bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient Modeling of Unconventional Well Performance with Millions of Natural and Hydraulic Fractures Using Embedded Discrete Fracture Model EDFM
Authors: Yu Wei , Gupta Anuj , Vaidya Ravimadhav N. , Sepehrnoori Kamy 
Published: December 2021

Abstract
The complexity of dynamic modeling for naturally fractured reservoirs has increased in recent years to incorporate more data and physics, as well as to handle advanced completion designs and development scenarios. While these complex models can provide more insight to difficult problems, they come with higher computational costs. Such a limitation prohibits an asset team from working with a large number of well/fracture scenarios that correctly represent geological uncertainty. This study presents a powerful non-intrusive Embedded Discrete Fracture Model (EDFM) method to efficiently handle millions of natural and hydraulic fractures with hundreds of horizontal wells, which has never been modeled in the literature. Specifically, we built a 3D geological model using a black oil reservoir simulator with 100 square miles in the horizontal area and 11 layers of 165 ft thickness. The total number of matrix cells without considering fractures is over 3 million. In total, 400 horizontal wells with well length of 6000 ft were modeled in two target layers. Each layer contains 200 wells. Each well has 112 hydraulic fractures with cluster spacing of 50 ft. The total number of hydraulic fractures is 44,800. In addition, we generated three cases with 10K, 100K and 1 million 3D natural fractures with dip angle from 70 to 90 degrees. For the case with 1 million natural fractures, the total number of cells is over 42 million. Well performance for the field example, with and without natural fractures, was investigated. This work adds significant value to the well and fracture spacing optimization process during field development planning. The non-intrusive EDFM method has been proven to be an efficient fracture modeling tool for simulating million-level complex hydraulic/natural fractures, which significantly improves accuracy and reduces computational time.
A Novel Machine-Assisted Technique for Extracting Multiscale Vugs and Fractures in Heterogeneous Carbonates Sequence
Authors: Parashar Sarvagya , Wu Ivan Zhia Ming 
Published: December 2021

Abstract
Predicting petrophysical properties in carbonate reservoirs is challenging due to the deposition and diagenetic history, which creates pore-scale features and heterogeneity at multiple-length scale. Non-fractured carbonate rocks with monomodal pore distribution often provide weak transportation properties compared to carbonates with multimodal pore system. The behaviour of such formations is subject to percolation effect where the connectivity of vug clusters control the poro-perm relationship which can be explained with high-resolution microresistivity images and nuclear magnetic resonance (NMR) data. A machine-assisted processing technique, defined as "thresholding," was applied to high-resolution microresistivity images, resolving vugs and fractures with similar resistivity. Other objects of interest are removed using object-oriented filters and thresholding, resulting in a "sculptured image" containing only vugs and fractures. The image is analysed to quantify formation porosity. A Laplacian of Gaussian filter is used to avoid highlighting features of no interest. Step two analyses T1 and T2 relaxations allowing portions of signal from a pore-size group to spill across the discrete boundaries. The pore-size takes on a fuzziness near the discrete relaxation time cut-offs corresponding to pore radii breakover points. High poro-perm layers of grainstone in overall thinly bedded sequences of packstone and wackestone were successfully identified and subsequently shed light upon the ambiguities observed in mobility values obtained from formation tester across the same lithocolumn. This novel technology helps in deciphering high-resolution integrated lithofacies. The histogram from the image porosity binning demonstrates a different response within vugular zones compared to fractured zones. Where the vugs sizes are variable, they exhibit a multi-pore system nature in NMR. For the fractured interval, the images and NMR exhibit weak distribution. The resistivity independent image pixel-based filtration technique helps to define interesting features on images which can be enhanced and measurable at various scales. Machine assisted technique in NMR complement the results in aiding to characterize the heterogeneous carbonate rocks.
Value Oriented Engineering Solutions for Business Continuity
Authors: Delgado Rivera Jose Luis 
Published: December 2021

