bluuebunny/crossref_metadata_2025_split huggingface dataset:
Revisiting Time-Rate-Pressure Production Analysis — Where Are We Almost 40 Years Later?
Authors: Blasingame T. A. 
Published: October 2023

Abstract
In the mid-1980s "time-rate-pressure" production analysis was proposed by this author to estimate reservoir properties, as well as in-situ volumes and EUR. This approach was primarily applied to conventional and tight reservoirs using "material balance decline curves" in the early 1990s and became known as "Well Performance Analysis" (WPA) before being rebranded by a vendor as "Rate Transient Analysis" (RTA) in the early 2000's. This analysis has been extended beyond fixed models (e.g., type curves for an unfractured or fractured well in a simple closed reservoir (e.g., a circle)) into analytical models for almost any case, as well as using numerical models for virtually any well reservoir configuration and complex multiphase fluid flow.
The "RTA" methodology has become a mainstay of modern reservoir engineering, but deserves a "look-back" and a "look-forward" in terms of where we can best utilize new modelling approaches (physical and data-defined models) to improve diagnostics and analyses. The primary goal of this work is to emphasize to both the casual and the experienced user that by whatever name we call it — Well Performance Analysis (WPA), Production Analysis (PA), or Rate Transient Analysis (RTA) — the purpose of these methodologies is to provide a diagnostically-driven analysis and interpretation of time-rate-pressure (TPR) data. WPA/PA/RTA are not just data fitting exercises, nor are they limited to simplified analyses (e.g., some sort of straight-line plots), these are fully integrated data diagnostic and analysis tools that warrant care and attention.
The present push to provide automated/augmented analyses is actually a noble (and predictable) outcome of the methodologies developed in the 1980s to provide estimates of reservoir properties from data that were not being used for that purpose, but as we develop more comprehensive (and more complex) analyses for TPR data, we must acknowledge that these data are inherently affected by operational aspects as well as measurement capabilities. In short, these are just data, and we need to stay focused on the diagnostic value of the data before attempting any analyses and interpretations — no matter how simple or complex those analyses and interpretations may be.
Interfacial Dilational Rheology Between Nitrogen and Aqueous Surfactant Solutions: Implications for Foam-Assisted EOR
Authors: Pan Ziqing , Trusler J. P. Martin , Zhang Kaiqiang 
Published: October 2023

Abstract
Foam-assisted EOR is a promising technique to meet the ever-growing global energy demand. However, foam is thermodynamically unstable because of large gas-liquid interface. The stability of foam depends largely upon interfacial rheological properties, which represent the resistance capability to disturbance. Most previous studies address limited pressure ranges, not revealing the behavior under subsurface conditions. To fill this gap, we measured the interfacial dilational viscoelasticity of (N2 + SDS (aq)) at various pressures in a high-temperature high-pressure view cell by using the oscillating-drop-profile method. The interfacial elastic and viscous moduli were studied at pressures from ambient pressure up to 26.7 MPa, temperatures of 298 K and 348 K, SDS concentrations below the CMC (0.05 mass% and 0.15 mass%) and above the CMC (0.50 mass%) and oscillating frequencies of 0.125 Hz and 0.0625 Hz, which may correspond to the low-frequency fluctuation expected during the reservoir fluids flow in porous media. The effects of pressure, temperature, SDS concentration and oscillating frequency were examined. Both elastic and viscous moduli decreased with increasing pressure, indicating weaker resistance capability to external disturbance under high-pressure conditions. At concentrations below the CMC, elastic modulus decreased, and viscous modulus increased with increasing temperature, while at concentrations above the CMC, both moduli decreased with increasing temperature. Surfactant solutions with higher concentrations had larger dilational viscoelasticity. However, once the CMC was reached and surfactant micelles were formed in the solution, a significant drop in the interfacial dilational modulus was observed. At concentrations below the CMC, both moduli increased with increasing oscillating frequency, while at concentrations above the CMC, the effect of frequency was insignificant. The expansion and compression of pendant drop during interfacial dilational modulus measurement is closely analogous to foam flow through the heterogeneous porous media. The foam interfacial dilational properties under a variety of pressure, temperature, composition, and oscillating conditions were systematically studied for the first time. The results obtained can help to advance understanding of foams stability, enhance the design of surfactant solutions and provide guide for the implementation of foam-assisted EOR.
CO2 Foam Flow Dynamics at Reservoir Conditions
Authors: Alcorn Z. P. , Halsøy H. , Sæle A. , Brattekås B. , Ellingsen A. , Graue A. 
Published: October 2023

