bluuebunny/crossref_metadata_2025 huggingface dataset:
Combining Automatic Decline Curve Analysis and Geostatistical Methods to Help Analytical Predictions
Authors: Biver Pierre , Lesage Alexandre , Ong Anthony , Dor Dimitri , Estival Remi
Published: October 2023

Two main methods are used to provide robust production forecasts on existing and new wells. The first option relies on building a geomodel on which reservoir simulations are performed that require long engineering time. The second option is to use the Decline Curve Analysis (DCA) and type curve construction. This method delivers fast and accurate results but relies solely on production data, neglecting the geology, production mechanisms and is often not enough precise to predict future wells’ performance.

In this paper, two workflows combining geostatistics methodology with DCA will be detailed:Workflow 1: A 4 steps’ workflow based on DCA, Distance based Generalized Sensistivity Analysis (DGSA) and type curves. This workflow is relatively time consuming and needs the expertise of a reservoir engineer.Workflow 2: A methodology using DGSA and historical time series interpolation and net gas thickness map

Both workflows have been tested on a tight gas field in Asia to predict, in blind test mode, the cumulative gas produced in June 2022 from all the wells drilled since 01/01/2021 (18 months blind test on 105 wells).

There is no dynamic model available for the field. Wells are produced after fracking and some of them are equipped with velocity string installation.

The prediction of gas production over the last 18 months has been performed with both workflows and lead to similar results.

Overall, the cumulative gas production from all the 105 wells in the last 18 months is accurate at 88% for the more sophisticated workflow 1 and 82% for the simpler workflow 2.

At the well-by-well level the historical vs predicted cumulative production data have a correlation factor of 0.72 for workflow 1 and 0.67 for workflow 2.

Workflow 2 is sufficient to derive quick-look resources of future wells drilled but is less accurate than workflow 1. Both workflows can be run to estimate quick uncertainties.

This work shows the interest of selecting the most appropriate method depending on the accuracy needed to take a decision and the time available. Those two workflows can also be combined to derive uncertainties for stakes associated to future drilling phases evaluations.
Lite Optimisation and Recommender Systems for Maintenance Inventory Management
Authors: Visser J. D. , Carydias P.
Published: October 2023

Objectives/Scope

This work aims to develop a systematic methodology for the optimisation of maintenance inventory management, independent of industry or project lifecycle stages (greenfield and brownfield). The objective is to enable operators to integrate the use of ‘lite’ dynamic optimisation and recommender systems into existing or proposed business processes, systems, and ways of working. Additionally, this work aims to explore methodologies for enabling the sustainment and ongoing improvement of such systems within a complex asset management context.

Methods, Procedures, Process

Leveraging Natural Language Processing (NLP) algorithms to improve the speed and accuracy of identifying and cataloguing interchangeable materials and classifying failure modes from operational maintenance data. These algorithms enable comparative analytics across and within facilities, including reliability modelling, material demand modelling, and production vs maintenance optimisation models. This approach leverages foundational maintenance build analyses outputs such as FMECA, RCM, and cataloguing.

Results, Observations, Conclusions

Results highlight the ability of these ‘lite’ dynamic optimisation and recommender models to be deployed at speed and to be sustained, whilst enabling significant value gains, across production uptime, maintenance cost, and safety, at low cost (particularly when compared to large software systems). Such systems are also designed to be user and use case centric, enabling them to be dynamic and easy to configure. A recent implementation of our data-driven approach has led to 40% reduction in inventory value while increasing the critical spare materials to enable high asset availability.

Novel/Additive Information

Advanced text processing algorithms used in conjunction with advanced maintenance and reliability modelling techniques, packaged within ‘lite’ systems. These systems are also live and provide recommendations at a frequency suitable to the operator's business process requirements.
Using Drones to Improve Project Construction Monitoring
Authors: Shawky Mohamed
Published: October 2023

The advent of technology has brought forth substantial changes in various industries, significantly transforming their operational capabilities and enhancing their productivity. A notable innovation shaping the future of many sectors is the use of Unmanned Aerial Vehicles (UAVs), commonly referred to as drones. Among various fields, the construction industry, and in particular the oil & gas sector, has significantly benefited from integrating drone technology, especially in project construction monitoring [1].

Overview of Project Construction Monitoring in the Oil & Gas Industry

In the oil & gas industry, project construction monitoring plays a crucial role, ensuring that projects progress as planned and any issues are promptly identified and addressed. These monitoring processes traditionally involve numerous on-site workers, heavy machinery, and extensive time and resources [2]. However, the industry's dynamic environment, characterized by sprawling sites, hazardous conditions, and complex projects, necessitates a more efficient approach to construction monitoring. In response to these challenges, the industry is increasingly turning to drone technology [3].

