bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Inflow Performance Relationship for Shale Gas Reservoirs Using Well Logs and Geochemistry Data
Authors: Oshaish Ali , Alnuaim Sami , Hassan Amjed , Mahmoud Mohamed
Published: October 2023

Exploiting the unconventional oil and gas resources has been sparked recently. Evaluating the well productivity in shale formations based on bare test rates is challenging and requires extensive work of simulation and extended periods of well testing. This work introduces a new, simple, and efficient IPR model for estimating the production performance from unconventional shale reservoirs at early stages of drilling and production. The implementation of this IPR model depends mainly on the integration between well logs and geochemical pyrolysis data to estimate the hydrocarbon potential in the reservoir. The proposed IPR model was applied using real data from shale gas reservoirs.

In this work, the well logs were initially analyzed to stratify the pay zone and to obtain the gas saturation. Then, an analytical correlation was derived to convert the organic richness indicator of the free and adsorbed gas (S1) to an incremental porosity and gas saturation values. After that, the final porosity and saturation profiles, along with the other petrophysical data were incorporated into a fractured reservoir simulation model using a commercial reservoir simulator (CMG). Then, the production outcomes of the simulation model were collected to be used in generating the IPR model as a function of the petrophysical and the pyrolysis data.

The results showed an excellent correlation between well performance, logging, and the pyrolysis data. The developed IPR formula was found in the form of famous Fitkovich’s back pressure model which fitted the simulator generated production data at different reservoir pressures with R2 value of 0.99 for different reservoir pressures. Moreover, the exponent (n) in Fetkovich’s IPR model which ranges from 0.5 to 1 in conventional reservoirs, was found to be greater than 1 in unconventional shale gas reservoirs. This finding was examined in a case study using real production data. On the other hand, the log C value, which is involved in the y-intercept of the logarithmic transformation of Fetkovich IPR, was seen to be dependent on reservoir’s characteristics and geochemical properties such as bed thickness, gas saturation, porosity, and organic production index (PI).

Overall, the study aims to develop a simple IPR model to estimate well productivity in shale gas reservoirs based on the available logging and pyrolysis data during the early stages of drilling and completion. Moreover, the proposed model can be integrated with Logging While Drilling (LWD) operation for real-time estimation of well productivity. For the first time, the geochemical properties are integrated with the logging data to provide an IPR model that considers the free and adsorbed gas in the shale formations.
Petrophysical Reservoir Property Prediction from Seismic Data. Bridging the Geophysical Properties to Geological Information. Case Study from Marib Basin Yemen, Alif Formation
Authors: Al-Maktari Amin , Al Shadadi Aref , Ali Al-Rawqi Mohammed , Aly Omar , Ibrahim Aya , Nafie Tarek
Published: October 2023

Objectives

The objective of this study is to understand the reservoir properties distribution of the Alif formation from seismic data and to Enhance the seismic interpretation model for well planning Support. This is to minimize the drilling risk associated with rapid spatial heterogeneity and compartmentalization of the current reservoir rocks. Seismic inversion and Rock physics are powerful tools that delivers information about intra-wells rocks elastic attributes and reservoir properties such as porosity, saturation, and rock lithology classification.

The paper provides detailed and comprehensive technical details of the Surface Seismic and Rockphysics Inversion study that has been carried out on the current project to characterize the reservoir properties of the Alif formation from the seismic

Challenges

There are several challenges related to the characterization of the current reservoir rocks. The reservoir rocks are affected by a series of complex fault systems. In addition, the rocks are characterized by a high horizontal and vertical heterogeneity of their reservoir properties distribution (Porosity, Saturation, and Rock Facies), which is tough to resolve using seismic imaging techniques alone.

It was crucial to go beyond seismic imaging techniques to better characterize the reservoir rocks in terms of reservoir properties such as Effective Porosity, Water Saturation, and Rock, Classification.

Geophysical logs including sonic and density logs, measure rock properties near the borehole. The reliability of these logs is affected by borehole diameter and shape, as well as drilling fluid invasion. Acoustic well logs need to be conditioned before being used in geophysical analysis as any error propagate through the subsequent processes.

Surface seismic data quality is impacted by residual noise, multiples contamination, and improper amplitude balancing. To optimize processing for inversion studies. Processes include curvelet domain noise attenuation, high-resolution Radon anti-multiple, and extended interbed multiple Prediction. Offset dependent amplitude and spectral balancing are applied to maintain seismic amplitude fidelity.
Multi-Scale Reservoir Characterization of a Diagenetically Complex Tight-Gas Reservoir; The Miqrat Formation, Oman
Authors: Al Hajri Salim N. , Merletti German , Armitage Peter , Al Rashdi Khalil , Gray Ewan , Al Saadi Sawsan
Published: October 2023

The Miqrat Formation is a Cambrian tight-gas (low permeability) reservoir in the Khazzan and Ghazeer fields (Block 61), which together with the Barik Formation comprise the most prolific gas and condensate reservoirs in northern Oman. The reservoir quality of these sandstones is controlled by the depositional environment, ensuing diagenesis, timing of liquid hydrocarbon charge and subsequent replacement by gas and condensate. The development of the Miqrat is challenged by its geological complexity and this study demonstrates an integrated multi scale workflow to reduce risk and uncertainty in developing these reservoirs.