Abstract
Foam is a promising technique to reduce CO2 mobility and mitigate the impacts of reservoir heterogeneity in CO2 enhanced oil recovery (EOR) and CO2 storage processes. However, the success of foam applications depends on maintaining adequate strength at reservoir conditions. Foam can breakdown in the reservoir due to surfactant adsorption, the presence of oil, and at elevated temperatures and salinities. Therefore, foam formulations must be screened to perform optimally at reservoir-specific conditions. This work presents steady- and unsteady-state supercritical CO2 foam corefloods evaluating the effects of foam quality, injection velocity, surfactant type and concentration on foam generation and strength at reservoir conditions. We also aim to reveal real-time foam displacement mechanisms with combined positron emission tomography (PET) and computed X-ray tomography (CT), high-resolution in-situ imaging technologies.
Foam quality scans with a commercially available water-soluble nonionic 0.1wt.% foaming solution indicated optimal foam qualities of 80% at 180 bar (2610 psia) and temperatures of 40°C (104°F) and 60°C (140°F). Foam rate scans showed shear-thinning foam rheology at both temperatures with a more rapid reduction in apparent viscosity with increasing injection velocity at 60°C. Unsteady-state single-cycle surfactant-alternating-gas (SAG) corefloods using different surfactant types (anionic and nonionic) at variable concentrations (0.35 wt.% and 0.50 wt.%) revealed that the foam strength was not dependent on surfactant concentration for the nonionic surfactant. However, the strength of foams stabilized by the anionic surfactant were sensitive to surfactant concentration, where the higher concentration generated a stronger foam. PET/CT images acquired during single-cycle SAG and WAG corefloods revealed real-time displacement mechanisms and saturation development during dense phase CO2 foam flow at reservoir pressure. The dynamic PET/CT images confirmed foam generation and showed that the foam displacement front was more stable and piston-like, resulting in additional fluid production, compared to experiments without foam.
Contractual Solutions to Barriers of Technology Transfer in the Upstream Contracts
Authors: Fathalizadeh Ali. , Belhaj Hadi 
Published: October 2023

Abstract
For Oil and gas producing countries it is important to transfer the advanced technologies used in upstream segments from E&Ps to NOCs and local companies. However, in upstream contracts, a large number of technology transfer agreements have failed to reach their initial intended goals. Therefore, the primary objective of this study is to examine barriers to technology transfer in upstream contracts and provide better contractual solutions. Library documents, previous studies, and semi-structured interviews have been used as research tools for this investigation. The statistical population of the research includes oil companies’ experts, high rank managers, engineers and project managers. Data analyses conducted using three stages of open-centered and selective coding, as well as the review of previous studies. The result shows that the four categories "lack of international communication", "lack of proper financing of projects", "lack of technology management knowledge", "inappropriate methods of technology transfer" are causal conditions stand as barriers to technology transfers. The results also showed that in order to tackle current obstacles of technology transfer in the upstream domain, infrastructures such as the research and technology centers, the role of technology transfer in the upstream contracts, relationship between educational and research centers with oil companies and contractors, and the bonuses in contracts regarding technology transfer should be strengthened and highlighted. In short, the contribution of this effort is twofold; first is to explore and find the impediments in technology transfer in the upstream contracts, and the second is to provide proper solutions for the upstream contracts to avoid or reduce the effects of these challenges.
Application of Artificial Intelligence (AI) Based Algorithm to Predict Contamination During Formation Fluid Sampling
Authors: Hunnur A. T. , Smith S. S. , Hall E. 
Published: October 2023

Abstract
Reservoir fluid sampling using the wireline or LWD tools has long had a difficult time predicting the filtrate contamination flowing through the tool. When the conventional curve fitting method was developed, changes in measured dynamic fluid data were thought to be best explained by fitting the entire data to a power law equation. Results from simulation study shows that the complete change cannot be explained by a single exponential fit, especially the later time data which is most important for predicting contamination. Thus, the conventional method requires a selection of data just during the later time to give better results. The results are thus extremely dependent on the user and the data used to create the fit.
A novel method was developed which uses an artificial intelligence (AI) based algorithm which was created using an extensive database of over 15,500 numerical simulations based on the fluid flow dynamic and accounting for most of the varying reservoir conditions for contamination prediction. Eight different models were developed and tested to provide not just accuracy of the results but also keeping in mind that this is a real-time decision-making tool, the time and computing power needed as well were considered.
Multiple sets of fluid sampling data from wireline and LWD tools were run through the contamination prediction algorithm in this study. Each dataset had multiple sensor responses and for each set of results at least 3 sensor responses were selected to be run through the conventional as well as the new algorithm. These results were then compared to lab determined contamination values to determine the error from each method.
Based on results from the multiple sets, this technique provides good predictions on the level of contamination not only in the conventional probes for which it was designed but also for focused sampling and sampling in LWD environments. This contamination prediction algorithm removes this user ambiguity and gives consistent and reproducible results.
Modeling of Gas-Liquid Anomalous Diffusion in Undersaturated and Saturated Unconventional Reservoirs and its Effect on Pressure and Rate Transient Responses
Authors: Yildirim G. , Ozkan E. , Artus V. 
Published: October 2023