Abstract
This paper presents a systemic approach using Engineering and analytics methods to avail the fastest and safest responses to recovering business operations after Abqaiq Plants major disruption after the 2019 September 14th incident. This new approach using value and agile engineering, risk management methodologies combined with the business continuity model suggested was successfully applied to recover Abqaiq Plants Operations after catastrophic events occurred.
This paper pretends to serve as example about how the business continuity plan should response to a major emergency and how this planning activity could be effectively supported using a Value Oriented Engineering Solutions (VOES). This VOES approach is based on Business continuity framework and adapted for use during emergency situations to generate effective and urgent responses to recover one of the most strategical operations in the Oil and Gas Industry worldwide ahead of the last year significant disruption.
VOES approach vastly implemented during Abqaiq Plants Restoration allowed a 100% functional recovery on 9 days, 5 days in advance to the most optimistic scenario. This paper shows a case study implemented for major instrumentation and electrical equipment activities performed in UA Spheroids plant, one of the most affected area and responsible to process the 100% of the Abqaiq Plants Oil Production rate.
This paper pretends to contribute with the research and practice on business continuity management. Considering a particular approach to BCM, incorporating value-oriented engineering solutions in the developing of continuity plans; we apply model-based techniques to provide quality assurance in the elaboration process, and to automate the generation/update of a BCP. On the practical side, this study converts Operational, Maintenance, Safety and Reliability perspectives in a holistic view provided from Engineering solutions responsible to generate the guidelines for an agile, effective and realizable recovery plan.
Application of a Drilling Simulator for Real-Time Drilling Hydraulics Training and Research
Authors: Skenderija Jelena , Koulidis Alexis , Kelessidis Vassilios , Ahmed Shehab 
Published: December 2021

Abstract
Challenging wells require an accurate hydraulic model to achieve maximum performance for drilling applications. This work was conducted with a simulator capable of recreating the actual drilling process, including on-the-fly adjustments of the drilling parameters. The paper focuses on the predictions of the drilling simulator's pressure losses inside the drill string and across the open-hole and casing annuli applying the most common rheological models. Comparison is then made with pressure losses from field data.
Drilling data of vertical and deviated wells were acquired to recreate the actual drilling environment and wellbore design. Several sections with a variety of wellbore sizes were simulated in order to observe the response of the various rheological models. The simulator allows the input of wellbore and bottom-hole assembly (BHA) sizes, formation properties, drilling parameters, and drilling fluid properties. To assess the hydraulic model's performance during drilling, the user is required to input the drilling parameters based on field data and match the penetration rate. The resulting simulator hydraulic outputs are the equivalent circulation density (ECD) and standpipe pressure (SPP).
The simulator's performance was assessed using separate simulations with different rheological models and compared with actual field data. Similarities, differences, and potential improvements were then reported. During the simulation, the most critical drilling parameters are displayed, emulating real-time measured values, combined with the pore pressure, wellbore pressure, and fracture pressure graphs. The simulation results show promise for application of real-time hydraulic operations.
The simulated output parameters, ECD and SPP, have similar trends and values with the values from actual field data. The simulator's performance shows excellent matching for a simple BHA, with decreasing system's accuracy as the BHA design becomes more complex, an area of future improvement.
The overall approach is valid for non-Newtonian drilling fluid pressure losses. The user can observe the output parameters, and by adding a benchmark safety value, the simulator gives a warning of a potential fracture of the formation or maximum pressure at the mud pumps. Thus, by simulating the drilling process, the user can be trained for the upcoming drilling campaign and reach the target depth safely and cost-effectively during actual drilling.
The simulator allows emulation of real-time hydraulic operations when drilling vertical and directional wells, albeit with a simple BHA for the latter. The user can instantly observe the output results, which allows proper action to be taken if necessary. This is a step towards real-time hydraulic operations. The results also indicate that the simulator can be used as an excellent training tool for professionals and students by creating wellbore exercises that can cover different operating scenarios.
Simulation of Pressure- and Temperature-Dependent Fracturing Fluid Loss in Multi-Porosity Multi-Permeability Formations
Authors: Liu Chao , Phan Dung , Abousleiman Younane 
Published: December 2021

Abstract
In this paper, the multi-porosity multi-permeability porothermoelastic theory is used to derive the analytical solution to calculate the pressure- and temperature-dependent fracturing fluid loss. A triple-porosity triple-permeability source rock formation is selected as an example to illustrate the model. The effects of fracturing fluid temperature and natural fractures on the fluid loss rate are systematically illustrated. The model successfully accounts for the varying leak-off rates in the multi-permeability channels through the hydraulic fracture faces. Furthermore, thermal diffusion near the hydraulic fracture faces contributes to a variation of pore pressure whose gradient at hydraulic fracture faces directly controls the fracturing fluid leak-off rate. The model shows that thermal effects bring almost 27% variation in the leak-off rate. Comparison study indicates that the single porosity model without considering multi-permeability systems or thermal effects significantly underestimates the rate of fracturing fluid loss and predicts nearly 84% and 87% lower leak-off rate, compared to the dual-porosity dual-permeability and triple-porosity triple-permeability models, respectively. Two case studies using published laboratory measurements on naturally fractured Blue Ohio sandstone samples are conducted to show the performances of the model. It is shown that the model presented in this paper well captures the total leak-off volume during the pressure-dependent fluid loss measured from laboratory tests. Matching the analytical solution to the laboratory data also allows rocks’ double permeabilities to be estimated.
Deterministic Modeling to Predict the Natural Gas Density Using Artificial Neural Networks
Authors: Shreif Mariam , Kalam Shams , Khan Mohammad Rasheed , Khan Rizwan Ahmed 
Published: December 2021