The Miqrat was deposited in alluvial plain and lacustrine sedimentary environments. The environment and provenance formed a mineralogically and texturally variable sediment at deposition, which has been diagenetically modified and degraded during subsequent burial history (maximum burial depth exceeding 5km). Understanding the heterogeneity of these sandstones at a range of scales is crucial in understanding the key risk of reservoir deliverability. To address this, we have accomplished a comprehensive core analysis programme including Nuclear Magnetic Resonance (NMR), and thin section petrology to identify the complex diagenetic and sedimentological controls on reservoir quality and their relationship to bound and moveable fluids. These plug scale measurements are upscaled to log scale where emphasis is placed on reservoir permeability. Log-derived models include porosity- and rock type-based trends. Water saturation models include the verification of potential deep conductive mud-filtrate invasion using resistivity modeling workflows.

Core-derived porosity and permeability plots show scattered, disguised trends demonstrating multiple competing controls on reservoir quality. Integration of post-hydraulic fracture clean up and flow tests provide additional evidence for larger scale reservoir complexity. Wells having similar log-derived gas absolute permeability thickness (KabsH) exhibit a wide range of initial reservoir performance. Core-calibrated, log-derived models are utilized to generate sand-thickness, pore thickness, absolute and gas effective permeability maps, to reveal the extent of the container, its space for fluids, and its lateral deliverability. Petrophysical maps are integrated to the understanding of hydraulic fracture propagation and well test results to further identify potential inter-well heterogeneity.

This paper demonstrates an integrated multi-scale workflow that effectively reduces uncertainty in the prediction of initial gas production to de-risk development in a complex reservoir.
Rig Sensor Data for AI-ML Technology-Based Solutions: Research, Development, and Innovations
Authors: Gamal Hany , Elkatatny Salaheldin , Al Gharbi Salem
Published: October 2023

The oil and gas industry is currently witnessing a notable shift towards automation and digitalization, driven by cutting-edge technologies like artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), and big data analytics. These advanced solutions are being implemented to enhance operational efficiency, improve profitability, and enable data-driven decision-making. Among the various segments of the petroleum industry, drilling operations for oil and gas wells hold immense significance due to the high sharing of the total well cost. Therefore, the adoption of technology-driven solutions is crucial to ensure safe operations and cost reduction. This paper presents the successful applications overview of machine learning in the drilling operations domain and addresses the existing challenges and future opportunities in this field.

Surface drilling sensors record real-time drilling parameters such as weight on bit, hook load, drill string rotation, drilling torque, pumping rate and pressure, and rate of penetration. These drilling data parameters provide valuable information about the characteristics of the drilled rock, requiring appropriate preprocessing techniques for data quality improvement. Data collection, preprocessing, analysis, and the development of machine learning models for prediction and classification in drilling operations are significant areas of research. Numerous researchers have utilized drilling data in machine learning applications to predict and optimize drilling rate, drill string vibrations, rock characteristics, and other important variables. These models contribute to optimizing drilling parameters, enhancing operational performance, and reducing costs. The paper technically discusses the achievements in ML research and industrial applications within the drilling domain that cover various ML techniques, different data sources, diverse training data for model features, and the target outputs from the developed models.

The research findings highlight the exceptional performance of ML applications, technically and economically, by showcasing successful case studies from the industry. Through the analysis of observations, valuable recommendations and potential future opportunities have been identified. These findings open up promising avenues for improvement and development in various areas. ML applications in drilling data have significantly contributed to the industry and academia by enabling real-time monitoring, advisory systems, automation, digitalization, and accurate prediction and classification through developed ML models.
Thermoplastic Lined Tubing: A Cost-Effective and Uptime-Enhancing Solution to Prolong Well Run Life
Authors: Alisaee M. K. , Al Hinai M. I. , Al-Mandhari S. , Al Riyami S. Y. , Al Saadi F. , Alhinai G. , Al Busaidi I. K. , Al Harthy A. H. , Al Masfry R. , Al Suleimani A. , Al Riyami H.
Published: October 2023

Production deferment and its associated costs are one of the key challenges in Well Reservoir Formation Management (WRFM) environment especially as wells are aging and frequently failing prior to their expected well life span. This could happen due to various reasons and one of them is the tubing erosion/corrosion in artificially lifted wells such as PCP and ESP. Therefore, the idea of installing thermoplastic lined tubing came up as an attempt to prolong the completion run life and thus reduce oil deferment along with CAPEX and OPEX.