Abstract
This study presents a one-dimensional numerical model for anomalous diffusion of three-phase, oil-water-gas, flow in a fractured, nanoporous medium. The focus is to address the current knowledge gap regarding gas-liquid anomalous diffusion in saturated and undersaturated unconventional reservoirs. To account for multiphase flow, we extend a modified flux law for anomalous diffusion using the relative permeability and capillary pressure formalisms. Caputo's representation is used to express time- and space-fractional derivatives with Murio's fractional finite difference approximation. A fully implicit computational scheme that incorporates Newton's iteration is employed for the treatment of non-linear terms. The proposed computational scheme should enable extension of anomalous diffusion concept to more realistic multiphase fluid compositions encountered in unconventional reservoirs. For illustration, we consider flow toward a constant-pressure vertical fracture along a horizontal well with one-fourth of the surrounding stimulated reservoir volume. The study showcases the production, pressure, and saturation behaviors resulting from super-diffusion phenomena caused by the presence of natural or induced fractures within the stimulated reservoir volume. It is shown that the effects of anomalous diffusion become more prominent in the presence of the gas phase. Super-diffusion accelerates production and enhances the efficiency of reservoir depletion. The results emphasize the importance of considering anomalous diffusion in modeling the flow and predicting the performance of a gas-liquid system in an unconventional reservoir.
First Challenging Geothermal Well for Carbon Neutral Campus
Authors: Gustafson O. , Bezner W. , Ibrahim A. Salaheldin , Jafri A. , Barton L. , Reyes A. , Poroli M. , De La Parra A. Cortes 
Published: October 2023

Abstract
Cornell University is exploring the direct use of geothermal energy as a sustainable energy source to heat its Ithaca campus. The Earth Source Heat (ESH) project is an essential component of Cornell University's solutions to achieve carbon neutrality by 2035.
The project's first phase included drilling a 3-kilometer-deep exploration well to collect subsurface data from the deep sedimentary and crystalline basement rock formations. These data will inform the design and specifications for creating an "enhanced geothermal system" comprised of a network of open fractures that will serve as a heat reservoir for a demonstration well pair, injecting cool water and producing hot water to heat Cornell University's campus in the cold New York winter.
The engineering design of the project's first phase involved many challenges, from selecting optimum casing seats with minimum offset well information to overcoming potential subsurface risks related to drilling through a thick salt formation and highly unstable shales. Which were taken into consideration during the design phase.
The Engineering team, along with Cornell University's scientists, collaborated in the design phase and utilized innovative engineering solutions on a cloud-based platform for optimizing the well design. This design was coupled with a dedicated mechanical earth model study for the well to reduce the mud window uncertainty.
Each component of the well design was analyzed to ensure optimum design practices and safe operational limits based on an extensive risk assessment of all potential hazards along with prevention and mitigation plans.
For the execution phase, the engineering team utilized a state-of-the-art digital solution for drilling automation and optimization, where drilling dysfunctions such as shock and vibrations and variable formation hardness were displayed in a real-time advisory mode for drilling performance optimization.
The well construction phase was a continuous, agile process between the well engineering team and the University's scientists to achieve the project's challenging goals.
PDC Bit Selection Guidelines Based on Physics and Lessons Learned
Authors: Pastusek Paul E. , Barajas Pablo E. , Payette Greg , Sowers Steve 
Published: October 2023