Importance of Efficient Project Construction Monitoring

Efficient construction monitoring is pivotal for the timely completion of projects, maintaining budget constraints, and ensuring safety standards. Any delays or cost overruns in large-scale oil & gas projects can have substantial financial and operational implications. Moreover, efficient monitoring can help identify potential risks and issues early, allowing for preventative measures to be implemented, reducing the likelihood of accidents and promoting a safer working environment [4].
Photonic-Hydraulic Fracturing Hybrid Approach Minimizing Breaking Pressure
Authors: Batarseh Sameeh I. , San Roman Alerigi Damian P. , Alrashed Ahmed A. , Zefzafy Ibrahim
Published: October 2023

This paper presents a novel approach to reducing the hydraulic breakdown pressure utilizing near-infrared continuous-wave high-power lasers (HPL). The thermo-mechanical and thermo-chemical processes induced by the HPL illumination of the rock above a particular threshold can lead to lower formation strengths, significantly reducing the formation's breaking pressure. This HPL application could improve energy efficiency and reduce the risk of hydraulic fracturing operations.

The rock absorbs a portion of the HPL's energy as thermal energy, causing a localized temperature surge, resulting in various physical and chemical changes. The former arises from sharp and fast-developing thermal gradients that generate micro and macro cracks in the formation. The thermal-chemical transformations of the rock include mineral dehydration, dissociation, decomposition, clay collapse, and retorting of organic matter. This electromagnetic-based mechanism has been assessed and proven to effectively reduce breaking pressure for all types of rocks. The process is independent of the rock's stress state and composition. It was evaluated on carbonate, shale, and sandstone formations in the lab. The experimental results guided the development of the first high-power laser field system. The system design incorporates an HPL generator and the optical assembly needed to deliver and manipulate the HPL in the subsurface. The optical assembly includes a subsurface optical tool whose primary function is to control the size, shape, and propagation direction of the HPL beam.

The HPL technique was tested on various rock types. Pre- and post-exposure analyses were conducted to evaluate its efficacy. These studies included uniaxial stress tests, unconfined ultrasound velocity measurements, permeability, porosity, composition, grain shapes, contact, and cementation. This investigation provided valuable information about the physical dynamics of the process. The results show that this HPL method could reduce breaking pressure in all rock types. The technique and HPL perforation could create targeted weak spots in the near-wellbore formation, improving the precision of hydraulic fracturing while decreasing its energy intensity, cost, and environmental impact.
Mixture of Anionic Surfactant and Surface-Modified Silica Nanoparticles for Enhancing Foam Stability
Authors: AlYousef Zuhair , Cha Dongkyu , Almajid Muhammad , Ayirala Subhash
Published: October 2023

Foam is one of the most promising techniques to reduce gas mobility in subsurface formations. Foamed-gas injection can reduce the mobility of gas by increasing the volume of trapped gas in the liquid phase, thereby increasing its apparent viscosity to reduce the relative permeability. However, the poor stability of foam generated by surfactants at reservoir conditions is a challenge that hinders the effectiveness of the foam flooding. The mixture of surfactant and nanoparticles can offer a potential solution to enhance foam stability. The objective of this study is to evaluate how such new mixtures formulated in this work enhances the foam stability.

Foam analysis using foam analyzer equipment and nanoparticle size measurements, were conducted to capture the foam stability and strength for an anionic surfactant and the mixture of an anionic surfactant and surface modified silica nanoparticles. Also, transmission electron microscopy (TEM) was used to assess and visualize the surfactant-nanoparticles interactions using different concentrations of the nanoparticles.

The results from the experiments demonstrated that the use of surfactant combined with nanoparticles enhances the stability and strength of the generated foam when compared to the use of surfactant alone. Comparative images of bubble count and structure of the foams generated showed higher bubble count with smaller bubble sizes when the surfactant is mixed with the nanoparticles. The higher bubble count and smaller bubble sizes are indicative of better, stronger and more stable foams. TEM images showed that the nanoparticles have a tendency to form layered structures in the solutions. This formed layer enhances the film stability by delaying the liquid film rupture.

The combination of nanoparticles and surfactant serves as a new technique for generating stronger and stable foams in gas mobility control applications. This study also provides an important learning point that the selection of the right surfactant and nanoparticle combination are the keys to generate more stable foams.
Synthesis and Study on a Type of New Salt-Resistant and Slow-Expansion Gel Particles for Deep Water Control
Authors: Zhang Haiqing , Liu Qixin , Meng Luming , He Zhongtao , Wu Yining , Dai Caili
Published: October 2023