Fields in South of Oman operate at harsh reservoir conditions. Wells are producing relatively heavy oil at high BSW and high sand content. In 2020, hoist intervened 31 times in two fields (A and B) with a total of 70 active PCP wells only. 74% of failures were attributed to hole in tubing and 60% of these had less than one year run life. These alarming statistics necessitated out-of-the-box thinking. Thermoplastic lined tubing came into a picture as a mean of reducing failures by minimizing the friction between tubing and pump rods. This new method was first piloted in PDO in four wells in field A.

Despite being installed for over two years, none of the wells in pilot have failed till to date. Completion run life has increased by double and nearly triple in some cases and wells are still continuously operating successfully. This is a great achievement when it comes to deferment and cost reduction. In field A & B, each hoist intervention cost $100-150k, and deferment might last for 20-40 days before well restoration take place.

Preliminary results showed a saving of three interventions per well within two years and an increase of well uptime. The successful results extended the current plan to full deployment that will include other artificial lift well types. Furthermore, more than 30 thermoplastics lined tubing installations are currently expected per year in different fields for different clusters in PDO.

Thermoplastic lined tubing has not only proven to increase completion run life but also improve workovers cost and has element of energy saving due to reducing friction loss between pump rods and the internal of the tubing. This means less pump torque and less power consumption to lift the fluid to surface with an estimated power saving of 7-10%.
Lessons Learnt on How to Do a Successful Pressure While Drilling Tests Despite Challenging Environment in Middle East
Authors: Al Riyami N. H. , Espinoza I. Baca
Published: October 2023

The pressure testing while drilling (PTWD) is one of the fastest ways how to confirm the reservoir pressure and mobility when planning the advance completions. An accurate evaluation of the pore pressure is helping to avoid the formation damage caused by overbalance and to reduce the drilling risks, associated with lost circulation, drill pipe stuck, as well as hole un-stability.

Some factors affecting the quality of pretests while drilling includes highly deviated and extended-reach horizontal drains; mud systems, such as heavy mud, oil-based mud (OBM), and high solid contents. Other challenges might be associated with unknown washouts area; well losses as well as the urgency of doing the pretests directly after drilling. The mixed lithology with various shale, anhydrite, carbonate, or sandstone content might reduce the permeability and affect the PTWD program’s success. To improve the quality of the PTWD several factors need to be assessed, such as potential loss of the seal due to the washout or fractures; sufficient timing for the mud cake; tightness of the zone above or below the probe; corrective sequence of the test parameters.

There are several scenarios were evaluated to enhance the PTWD performance. First, the mud invasion across the highly permeable formation was expected to form a fast mud cake. The results show that for the cases with mobility of more than 20mD/cP the sufficient repeatable test could be acquired as soon as 2hrs with pumps-off acquisition mode. Secondly, the cases across the tight formation with <10% p.u. were evaluated. Typically, the filtrate invasion in low permeability is very slow and if the PWD acquisition was too early, the pressure tests have no repeatability. In the third scenario, the tests were acquired 4 times across the same depth point with a very low porosity zone and a few hours between each pretest. It was visible how the mud was formed and how the pressure was reduced till the actual formation pressure only after 15 hrs from drilling. To avoid misleading pressure tests, it is recommended to plot the expected fluid gradient on top of a single valid point that has more than ~10 mD/cP mobility. For the cases with lower mobility, it is recommended to obtain three low-volume pretests with short build-up times and to repeat pretests in the nearby footage. The pump-off function is recommended for all pretests. For the cases where it is critical to have a real-time curve, it is recommended to repeat the test with pumps on only after completing the pumps off test. The OBM find to be helpful in wellbore stability and helps to improve the PTWD quality.

The result of this study shows the steps on how to plan the successful PTWD acquisition despite the formation and wellbore challenges. The quality check procedure would allow us to recognize valid tests and avoid making critical decisions based on false responses.
Characterizing the Stimulated Reservoir Volume Using Manifold Learning on 3d Motions of Microseismic Sources
Authors: Chakravarty Aditya , Misra Siddharth
Published: October 2023

Uniform manifold approximation and projection (UMAP) finds a low-dimensional representation of a complex dataset while preserving local structure and global distances present in high-dimensional data. Using UMAP, a high-dimensional microseismic data is transformed into a lower-dimensional, graph-based representation. In this paper, UMAP is applied on accelerometer signals recorded during an intermediate field-scale fracture propagation experiment at the Sanford Underground Research Facility in South Dakota. Our analysis shows that the short-time Fourier Transform of signals recorded by a single channel of the 3D accelerometer is the best feature extraction technique for the desired representation learning. For the first time, we have successfully identified the distinct fracture planes corresponding to each micro-earthquake location using accelerometer data from an intermediate-scale hydraulic stimulation experiment.