Abstract
The objective of bit selection is to drill a round, ledge free hole, without patterns, with minimum vibration, minimum dog leg severity, that reaches all directional and geologic targets. And to do this in one run per section where rate of penetration (ROP) is unconstrained by the bit, and it remains vibration free in control drilling situations. The objective of this paper is to share these guidelines, accumulated from forensics investigations and sometimes costly lessons learned over the past decade.
Bit selection can be based on; offset runs, forensics analysis, and first principles. Offsets capture past learnings. Forensics analysis is applied to past and current wells, and it is the foundation for continuous improvement. First principles, based on independent thinking, are required to challenge the status quo.
These guidelines are the distillation of forensics observations, offset analysis, and physics modeling. It is important to note that these are guidelines, not rigid standards. They are presented in their current state, to be challenged, tested, and revised as new ideas and technology are developed. They are not a substitute for thinking.
The guidelines start with a description of the formation properties, drilling environment, and other requirements such as directional objectives, drill out considerations, and required life. They cover how to suppress bit whirl, stick slip, and borehole patterns; improve structural integrity, allow for predictable build rates, reduce gauge trimmer damage, and design for appropriate aggressiveness, ribbon flow, bit stability and life. These functions and dysfunctions are paired with design features such as depth of cut elements; gauge pad length and relief; cutter materials, size, and geometry; back rake; blade count and standoff; hydraulic design; and blade strength. The guidelines document specific and general lessons learned and why each rule was established. They help drilling engineers and service companies determine which design features are most important for a given application. Applying them across teams and applications highlights design elements that may be of concern and has helped avoid repeat failures. The first failure is for learning, the second failure is a failure to learn.
Design features have been matched up with associated critical performance limiters. This transparency in thinking allows the assumptions to be questioned, provides knowledge of which rules apply in each application, and provides background to evaluate when new technology may help. Some of the hard problems that remain are; consistent forensics analysis, chip flow modeling, cutter stress verses rock strength and penetration per revolution, understanding and suppressing high frequency torsional oscillation, and improvement and expansion of in-bit instrumentation.
A Two-Phase Type-Curve Method with Fracture Damage Effects for Hydraulically Fractured Reservoirs
Authors: Zhang Fengyuan , Pan Yang , Rui Zhenhua , Emami-Meybodi Hamid , Yang Chia-Hsin , Wang Ruiqi , Zhang Wei 
Published: October 2023

Abstract
Type-curve analysis on flowback and production data is a powerful tool in characterizing hydraulic fractures (HF) and reservoir properties. In order to evaluate HF characteristics and their dynamics for multi-fractured horizontal wells (MFHWs) in hydrocarbon reservoirs, we provide a novel type-curve method and an iterative workflow. The type curve incorporates the fracture damage effect, which is characterized by choked-fracture skin factor, into the two-phase flow in HF and matrix domains. The type-curve method can be applied to inversely estimate choked-fracture skin factor, fracture pore-volume, fracture premeability, and fracture permeability modulus through the analysis of two-phase production data. By introducing the new dimensionless parameters, the non-uniqueness problem of the proposed semianalytical method is significantly reduced by incorporating the complexity of fracture dynamics into one set of curves. The proposed type curve's accuracy is examined by numerical simulations of a shale gas and shale oil reservoir. The validation results demonstrate the good match of analytical type curves and numerical data plots and confirms the accuracy of the proposed approach in estimating the static and dynamic fracture properties. The flexibility and robustness of the proposed method are illustrated using the field example from a shale oil MFHW. The interpreted results from the flowback analysis of the field example offers a quantitative insight of fracture properties and dynamics.
First Complete Digital Drilling Package Deployment For Risks Reduction And Performance Optimization: Africa Case History
Authors: Ferrara Paolo , Dal Forno Luca , Magni Gianluca , Santoro Domenico , Sanasi Carla , Mutidieri Luigi 
Published: October 2023

Abstract
In an era of reduced profit margin and high market uncertainty, more than ever it is important to meet operational excellence as a key factor for business sustainability. This is common to most technical applications, but it is particularly true for the drilling operations, where considerable investments and associated risks are involved. During last years, as part of its digital transformation process, the operator has equipped itself with several digital tools for the diagnosis and the monitoring of drilling and completion operations. Goals and reached benefits can be summarized in risk reduction, operational efficiency and performance optimization.
Based on an already wide case history started in 2019, a Digital Drilling Package was developed for operations support, from the design to the construction phase. Three main tools are now available to be applied to the most complex wells, either stand-alone or in parallel, covering Non-Productive Time (NPT) prediction, performance advanced analytics and drilling operations real time simulations. This last simulation tool has been deployed for the first time in 2021 on some wells in Africa and is now being included in the engineering and operation workflows.
Attacking operational NPT and invisible lost time with the aim to increase safety and to reach the technical limit is not only a matter of processing tools. It requires a deep integration among headquarters, geographical units and field locations, with the definition of a strong data management infrastructure. This paper describes operator’s experience both on-site and in office, showing how the portability and integration of big data systems, suitable data lake architectures and human factor synergies can create effectiveness at all levels. An Africa field case history will be reported to show how predictive and data analytics modelling and tools interact. In addition, the way in which these tools have been managed to support optimum decision-making processes will be also highlighted.
Next development steps will target an even higher level of integration of all available digital tools in order to have a single diagnostic approach based on univocal dashboards and in-house data server infrastructures.