Enhancing the development of low permeability reservoirs is an important investigation direction for increasing crude oil production in China. Currently, prolonged water or polymer flooding in oil fields exacerbates reservoir heterogeneity. Leading to premature water breakthrough and high water cut significantly hindering efficient oil field development. It is difficult for oilfield production to control the preferential water pathways within the low permeability reservoir and expand the utilization degree of the deep remaining oil. The reservoir control agent represented by polymer gel particles can effectively control the preferential water pathways, expand the sweep range of injected water, and achieve oil field production and efficiency. However, inherent drawbacks of polymer gel particles, such as poor performance of salt resistance and water absorption, high initial hydration expansion rates and low post-expansion rates, present a challenge for in-depth migration and water control. To solve the above problems, in this paper, we prepared a gel particle with excellent salt resistance and water absorption performance, which can delay swelling as well. In order to enhance the salt resistance and water absorption of the gel particles, a zwitterionic monomer methacrylamide propyl-N, N-dimethylpropane sulfonate (with anti-polyelectrolyte effect) with salt resistance performance was synthesized. The method of the composite crosslinking was used to delay the expansion of the gel particles. The salt-resistant and slow-expansion gel particles with low primary expansion ratio and higher secondary expansion performance were prepared and optimized. The results showed that the preparation of the particles was successful and the mechanism of delaying expansion was revealed. The deep migration and deep plugging performance of the gel particles were further studied through a multi-point pressure measurement experiment of sand pipe. This paper solves the problems of poor salt resistance, water absorption ability and fast expansion speed of polymer gel particles. The results shown here provide theoretical guidance and technical support for in-depth water control of low permeability reservoirs.
Sustainability in Drilling Operations Using Zero Liquid Discharge Wastewater
Authors: Ramasamy J. , Al-Arfaj M. K. , Ayirala S. C. , Saleh S. H.
Published: October 2023

Produced water is generated from subsurface reservoirs during oil and gas extraction. Zero liquid discharge (ZLD) produced water desalination technology generates clean low salinity water from hypersaline produced water with 80 to 90% recovery efficiency. The minimal volumes of salt laden reject streams discharged from ZLD desalination plant could be recycled for mineral recovery or drilling applications to achieve 100% circular economy. Such applicability of wastewater streams for potential reuse in drilling applications is evaluated in this study in order to avoid waste disposal into the environment and promote sustainability.

We have tested and demonstrated the applicability of ZLD reject water as a makeup fluid for preparing water-based mud systems. The total dissolved salt of ZLD reject water is around 360000 ppm. The conventional water-based mud additives have limitations in terms of salt tolerance. Therefore, it is essential to study the conventional water-based mud additives to ensure the compatibility in such high saline environment.

Three basic water formulations with viscosifier, fluid loss control and pH controlling additive are prepared using 100 % regular fresh water, 100% ZLD reject water and 50:50 mixture of fresh water and ZLD reject water. Mud formulations were made with bentonite and xanthan gum as viscosifiers. The mud samples have been subjected to routine mud analysis such as hot rolling, rheological and filtration control tests. Initial screening was done for choosing the viscosifier. Formulations made with Bentonite as a viscosifier failed to provide viscosity and solids suspension property for the muds formulated using 100% reject water and 50:50 mixture of fresh water and ZLD reject water. This is due to the high salt intolerance of Bentonite. Formulation of 50:50 mixture of fresh water and reject water using Xanthan Gum as viscosifier resulted in acceptable properties such as rheology and filtration control, whereas poor rheological and filtration control properties are observed for 100% reject water.

Further testing was conducted by adding more additives such as bridging materials, weighting materials and drill solids contaminants to the basic mud formulation having 50:50 mixture of fresh water and reject water. The results for the mud that was hot rolled at 212 °F and 500 psi showed acceptable rheological and filtration control properties. Excellent mud suspension property has been observed with no solids settling or separation even after 24 h. These interesting laboratory results demonstrate that the waste reject water obtained from ZLD produced water desalination plant could be an alternate to fresh water currently used in mud preparation.

The ZLD waste reject water was successfully used to formulate water-based mud to achieve 100% circular economy. This novel development paves the way to effectively recycle wastewater for drilling applications to conserve fresh water and promote environmental sustainability in drilling operations.
Taro Mucilage as Green Inhibitor in Water-Based Drilling Fluid to Modify the Rheological and Filtration Properties and Mitigating Shale Swelling Characteristics
Authors: Khan Muhammad Arqam , Sheikh Muhammad Aashan , Salman Muhammad , Lalji Shaine Mohammadali , Ali Syed Imran , Li Mei-Chun , Lv Kaihn , Sun Jinsheng
Published: October 2023