Due to the scatter of microseismic events and associated uncertainty of microseismic event locations, the assignment of reliable fracture-plane label to a microseismic event is possible only for a small percentage of events that have sufficiently high signal to noise ratio, and/or are favorably located for unambiguous assignment. In this paper, we also present a semi-supervised learning method based on UMAP for label propagation to assign fracture-plane labels to many unlabeled microseismic events, utilizing a limited amount of labeled data, which have pre-assigned fracture-plane labels. The proposed semi-supervised label propagation on a low-dimensional manifold achieves exceptional precision and recall (>92%) while employing just a small percentage (~20%) of microseismic events with fracture-plane labels. With just a small set of labeled microseismic events, it is possible to assign fracture-plane labels to four times as many microseismic events.
Serpentinization in Peninsular Malaysia: Implication for Hydrogen Generation
Authors: Ismail H. H. , Zhao H. , Rajput S. , Jones E. A. , Tan S. W. , Basori B. I.
Published: October 2023

Natural hydrogen is one of the key elements in the green energy initiative for the carbon net zero strategy of the world. Serpentinization is known as the most common process that generates natural hydrogen. This research work is aimed to gain a deeper understanding of the mineralogical composition and distribution of ophiolites in Peninsular Malaysia and to evaluate the potential of natural hydrogen generated from serpentinization processes. Field studies were conducted in various areas along the Bentong-Raub suture zone to study ophiolite rock occurrences in the suture zone. Standard petrographic and X-ray Diffraction (XRD) analyses were conducted to examine the mineralogical and chemical composition of rocks samples. The results show the majority of samples contain a significant amount of serpentine minerals such as antigorite, cronstedtite and lizardite, as well as some unaltered ultramafic minerals (e.g., forsterite, fayalite, pyroxene and hornblende), and secondary minerals (e.g., magnetite and chromite). The degree of serpentinization varies between 15% and 93% of the bulk volume with most samples exceeding 75%. Samples collected at Sungai Koyan, Cheroh, Bentong, and Bukit Rokan are characterized by high concentrations of antigorite, a type of Mg-rich serpentine. In contrast, cronstedtite, a Fe-rich serpentine mineral, is the dominant species in the samples from the Petaseh area. The mineralogy of the samples indicates hydrogen generation occurred via the reaction between fayalite (Fe-rich olivine) reaction with water, which is consistent with the observation that a significant amount of magnetite was found within samples from the Petaseh outcrop. Findings from a geochemical and mineralogical analysis reveal a significant serpentinization process along the Bentong-Raub suture zone, ultimately producing a substantial amount of hydrogen. These results highlight a potential natural hydrogen source in Peninsular Malaysia; however, supplementary research is necessary for further evaluation.
Development of a New Retarder Recipe Containing Boric Acid for Improved Performance Efficiency at Mid Temperature Range (MTR) in Oil and Gas Well Cementing Operations
Authors: Ohochukwu Chioma , Mathew Samuel
Published: October 2023

Various cementing retarders used in field operations where the Bottom Hole Circulation Temperatures (BHCTs) are in the range of 240F to 280F have been observed to pose deficiencies like the inability to adequately cover the entire temperature spectrum, especially towards its higher end. This study recommends a recipe that has more reliability across the entire temperature range.

API 10B-2 was adopted as the method of choice during the study's laboratory analysis. The thickening times for various concentrations of existing widely used mid-temperature retarders were analyzed to find out the temperature range in which the retarder works with its optimum performance efficiency. Then, the recommended recipe which combines Boric acid, and a lignosulfonate-based product was subjected to the same test conditions to reveal the maximum attainable temperature. These results were compared to show which recipe had the optimum performance.

The laboratory results obtained showed that despite the increasing concentrations of the reference mid-temperature retarders (MTRs), which were tested at different mid-temperatures, it was not possible to achieve extended thickening times especially as the test temperatures approached the higher end of the temperature spectrum (260F-280F); Some reference retarders, despite their claims to be used as MTRs, could not be used to design extended thickening time above 220F, others which were reliable at the lower end of the temperature spectrum, lost desired efficiency as the test temperatures increased up to 250F. However, the recommended recipe under study which combines a fixed concentration of the lignosulfonate-based product and varying concentrations of Boric acid was effectively reliable with better thickening time performance across the entire temperature spectrum from 240F to 280F.

This development introduces to the industry a reliable Mid Temperature Retarder (MTR) recipe that covers the entire spectrum of the mid-temperature range and allows for the design of both short and long thickening times.
India's Pioneer High Pressure Air Injection Process Design: An Evaluation of its Efficacy for Enhanced Oil Recovery
Authors: Singh S. , Sharma S. , Trivedi S. , Mishra G. , Meena R. , Mitra S.
Published: October 2023

High Pressure Air Injection (HPAI) is one of the most versatile EOR processes and offers several advantages over other processes in low permeability light-oil reservoirs. The current study illustrates a HPAI pilot design process for an onshore light oil field of India having permeability in the range of 1-15mD. Study included screening of the field, combustion tube tests to establish technical feasibility & spontaneous ignition, modelling of lab results to validate kinetics and pilot design through simulation.

Laboratory study was conducted on Combustion Tube (CT) System at IRS, ONGC, Ahmedabad. Here one-dimensional reservoir of ~2m length was created to physically represent reservoir condition in the CT and air was injected at high flux rate. To develop comprehensive kinetic model involving Thermal Cracking, LTO and HTO, the target oil was characterized based on maltenes and asphaltene.

