relevant outcomes for the projects (like total field gas production and gas plateau length) and most relevant impacting parameters.
The presented uncertainty quantification workflow and associated analytic techniques have led to a roughly halving of the standard time needed for the uncertainty analysis (after history match) of the tight gas case. Further analysis on the posterior uncertainty helped in risk mitigation and its consecutive decision-making by changing the original drilling schedule to accelerate data acquisition that can reduce the forecast uncertainty range.