Clay bearing shale formations tend to swell upon contact with water-based drilling fluid. The migration of hydrogen ions into the nano-spacing of shale platelets is mainly responsible for its disintegration and swelling. To mitigate the clay swelling problem, various shale stabilization materials are added in the water-based muds (WBMs). Before adding these additives, it is crucial to understand their physical and chemical interactions with clay minerals as well as within fluid. In this study, Taro Root Mucilage (TRM) is used as a green chemical in WBM to decrease the shale swelling characteristics. Taro root was boiled in distilled water at 40°C for 24 h and mucilage was prepared, which was characterized by FTIR and XRD pattern. It was then made part of a mud system, which then interacted with the shale sample collected from the western zone of Pakistan. Moreover, this mucilage was compared with sodium alginate mud system, a biopolymer commonly used in industry. The results of the experimental studies showed that TRM appreciably reduces clay swelling characteristics compared with the distilled water and sodium alginate. Moreover, all the rheological parameters fall under the recommended API range for TRM samples. Furthermore, it was found that the TRM produces a thin filter cake and minimizes fluid loss volume. In addition, during the shale cutting recovery test, 50%, 80% and 100% recoveries were obtained from base mud, whereas 10% and 20% were obtained from TRM based WBM respectively. TRM encapsulates the drilled cutting and preserves it from breaking into smaller fragments. In addition, TRM concentration in drilling mud increases the hydrophobicity of the shale sample. The adsorption of TRM over the surface of shale allows less penetration of water in the nano-spacing of shale structure and improves the shale stability. Hence, the finding in this article implies that TRM can be used as a green and sustainable substitute for traditional clay stabilizers in drilling operations to reduce formation damage. It has all the desired properties that help it to become an alternate solution in the form of a clay swelling inhibitor.
On the Road to Net-Zero Carbon Emissions: A Cementing Emissions Assessment Tool for Quantifying, Evaluating, and Helping Decarbonization
Authors: Droger N. , Kapoor S. , Yakovlev A. , Lafitte V. , Mendoza O.
Published: October 2023

An important step in decarbonization is using an end-to-end approach to quantify carbon emissions during cementing operations. By careful analysis of the entire cementing operations process, it is then possible to measure and compare carbon emissions at various stages of the operation. Understanding and isolating the main drivers of the carbon emissions footprint enables making better choices and developing best alternatives with lower environmental impact.

The methodology considers the lifecycle assessment of cement from quarry extraction to well abandonment, and includes steps such as manufacturing of raw materials, transportation and logistics, and operations in the field. For these stages, careful quantification of emissions is performed based on the manufacturer's carbon emissions of cementing products, transportation (distance and means) to the bulk plant and rig site, and equipment-related emissions such as blending and pumping units. In some cases, when assessing the footprint of different technologies, a sensitivity analysis can be carried out to compare the operation-related emissions based on a field case.

Using an assessment tool during key cementing operations allows for identifying the main contributors to greenhouse gas (GHG) emissions. In most cases, the embodied carbon in the cement slurry itself outweighs the operational emissions (on an average, one ton of CO2e is emitted for every ton of Portland cement produced). The embodied carbon of cement systems mainly depends on the data quality of the emission factors of the slurry components. These factors are not yet broadly available and until then, correct proxies are needed to perform such studies.

Besides the embodied carbon, the assessment tool also quantifies other elements of the cementing operations. Examples of sensitivity analysis will be presented in this paper, covering aspects such as an optimal transportation choice from the supplier location to the implementation site. Furthermore, the tool supports the selection of cementing technologies, integrating performance and larger impacts, such as a change in the well design or elimination of remedial operations during the life of a well.

The cementing emissions planner supplies a platform for consistent and transparent quantification and comparison of cementing technologies supporting an effective environment action. This tool embraces forward-thinking and innovative cementing solutions that help decarbonization in the oil and gas industry in achieving net-zero carbon emissions.
The Critical Factors Causing Casing Corrosion in Aqueous Drilling Fluids
Authors: Barmatov E. , Corcoran E. , Isaacs J. , Medvedev A. , Panamarathupalayam B. , Young S.
Published: October 2023

Understanding the corrosivity of aqueous drilling fluids is essential for more efficient and safer drilling operations. The main factors causing the corrosion of typical aqueous drilling fluids were investigated under laboratory conditions using American Iron and Steel Institute (AISI) 1018 mild carbon steel at 70 degC dynamic flow. Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX), X-ray fluorescence (XRF), and X-ray photoelectron spectroscopy (XPS) analyses were used to characterize the metal microstructure of AISI 1018 steel rotating cylinder electrodes (RCE) and study the changes that occurred during corrosion. The effects of fluid composition, barite weighting agent, and clay contaminant were investigated using RCE to simulate the effect of flow velocity on mild carbon steel corrosion and the effect of dissolved oxygen. Starting with a low salinity chloride-brine base fluid (3% NaCl), the effect of adding various components such as amine-based shale inhibitors, polymeric viscosifiers, and suspended solids on the corrosion of RCE was investigated using various electrochemical techniques such as linear polarization resistance, Tafel analysis, and weight loss measurements. Three additional corrosion factors and chemical additives affecting the corrosion of AISI 1018 mild carbon steel were identified: (1) polymeric viscosifiers, (2) the formation of a mud solids skin on the metal surface, and (3) galvanic corrosion. These factors improve the understanding of the corrosion mechanisms occurring in aqueous drilling fluids and provide valuable insights for the development of effective strategies to reduce corrosion in drilling operations.
Modeling Fractures in a Heterogeneous Carbonate Reservoir Onshore UAE: A Case Study
Authors: Lavenu Arthur P. C. , Irving Alan , Niculescu Elena , Singh Nepal , Kusyairi Amirul , Douik Hela
Published: October 2023