Abstract
During the past decades, several research studies have been made to unfold the immense and diversified benefits of the innovative applications of machine learning (ML) techniques in the petroleum industry. For instance, machine learning algorithms were applied to estimate the various physical properties of natural gas. Natural gas density is considered an indispensable metric that influences the determination of several variables necessary for analyzing natural gas systems. In this work, the Artificial neural network (ANN), a machine learning technique, was applied to estimate natural gas density incorporating the influencing factors. The ANN model was also compared with another ML technique, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS). A mathematical form has been also presented using ANN. A real data set was taken from the literature, comprised of about 4500 data points assimilating three influencing input variables, including pseudo-reduced pressure (PPr), pseudo-reduced temperature (TPr), and molecular weight (Mw). The PPr and TPr are obtained by calculating the averages of the sample gas critical pressures and critical temperatures. A complicated nonlinear relationship exists between the three influencing variables and the gas density. The data set was divided into a 70:30 ratio for training and testing the model, respectively. Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANN) were applied to train and test the model. Absolute average percentage error (AAPE), coefficient of determination (R2), and root mean squared error (RMSE) were considered in the error metrics to acquire the best possible model. Levenberg–Marquardt backpropagation algorithm was employed for ANN, while subtractive clustering was used for ANFIS. Results showed that natural gas density can be well correlated with numerous inputs using machine learning tools (ANN and ANFIS). The input parameters include Ppr, Tpr, and Mw, as mentioned above. ANN performed better than ANFIS. The network was adjusted against the training sub-set to set-up weights and biases covering each node. R2 for both testing and training data was more than 99%, while AAPE was around 4% for both cases. Moreover, a detailed mathematical scheme for the ANN model is also provided in this paper.
Fracturing Fluid Design: A Closer Look at Breaker and Surfactant Selection
Authors: Alfakher Basil , Al-Taq Ali , Aldarweesh Sajjad , Alhamad Luai 
Published: December 2021

Abstract
Guar and its derivatives are the most commonly used gelling agents for fracturing fluids. At high temperature, higher polymer loadings are required to maintain sufficient viscosity for proper proppant carry and creating the fracture geometry. To minimize fracturing fluids damage and optimize fracture conductivity, it is necessary to design a fluid that is easy to clean up by ensuring proper breaking and sufficiently low surface tension for flow back. Therefore, breakers and surfactants must be carefully selected and optimally dosed to ensure the success of fracturing treatments.
In this study, two fracturing fluids were evaluated for moderate to high temperature applications with a focus on post-treatment cleanup efficiency. The first is a guar-based fluid with a borate crosslinker evaluated at 280°F and the second is a CMHPG-based fluid with a zirconate crosslinker evaluated at 320°F. The shear viscosities of both fluids were tested with a live sodium bromate breaker, a polymer encapsulated ammonium persulfate breaker and a dual breaker system combining the two breakers. Different anionic and nonionic surfactant chemistries (aminosulfonic acid and alcohol based) were investigated by measuring surface tension of the surfactant solutions at different concentrations. The compatibility of the surfactants with other fracturing fluid additives and their adsorption in Berea sandstone was also investigated. Finally, the damage caused by leak-off for each fracturing fluid was simulated by using coreflooding experiments and Berea sandstone core plugs.
Lab results showed the guar and CMHPG fluids maintained sufficient viscosity for the first two hours at baseline, respectively. The encapsulated breaker proved to be effective in delaying the breaking of the fracturing fluids. The dual breaker system was the most effective and the loading was optimized for each tested temperature to provide the desired viscosity profile. Two of the examined surfactants were effective in lowering surface tension (below 30 dyne/cm) and were stable for all tested temperatures. The guar broken fluid showed better regained permeability (up to 94%) when compared to the CMHPG (up to 53%) fluid for Berea sandstone.
This paper outlines a methodical approach to selecting and optimizing fracturing fluid chemical additives for better post-treatment cleanup and subsequent well productivity.
Assessment of Foamed Fluids Based on Surfactants and Nanoparticles for Fracturing and Acidizing Applications
Authors: Alarawi Abeer , Al Moajil Abdullah , Alrustum Abdullah , AlMahri Waddah 
Published: December 2021