Further lab results were modelled using thermal simulator to validate the developed comprehensive kinetics. Later, the pilot was designed through field scale simulation study using the validated kinetic model. A fine scale Geocellular model prepared with block dimensions 50*50 was used for pilot design.

In CT combustion front could be created, sustained and propagated. The average peak temperature of the stable zones was ~415°C with a temperature of ~600°C in the zones packed with native core, coke and shale. High peak temperature was observed due to catalytic effect of clay & coal present. Air requirement was 188 m3(ST)/m3, fuel consumption was 18.40 kg/m3, air to fuel ratio of 10.21 m3/kg and apparent H/C ratio of 1.21. Ignition was achieved within 12 hours of commencement of air injection at reservoir temperature (101°C) in second CT test confirming spontaneous ignition.

The combustion tube model using comprehensive kinetics showed satisfactory match of oil rates, combustion front velocity, and peak temperature. Typical combustion characteristics such as formation of coke, and change in viscosity with temperature were successfully captured in the tube run. The temperature profile just ahead of the front showed the LTO reactions taking place in that region.

In simulation, after history match, prediction variant was run with two inverted five spot patterns for pilot design. Simulation indicates average air injection rate of ~50,000 m3/d during the project life of 8 years. Envisaged incremental oil from the pilot area was ~12% above BAU case of the target STOIIP.

Based on the study, India's first High Pressure Air Injection project is to be implemented in the tight light oil field by April 2024. The comprehensive design of the process via laboratory, simulation and process optimization would lessen the uncertainty of the process and would pave the way for improving recovery from tight light oil field. Also, confirmation of spontaneous ignition in such reservoirs reduces the number of factors influencing the success of the process.
Optimization Design of Gravity Assisted Gas Drainage Combined with Pattern Flooding and the Application in Pilot in H Reservoir
Authors: Wang Rujun , Lian Liming , Zhang Chengze , Chen Dong , Xu Hanbing , Huang Zhaoting , Zhou Wei , Cheng Ronghong , Luo Ji , Fu Ying , Wu Yongping , Jin Quan , Dong Lisheng , Ka De'er , Chen Xiaobo
Published: October 2023

Gas flooding is one of the important technologies to enhance oil recovery and contributes over one third of world's EOR production. This paper provide a research method based on the combination of gravity assisted gas drainage and pattern gas flooding, trying to solve the problem that formation structure is complex possessing large dip angle and small formation amplitude concurrently. This design is finally applied in scheme of H Reservoir which includes H-L Reservoir and H-Y Reservoir.

Gravity assisted gas drainage and pattern gas flooding has been applied separately in the development of structural higher part and structural lower part. Laboratory physical simulation experiment, fine reservoir description and residual oil distribution have been researched to obtain higher oil recovery and gas-oil exchange rate. Multiple series of well patterns have been designed to according with multi-layer reservoirs. Stereoscopic well pattern will be reconstructed with gas flooding in the lower layers and existing development mode in the upper layers. This design has been used in the reservoir scheme of sandstone reservoir H. The combination gas flooding design and relative research methods proposed in this paper have been implemented in the reservoir scheme of H Reservoir.

The design and development model was applied in the H-L Reservoir enhanced recovery program and field practice. After 20 years’ prediction, the cumulative gas injection was about 100 Bcf, the cumulative oil production was about 15 MMBbls, the water content at the end of the period was reduced to 60%, and the degree of recovery was improved by more than 20 percentage points compared with the water drive.

The design and development model was applied in the H-Y Reservoir enhanced recovery program and field practice. After 30 years’ prediction, the cumulative condensate oil production was about 15 MMBbls, and the cumulative condensate gas production was more than 1000 Bcf. The EOR at the end of the test period was improved by over 28 percentage points compared with that of the depletion program.

The improved EOR technique of combination of gravity assisted gas drainage and pattern gas flooding is creatively applied in formation with large dip angle and small structure amplitude concurrently in this paper, and bring about a striking effect. Other technologies such as fine reservoir description, stereoscopic well pattern, perforation upward layer by layer, GAGD, et al. will also achieve jelly results. In addition, the application of CO2 GAGD - pattern flooding could converse into CCUS later, while HC- GAGD - pattern flooding could converse into gas storage later.
Digitalization as the Key Enabler to Unlock New Carbon Value Streams
Authors: Thiebaut De Kergret Malou
Published: October 2023

As regulators and financial institutions set high expectations to transition to net zero, climate-neutral operations became a requirement today. However, many companies in the industry face challenges in measuring their emissions in an accurate, consistent, and automated way. As regulations become more stringent, calculating its carbon footprint is critical to unlock value and avoid penalties for inaccurate carbon footprint reporting. In this paper, I will share how digitalization is the foundation for effective carbon footprint management.