A brown field producing from an Upper Cretaceous carbonate reservoir in an elongated anticline is facing water management challenges (increasing water cut, premature water breakthrough), impacting production and recovery. The complexity of heterogeneities encountered in the reservoir (fractures, karst-related features, high permeability dolomitic drains), where depositional settings, diagenesis, and tectonics are intertwined, makes reservoir characterization critical to a successful field development plan. Evidence of dual medium behavior, combined with the presence of fractures from image logs, suggests that fractures may play an important role in reservoir dynamics, and hence need to be modeled appropriately.

In this study, the scope of work was threefold: reviewing the conceptual fracture model in considering the latest data, creating updatable workflows to build discrete fracture networks in commercial geomodeling software, and, ultimately, comparing upscaled properties to well test interpretations representing "fracture" and "matrix" responses. Main fracture sets trend NE-SW, parallel to the anticline axis, and E-W. Two fracture scales have been modeled in the present case study: large features that relate to the deterministic component of the dataset (fracture clusters from image log interpretation and seismic lineaments), and small-scale fractures, stochastically distributed, to reflect the permeability contribution of diffuse fractures connecting deterministic objects.

Calibration to dynamic data is performed by analytical estimation of fracture aperture per fracture orientation set, upscaling to equivalent grid permeability, and iterating until reaching a satisfactory match with the test-derived permeability. The calibration exercise gives a consistent fracture aperture for the two orientation sets tested (NE-SW and E-W).

Fracture modeling was done in parallel to building reservoir matrix properties hence the dynamic calibration considers only fracture permeability. In some cores, measured permeability can reach several Darcies, leading to dual medium behavior without the contribution of fractures. Future work could integrate this analysis with existing sedimentology and reservoir dynamic syntheses to assess the relative impact of high permeability streaks on equivalent permeability and deconvolve it from the role of fractures.
Study On In-Situ Stress Evolution and Infill Well Fractures Propagation in Unconventional Reservoir
Authors: Li Xiang , Zhou Wei , Xie Lei , Xie Dan , Xu Hanbing , Cao Qianqian , Li Junfei , Ding Yajie , Dong Jingya , Liu Yan , Xu Gang , Han Zijian , Hou Cao , Chen Liten , Li MingHong
Published: October 2023

Fluid transport and rock deformation are the core scientific issues in oil and gas development. The development of natural fractures in unconventional reservoirs, the variety of fluid flow mechanisms in the formation, and the non-homogeneity and anisotropy of rock mechanics parameters make the coupling of seepage and geomechanics in unconventional reservoirs exceptionally complex. During the production process, the reservoir around the wellbore generates different degrees of pressure drop, which disturbs the original ground stress in the pressure drop area, and the reservoir stress evolves with the extraction time, i.e., four-dimensional dynamic ground stress. Accurately predicting the reservoir's four-dimensional dynamic ground stress field is a prerequisite for the design of fracturing and repetitive fracturing of infill wells. Therefore, this paper systematically summarizes the numerical simulation methods of oil and gas reservoir seepage - geomechanical coupling and fracture extension of infill wells and discusses the progress of multi-field coupling simulation and the latest research results in depth. Currently, there are various models of oil and gas reservoir seepage - geomechanical coupling, which can be classified as full coupling, sequential coupling, one-way coupling, and proposed coupling according to the form of coupling solution. Due to the complex geological characteristics of the reservoir, the current four-dimensional stress evolution model has been improved based on the traditional model, which is mainly a continuous medium model and a discrete fracture model based on the full coupling method, as well as an iterative coupling model. The ground stress decreases with the decrease of pore pressure during the development process, and the stress direction will be deflected. Fractures can affect the reservoir stress distribution pattern and trend compared to continuous media. This evolution of the ground stress state will cause the fracture extension of the infill wells to deflect and produce the "Frac-hit" phenomenon and cause the "microseismic barrier" effect. The study of reservoir seepage - geomechanical coupling and fracture expansion in unconventional gas reservoir development is a multi-physical field, multi-dimensional, and multi-scale coupling problem. In this paper, it is suggested to study the integrated geological-engineering solution and carry out research on the mechanism of complex fracture expansion during repeated fracturing of horizontal wells and fracturing of infill wells under four-dimensional ground stress evolution conditions to provide theoretical support for the sustainable and efficient development of unconventional oil and gas reservoirs in China.
Re-Inventing Pressure Retained Core Acquisition for Advanced Reservoir Property Determination
Authors: Wunsch D , Rothenwänder T. , Anders Erik , Deutrich T. , Brown D. , Ramoin J. , Verret C. , Mukherjee P.
Published: October 2023

Innovation has always played a key role in past industry transition periods and helped to unlock the true potential of new technologies. For this reason, it is crucial to utilize and adapt these past experiences to effectively approach and tackle the challenges any operator is currently facing. The challenges range from understanding production behavior of reservoirs at any point of their lifecycle as well as CCS scenarios. Whenever injection is considered at any stage throughout secondary-, tertiary recovery stage or the general ‘re-utilization’ of the reservoir for storage respectively a thorough assessment is required. This increases the demand for sufficient data acquisition methods or workflows to overcome numerous shortcomings.