Abstract
Foamed fluids are commonly used in acidizing and fracturing applications to minimize formation damage, improve fluid recovery, and as diverting-agents. However, significant concerns with foamed fluids are poor stability and low viscosity. The study objectives include evaluating the commercially available surfactants’ foamability and stability when mixed with and without nanoparticles. The prepared foamed fluid characteristics such as rheology, morphology, stability, and proppant suspension were evaluated.
Foam loop rheometer experiments were conducted at 1500 psi and 70% N2 quality to assess foam-stability and rheological properties. Foam decaying time was detected by half-life-time measurements (measuring foam-height as a function of time). Turbiscan was used to study the proppant settling using backscattering light. A high-resolution optical microscope was used to observe foam morphology and stability.
The surfactant C-nanoparticles-based foamed fluid demonstrated stable foam with a high viscosity value that reached &gt;110 cP at 100 S-1 77 °F and 70% N2 quality. Compared to the surfactant-based foamed fluid, combining the surfactant with nanoparticles as a foam-stabilizer increased the foam-half-life-time by nearly 35-75%. Foam bubbles size of surfactants A and B (with/without NPs) were large with an irregular shape and tended to rupture intermittently within 50 and 8 minutes, respectively. Bubbles average size of surfactant C (with/without NPs) based foams was small, and the count was higher than the foams of surfactants A and B. surfactant C (with/without NPs) based foams demonstrated bubbles with a spherical shape.
Turbiscan stability index values of several surfactants-nanoparticles-based foamed fluids were almost comparable at 77 and 122 °F. Lastly, the foam fluids’ proppant settling velocity prepared with nanoparticles was lower than pure surfactant-based foams.
Successful Mitigation of Excessive Backreaming in Troublesome Vertical Applications in the Sultanate of Oman
Authors: Pranava Ananda , Ali Hassan Albalushi Humaid , Mamari Zakaria , Al Zeidi Badar , Newman Tom , Mounzer Fadi 
Published: December 2021

Abstract
Drilling through some of the reactive shale formations in the western gas fields in the Sultanate of Oman has proven challenging and often troublesome. Frequently, time spent on backreaming would exceed the time required to drill the related hole sections. In addition, the carbonate Natih sequence has also proven problematic. High levels of vibrations are often encountered. Such drilling dysfunctions are known to be destructive to both bit and bottom hole assembly (BHA). Different mud systems, drive systems and reamer types were used in separate attempts to alleviate the faced dysfunctions to little avail. This paper illustrates a trial campaign introducing an alternative design stabilizer (ADS) and reamer (ADR) to the drilling BHA with the aim of addressing and resolving the aforementioned limiters.
Based on a set of agreed-on key performance indicators (KPIs), and following a methodical approach, a 4-well trial was conducted in order to introduce a unique stabilizer-reamer design while simultaneously scrutinizing and optimizing the BHA configuration accordingly. Two of the candidate wells targeted the 17-1/2" section while the other 2 wells targeted the 12-1/4" sections. The main goals were to reduce the time spent on backreaming by 50% and minimize the experienced levels of vibrations in order to extend bit runs and reliability of the different BHA components. For further comparisons, the same approach was tested on a rotary BHA as well as a steerable motor BHA in the larger hole sections.
Both 17-1/2" sections were each drilled in a single run similar to the second 12-1/4" section. The first 12-1/4" also proved smooth and required 2 runs due to bit hours, still noting a record section distance run for a single bit. All BHAs were optimized around the placement of the new design stab and reamer design combination. The optimized BHA configuration enabled pulling out of hole (POOH) on elevators for all 4 sections almost fully eliminating the hard backreaming experienced in past wells. In addition, it was also noted that in all cases the levels of vibrations were significantly reduced compared to what is typically experienced and recorded in the offset wells. This enabled a record setting bit run for that particular section and field.
The authors detail the historical challenges encountered drilling such wells then present the applied benchmarking exercise and the adopted systematic approach to tackle those challenges. Following, the unique design characteristics of the deployed technology are highlighted and how this is applied in each of the runs in view of optimizing casing point to casing point section delivery times. Finally, the achieved results and gains are underlined together with a roadmap forward.