While every company is unique one thing remains constant; measurement is the first step towards effective carbon footprint management. To achieve the best results possible scope creep must be avoided for effectiveness. Once the key emitting processing units are selected, the main sources of emission and measurement can be identified for scopes 1 and 2. With a Fit-for-plant mindset, real-time data, and digitalization, models can be deployed to automate emission calculations. Doing so lets you effectively measure and track the carbon intensity of your intermediary and final products in real-time and provides carbon data in your daily operation management.

Through implementing this approach with customers, we have seen benefits of reducing efforts and costs related to emission data calculation and validation from 3-4weeks of effort quarterly to 0days; freeing up 1 to 2 resources to focus on value-added tasks; identifying high emitters, operational discrepancies, equipment inefficiencies, and operational improvements to reduce emission from 18,000 to 7,000 ton CO2e/year for a 150,000 bbl/day for a deep conversion refinery and to save up to 0.5% of energy consumption. Furthermore, the approach helped reduce IT overhead as emissions and energy consumption are measured, validated, consolidated and reported through one readily available tool. Lastly, the customers were able to trace the carbon intensity into their final products and leverage this for new value stream opportunities.

Digitalization is the key to making the invisible visible and manageable. To track carbon, you must know where it comes from in real-time, so it becomes actionable. Quarterly or monthly calculations based on estimated and inaccurate emission factors methodology won't be sufficient for emission accounting and capturing opportunities arising with green premium and scope 3. This whitepaper offers a new perspective on carbon footprint management and the need for an automated emission calculation system to manage emissions effectively and track carbon. This will, in turn, unlock new value stream opportunities. Lastly, this paper highlights the workforce empowerment benefits and the financial considerations of emission granularity, as inaccurate emissions calculations will have financial implications in the future.
Fracture Characterization and Evaluation Using Fault Likelihood Technology Reveals Sub-Seismic Deformation Zones and Reduces Drilling Uncertainties in Abu Dhabi Unconventional Plays, United Arab Emirates
Authors: El-Din R Mahmoud Salah , Al-Marzooqi Hassan , Al-Blooshi Abdullah , Alharthi Amena , Al-Hashmi Abdulla
Published: October 2023

The main objective of this study is to maximize the efficiency of characterizing and evaluating naturally fractured unconventional reservoirs in the Emirate of Abu Dhabi, United Arab Emirates. Using routine 3D seismic interpretation methods in these highly fractured geological settings has previously led to the misinterpretation of seismic noise as fractures and potentially overlooking a great deal of sub-seismic detail. Consequently, a more advanced Fault Likelihood technology was used to overcome the challenges associated with this goal. This objective is intended to reduce drilling uncertainties, minimize the risk of drilling geohazards, and optimize hydrocarbon productivity in areas of dense natural fracture swarms.

An advanced Fault Likelihood approach was used in this study by calculating semblance across adjacent 3D seismic traces in elongated fault-like windows at different azimuthal and dip directions. The quantified semblance values are then used to locate possible faults at low semblance values between seismic traces after integration with dip and azimuthal values. A structural coherency filter was used to smooth seismic data along the main reflection dips without altering discontinuous surfaces, including possible faults. Fault Likelihood, azimuth, and dip volumes were incorporated to obtain a tracking volume.

The presence, shape, geometry, orientation, and distribution of each seismic-scale and sub-seismic fracture was possible to outline by using detailed analysis of the resulting fault likelihood volumes and visualization in the three-dimensional domain. Additionally, automatic fault extraction was applied to create more robust seismic maps of key horizons. Resultant numerous, low-uncertainty faults and fracture objects are to be used in the fault modeling workflow as part of static reservoir modeling. Results of this study are intended to be used in creating low-uncertainty, highly detailed fracture models that are of primary importance in the dual porosity nature of the unconventional reservoirs in the United Arab Emirates.

Routine manual fault interpretation is a tedious and subjective process in 3D seismic interpretation. If the subject area has many fractures and faults of various scales, structural interpretation will be very time-consuming and will not identify sub-seismic discontinuities. Therefore, automated fault interpretation and extraction is a better option. Alternative methods of routine edge-detection automated fault interpretation often give generic results that can misinterpret seismic noise as genuine geological surface discontinuities while overlooking a great deal of fracture presence and distribution. To resolve this challenge, the fault likelihood approach provides a breakthrough by improving fault attribute quality using three-dimensional seismic data.
In-Pipe Localization for Pipeline Intervention Gadgets
Authors: AlSharif Mohammed H. , Ba'adani Mohammad , Toro Frankly , Ghamdi Khalid , Zahrani Salah , Abdulmohsin Mohammed , Al-Jarro Ahmed
Published: October 2023