With full bore core data being one of the key elements for ground truthing any data set used for reservoir modelling and project decision making (Saucier et al. 2022), the conventional methods utilized to acquire these core samples have a variety of weaknesses. While these standard methods are well established, more advanced coring methods are required to provide more comprehensive datasets for reservoir description. The method discussed in this paper aims to address these demands by delivering a high-quality in-situ core sample which is then processed on-site and introduced to best-fit lab workflow.

Different special methods in the field of core acquisition are compared and strengths and weaknesses provide the context for potential need for a large diameter pressure coring technology. How this technology directly helps operators to better understand their reservoirs in any of the above-mentioned reservoir scenarios will be explained by describing different exemplary fields of application. These descriptions range from more accurate saturation determination of ROZs in depleted formations to acquiring in-situ PVT data for recombination of fluid volumes in conventional reservoirs to actual OGIP and GOR measurements in unconventional reservoirs. With the ongoing shift in the oil-&gas industry, pressure coring technology also has a high potential to become an important tool in storage efficiency assessments in CO2 injection wells for CCS applications.

The study outlines how pressure retained core samples can contribute to reduce uncertainties and improved datasets which are needed in cases where the design of reservoir models require comprehensive knowledge of the entire spectrum of reservoir data. The proposed best practices are backed up by findings from recent achievements as well description of field activities in different applications. The study aims for giving an overview on how pressure coring technology enhances the available toolbox for downhole data acquisition and how the technology brings added value to the industry in an environment when more stringent economics rely on more accurate data validation of any asset.
Different Origin of Microseismic Activity Highlighted by Magnitude of Completeness and B-value Computation Case Study on Underground Salt Exloitation and Storage
Authors: Fortier Eric
Published: October 2023

Seismic monitoring becomes an important and reliable method to identify instabilities induced by underground operations. Depending on the type of operations, as underground storage in salt caverns, hydraulic stimulation, or reservoir monitoring, different types of seismic activities are identified. After the location of micro-seismic events, different parameters are computed, like the peak ground velocities, the magnitudes, the source radius, or the B-value.

When a network does not have enough sensors to calculate reliable focal mechanisms, the use of such parameters can help us to better understand the seismic origins, their occurrence, and what induced the micro-earthquakes.

The Richter magnitude is an important attribute to characterize the seismic energy induced by cavern activities. The magnitude is computed from the seismic moment (Aki, 1966; Kanamori, 1977). The magnitude of completeness (Mc) is the minimum magnitude above which all earthquakes within a certain perimeter are reliably detected. The B-value computation corresponds to the slope of the number of located events versus their magnitude on a log scale. It gives an indication of the relation between the "earthquake" size and its occurrence. It is generally accepted that b-value around 1 is observed for "structural origin" and around 2 is observed for "small induced micro-seismicity".

Some sites are leaching or storing gas in underground caverns inside salt formation. Those sites are equipped of seismic networks using sensors in shallow buried arrays to monitor the associated microseismic activity. A significant seismicity is occurring since many years of monitoring. According to the B-Value computation, we manage to identify three types of seismicity. First one is cavern leaching seismicity associated to a B-value close to 2, indicating small energy activity located in the vicinity of the caverns. The second and third ones are gas storage caverns, and salt coverage seismic origin, with a B-value close to one, showing a more important seismicity in term of energy, induced by micro-structure re-activation or insoluble layers sliding.

This seismicity interpretation allows a new viewing of understanding the micro-earthquakes origin induced by underground challenges. Taking into account the geological context, we can better define the nature of the seismicity by computing such parameters. The only factor needed to compute a reliable magnitude of completeness and B-value, is the necessity of a significant database of seismic events.
Cloud Based Open API Applications Delivers Differential Value in Well Planning Efficiency Saving 60% of Well Planning Time
Authors: Mwansa Peter Levison
Published: October 2023

As part of ADNOC Onshore's aim to standardize and improve well planning efficiency and standardize, a Digital Well Technology Piloting Agreement (TPA) was signed to test cloud based open application programming interface (API) aware well planning software.