The in-pipe localization is a challenging task, particularly in underground buried pipelines, due to the blockage of GPS signals and the infeasibility of installing additional sensors on the already constructed multitude of networks of pipelines. This paper proposes a novel localization system that capitalizes on the detection of welds that are regularly positioned within a pipeline, via electromagnetic sensors mounted on a traveling device inside a pipeline. The welds are present as a result of joining each pair of pipe segments, known as spools, which are manufactured of a standardized length. The localization is achieved by means of recording the timestamp whenever a weld is detected, whereby the average velocity and travelled distance of the moving device can then be determined from two consecutive readings. The estimated average velocity and travelled distance obtained from the detection of welds are combined with the acceleration and angular velocity readings obtained from an inertial measurement unit to determine the location of the travelling device. The proposed system is designed to provide higher accuracy at lower computational complexity and hardware costs when compared to other existing systems, which often require both in-pipe and out-of-pipe interactions. Furthermore, the proposed system is designed attachable to and/or integrate-able with standard pipeline intervention gadgets (PIGs), robots, or other widely used intervention and inspection tools.
Hydrogen Blending in Gas Network – A Case Study of Jubail City in Saudi Arabia
Authors: AlShammari Saud , Haq Bashirul , Alshehri Dhafer
Published: October 2023

In recent years, Saudi Arabia's development has been blooming on many fronts. That necessitates an increase in energy demand. More than 60% of that energy generation is yielded from Natural Gas (NG). On a national scale, more than 200 million metric tons of Carbon Dioxide (CO2) is estimated from NG combustion for energy generation every year. This study will evaluate H2-NG blending network readiness in Jubail City, Saudi Arabia, to reduce CO2 emissions.

The gas network system in Jubail City is thoroughly studied to investigate the system's readiness for hydrogen blending. Different scenarios are considered to provide flexibility to adopt Hydrogen blending with the existing network without the need for any major upgrade. A gas network model of Jubail City is developed in PIPESIM-Net software to examine corrosion and erosion effects on the existing gas network with various CO2 and H2O concentrations. Furthermore, Hydrogen is introduced to the composition at different concentrations such as 5,10,15,20, 30, 40, 50, 60, 70, 80, and 90%. The model will be expanded to include all gas network components in the Kingdom.

The developed simulation model showed that the existing gas network in Jubail Industrial City could handle the target hydrogen concentration of 5 to 20 percent with no significant upgrade required. Additionally, worst-case scenarios for high water and CO2 saturation sensitivity analysis showed mild corrosion rate, with the latter causing a more noticeable corrosion rate. Also, the model showed no significant concerns for erosion, indicating that the pipelines are adequately sized. Finally, it is estimated that a 4 million metric tons reduction per year of CO2 emissions in Jubail Industrial alone that can be extrapolated to 20 million metric tons on a national scale.

This study will directly impact the global environment by evaluating Hydrogen blending readiness in Saudi Arabia, which will significantly reduce carbon emissions and support the Kingdom's mission to be carbon-neutral.
Finding Optimal Motor Valve Open Triggers in Plunger Lifted Wells with Offline Reinforcement Learning
Authors: Mayfield Walter , Lopez Felipe , Yu Yingwei , Wang Haozhu
Published: October 2023

Reinforcement learning is a novel approach for artificial lift in which optimal control policies are learned through interactions with the environment. This paper reports the first implementation of reinforcement learning for plunger-lifted wells using only historical data in an offline approach. The use of offline reinforcement learning allows production engineers to remain in control during the exploration phase, instead of allowing the agent to explore set-points that could result in unsafe operation. This paper explores the application of the Conservative Q-Learning (CQL) algorithm to maximize production in a small-scale plunger-lifted well model that mimics a low-pressure gas well controlled by the "minimum on-time" framework. The well was designed to receive a new open-trigger value for the motor valve from the CQL agent at the beginning of every cycle. The reinforcement learning problem was formulated to maximize gas production (reward) by adjusting the "casing-line" open trigger value (action) given the volume of fluid in the volume after the well has settled (state). Experimental results demonstrate that a dynamic policy that modulates the open trigger set point based on slug volume improves the average production rate by 35% compared with a static casing-line pressure trigger. The optimal policy suggests that using higher casing pressure open triggers for large slug volume cycles improves long-term production in plunger lift.
Practices of Low Carbon Transition of Tarim Oilfield
Authors: Deng Qianxing , Shen Fuxiao , Wang Kelin , Gao Jieyu , Li Ruyong , Wen Zhang , Wei Zhiqiang , Guo Xinyong , Liu Guode , Xia Xianwei , Miao Xinyue
Published: October 2023

The goals of carbon emission peak in 2030 and carbon neutrality in 2060 were put forward by China in 2020. However, the production of Tarim Oilfield reached 33.1 million toe(tonnes of oil equivalent) in 2022, with total energy consumption of 2.46 million tce(tonnes of coal equivalent) and total carbon emission of 2.2985 million tCO2e(tonnes of carbon dioxide equivalent). And the production is expected to exceed 40 million toe by 2025. Energy consumption and carbon emission remain increasing if effective measures are not taken, therefore, and low carbon transition of Tarim Oilfield is urgent.