ADNOC Onshore engineers currently perform well planning and design in multiple legacy applications, requiring them to move the inputs and outputs from one place to another manually. For example, the well targets are identified by a different team in a service provider platform tool. The trajectory is then planned using a different vendor software. The rest of the well planning is completed with another legacy software, in individual modules for each aspect of design that don't integrate. Much of this is outsourced to "well services suppliers" to either do the full design or validate the internal design. The final execution document (Drilling Program) is completed in word and is typically 50-80 pages long. This is inefficient, and also allows for potential mistakes. If anything changes, all of this has to be re-worked. For example, if the pore pressure and fracture gradient (PPFG) analysis changes, there is no way to alert or notify the engineer that they need to update other parts of the well design (e.g. cementing, etc.). This creates communication challenges internally and with our third-party providers. It also leads to sub-optimal well design choices due to an inability to see the full picture.
Use of Critical Point in Equation of State Modeling for Reservoir Fluids
Authors: Pedersen K. S. , Christensen P. L. , Shaikh J. A.
Published: October 2023

Several equations of state have been proposed as a supplement or a replacement for cubic equations, but cubic equations have remained an industry standard in the petroleum industry. Cubic equations are bound to correctly predict the critical point of each component in an oil or gas mixture. With a minor correction, the location of the critical point also determines the simulated gas and liquid properties of a pure component at other pressures and temperatures. Also, for multicomponent reservoir fluids, the location of the critical point exerts a large influence on the phase behavior of the fluid in the entire gas and liquid region. The paper presents procedures that, for both reservoir oils and gas condensates, allow a reliable equation of state model to be generated with a fluid composition and an experimental saturation point as the only experimental data. This is possible by using an estimated critical point as an artificial data point. For oils, the estimated critical point is for the entire reservoir fluid, while for gas condensates it is the critical point of the C7+ fraction, since not all gas condensates have a critical point. The method can also be used to quality check existing EoS models or as an additional constraint when developing an EoS model by regression to experimental PVT data. This is particularly useful for heavily lumped EoS models.
Well On/Off Time Classification Using Recurrent Neural Networks and a Developed Transient Well Simulator
Authors: AlHammad Y. K. , Hoteit H.
Published: October 2023

Supervised machine learning (ML) projects require data for model training, validation, and testing. However, the confidential nature of field and well production data often hinders the progress of ML projects. To address this issue, we developed a well simulator that generates realistic well production data based on physical, governing differential equations. The simulation models the reservoir, wellbore, flowline, and choke coupled using transient nodal analysis to solve for transient flow rate, pressure, and temperature as a function of variable choke opening over time in addition to a wide range of static parameters for each component. The simulator's output is then perturbed using the gauge transfer function to introduce systemic and random errors, creating a dataset for ML projects without the need for confidential production data.

We then generated a simulated dataset to train a recurrent neural network (RNN) on the task of classifying well on/off times. This task typically requires a significant number of manhours to manually filter and verify data for hundreds or thousands of wells. Our RNN model achieves high accuracy in classifying the correct on/off labels, representing a promising step towards a fully-automated rate allocation process.

Our simulator for well production data can be used for other ML projects, circumventing the need for confidential data, and enabling the study and development of different ML models to streamline and automate various oil and gas work processes. Overall, the success of our RNN model demonstrates the potential of ML to improve the operational efficiency of various oil and gas work processes.
Leveraging the Power of Spatial-Temporal Information with Graph Neural Networks as the Key to Unlocking More Accurate Flow Rate Predictions
Authors: Voskresenskii A. , Pakhomov M. , Katterbauer K.
Published: October 2023

The digital transformation of the oil and gas industry has prompted the need for improved forecasting methods to enhance efficiency, safety, and decision-making processes. This paper proposes a novel approach to oil flow rate forecasting by leveraging the power of Graph Neural Networks (GNNs) to capture complex spatial and temporal dependencies within oil and gas production systems. The study presents a graph representation of oil wells, employing GNNs to learn latent representations of the wells and their connections, while incorporating temporal convolution to capture time-dependent relationships. Experimental results show that the proposed GNN-based approach achieves higher accuracy in terms of mean absolute error and coefficient of determination compared to traditional time-series forecasting methods such as CRMs, Arps method, decision tree based models and other types of linear and autoregressive models. The findings highlight the potential of GNNs for accurately forecasting oil production, which can significantly impact production planning, resource allocation, and revenue estimation in the oil and gas industry.
Causes of Rapid and Extensive Fracture Propagation After Fracture Coalescence
Authors: Jin Yuteng , Misra Siddharth , Rougier Esteban
Published: October 2023

The paper identifies specific spatial arrangement of the existing crack pathways and the crack network at the time of crack coalescence that lead to a rapid and extensive crack growth immediately after crack coalescence. To that end, we engineer relevant and informative features from simulated crack network generated using the HOSS simulator and then train machine learning model to relate the most significant crack-network features with the onset of rapid and extensive crack propagation immediately after crack coalescence. These features are indicators of the underlying mechanism of crack propagation and coalescence. The features serve as the inputs of a SVM classifier with RBF kernel to find the decision boundary between the two types of samples, those that undergo rapid and extensive crack propagation after coalescence and those that don't. Through permutation feature importance evaluation, we determine the 7 most important crack-network features associated with sudden, large crack growth. Notably, these features are associated with the status of energy buildup, energy distribution, and energy release inside the material. The primary aim of this study is to explain the sudden and extensive fracture-propagation post coalescence in terms of the KDE-based and subgraph-based features. The underlying assumption is that the stress and energy state inside the material cannot be directly observed; hence, the phenomenon of coalescence and large fracture propagation post-coalescence need to be answered in terms of the mechanisms observed based on the spatiotemporal evolution of the crack network under the uniaxial compression.
Decarbonization of Offshore Oil and Gas Installations with Offshore Wind and Energy Storage Solutions
Authors: Laskar Karishma , Kumar Avinash
Published: October 2023

In light of India's commitments to COP26, there is a sense of urgency to accelerate the energy transition and to decarbonize the energy portfolio of oil & gas companies. This paper discusses the following decarbonization strategies; (a) Installing offshore wind farms and battery solutions for providing power to process platforms and commercialization of the remaining power, (b) Integrating solar with Li-ion energy storage solutions in unmanned platforms. This work outlines how a reliable energy storage solution can be the key to stepping towards this transition. The offshore unmanned platforms have conventional battery solutions such as: Lead-acid batteries - Installed to meet no sun days & also provide power during the night.Ni-Cd batteries - Integrated with primary power sources such as gas turbines provide power in manned platforms.

Conventional batteries have limitations in terms of energy density, frequent replacement period, footprint, and their heavy weight. With the introduction of renewable energy sources such as offshore wind & solar, a very reliable solution is the need of the hour to supply uninterrupted power during energy fluctuations due to wind speed or intermittency of solar and to limit the usage of carbon-emitting sources such as Diesel generators. This makes Li-ion batteries one of the favourable candidates for powering offshore installations where space is a constraint and due to its added advantages of high energy density and low maintenance requirements. It also discusses how offshore wind can be a potential candidate for a cluster of wells and process platforms where the power requirement is in Megawatts and extra power generated can be fed back to the onshore grid nearby through PPA agreements. A pilot project has been considered for the purpose of the study and different cost components to assist in techno commercial analysis of such offshore wind projects of 50 MW.
Integrated Carbonate Lithofacies Modeling Based on the Deep Learning and Seismic Inversion and its Application
Authors: Xin Chen , Deshuang Chang , Qing Liu , Qian Sun , Weixiang Zhong , Wenwen Yu , Xiaoliang Li , Hanzhou Fan , Qingning Yang , Dengyi Xiao , Fuli An , bo Wang , Lu Lv , Yu Peng , Qiang Liu , Kongzhi Huang
Published: October 2023

To improve the accuracy of carbonate lithofacies modeling, mainly well data such as core, thin section and well logging data had been adopted in conventional methods. Although the reservoir types classification is very detailed, but it is usually difficult to integrate with seismic data to make 3D lithofacies model. To address the issue of carbonate lithofacies modeling, a new integrated carbonate lithofacies modeling technique was summarized based on thin section, core, well logging, 3D seismic data and production performance data.

The integrated carbonate lithofacies modeling workflow mainly contains 5 steps. 1) Integrated lithofacies classification based on the core, thin section, well logging, FMI, CMR and production performance data. 2) Petrophysics lithofacies classification based on the cross-plot analysis between sensitive well log curves. 3) Petrophysics lithofacies prediction based on the sensitive well log curve by deep learning method, and verification by core lithofacies analysis. 4) Seismic inversion volume optimization by well lithofacies calibration. 5) Lithofacies modelling based seismic inversion based on the seismic inversion cut-off analysis (Fig.2). This workflow integrated seismic impedance (continuous variable) with lithofacies (discrete variable), and converts seismic inversion into lithofacies directly.

According to the certification of new wells, this technique had been applied successfully in carbonate reservoir of M oil field in Middle East, it not only improves the accuracy of 1D lithofacies prediction for wells by deep learning method, but also improves the accuracy of 3D lithofacies modeling for the whole oilfield by well and seismic inversion integrated. The lithofacies modeling not only matched with lithofacies from core analysis and petrophysics lithofacies prediction from well log analysis, but also matched with seismic inversion data in no well area.

The integrated carbonate lithofacies modeling workflow integrated thin section, core, well logging, 3D seismic data and production performance data, and improved the improves the accuracy of 3D lithofacies modeling for no well area. It’s useful for new wells optimization and high efficiency development with lower cost. The integrated carbonate lithofacies modeling workflow not only suit for carbonate reservoir, but also suit for clastic reservoir.