In this context, greater goals that carbon emission peak by 2025 and carbon neutrality by 2040 have been proposed, and some measures have been taken. According to energy saving and consumption reducing, technical means like process optimization and torch extinguishment are adopted to strictly control energy consumption of new projects. As for substitution of clean energy, distributed photovoltaic, waste heat utilization and other measures are used to decrease carbon emission of the established production system. Meanwhile, CCS/CCUS pilot projects are carried out. Energy conservation, carbon emission reduction and substitution of clean energy are promoted by demonstration area. According to clean energy supply, large amounts of land such as deserts and Gobi in western China can be utilized, and many factors like natural resources, consumption market and power grid structure are also considered to develop new energy power generations which may be photovoltaic power station, solar thermal power plant.

Results of the net zero transition of Tarim Oilfield were remarkable last year. As for energy conservation and carbon emission reduction, two demonstration areas, the first zero carbon desert highway in China and Lunnan Oilfield were built with carbon emission of -14,000 tCO2e and 6,600 tCO2e respectively. And total energy consumption decreased by 0.46%, energy use decreased by 8.41% in intensity, and carbon emission decreased by 0.57% in intensity. As for clean energy supply, two 100 megawatts(MW) photovoltaic power stations have been built, generating electricity of 400 million kWh and reducing 311,700 tCO2e per year. And photovoltaic power stations with total capacity of 1100 MW are under construction, which are expected to generate 1.919 billion kWh and reduce 1.4955 million tCO2e annually. And the clean energy will not only meet its own demand, but also be provided for other enterprises.
Application of Digital Twin for Real-Time Early Identification and Warning of Pipe Stuck Using Hybrid Approach of Physics Model and Machine Learning
Authors: Zhang Jiawei , Huang Hongchun , Wang Haige , Wang Qing , Ji Guodong , Li Hong
Published: October 2023

Pipe Stuck is one of the predominant causes for drilling-related non-productive time (NPT). According to statistics, losses up to hundreds of millions of dollars are caused by pipe stuck globally each year. Early identification and warning of pipe stuck are essential for predicting and avoiding stuck issue once preventive measures are taken promptly. Typical detecting methods based on data fluctuation amplitude or curve trends subject to expert user experience and human error. Moreover, pipe stuck usually have already happened in most cases when noticed by these methods.

This paper presents an innovative system combing physics model with machine learning method, which enables automatically pipe stuck risk monitoring and warning while drilling. The new system combines these approaches: 1)real-time calculation of hook load, torque and standpipe pressure(SPP) for 9 different drilling states (rotary drilling, slide drilling, reaming, back-reaming, tripping in, tripping out and etc.) based on drill string mechanics and wellbore hydraulics model; 2)The calculated parameters are checked and calibrated automatically within set computing cycle to narrow down calculation error; 3) The deviation of actual parameters from theoretical modeled value and rate of change(ROC) of actual parameters are calculated and compared on time-series, based on which a pipe stuck risk index (PSRI) is proposed ranging from 0% to 100%; 4) With different risk index ranges, pipe stuck risk level is monitored and evaluated as low (green), medium(yellow) and high(red) on real-time basis. For historical wells with and without pipe stuck issues under different drilling states, thresholds for deviation and ROC of parameters corresponding to different risk levels are obtained by random forest algorithm (RFA).

The system is designed to provide users, driller or monitoring specialist a warning signal with prompt window jumping out and constant beep sound whenever a high-risk is identified. Once detected, preventive or intervention measures are generally mandatory for on-site personnels. Application cases showed that alerting warning of high-risk of pipe stuck could be realized typically between 30 minutes and 2 hours ahead during back-reaming and tripping operations, which demonstrated the system capability for early identification and warning of pipe stuck under different drilling states.

The new system showed that digital twin driven technique could provide effective solution for detecting the onset of pipe stuck, which could help to minimize NPT, better capture and utilize digital data for optimizing drilling.
Enhancing Drilling Operations and Management Through Digital Ecosystem
Authors: Zhang Jing , He Xusheng , Dai Yong , Wang Jinlu , Zhu Jun
Published: October 2023

The digitalization of the drilling process has revolutionized the oil and gas industry by incorporating digital technologies and data analytics into drilling operations. This transformative shift aims to optimize operational efficiency, enhance safety measures, and enable prompt decision-making.

In this paper, we will look into the various benefits of creating a digital ecosystem for drilling, focusing on improved operational efficiency, potential risk identification, advancements and application in smart equipment, enhanced communication and collaboration, and the reduction of operational expenses. We will also discuss a practical case study that demonstrates the effectiveness of digital ecosystem in reducing costs, minimizing downtime, and enhancing overall drilling performance.

Furthermore, the integration of VR simulation with digital twin models in the digital ecosystem for drilling holds immense potential for operators. By providing a realistic and immersive training experience, operators can optimize their drilling operations, minimize risks, and ultimately save costs. Through this exploration, we aim to highlight the transformative power of digitalization in the drilling industry and showcase the benefits that can be achieved by embracing this technology-driven approach.