bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of a New Retarder Recipe Containing Boric Acid, Which Exhibits Excellent Mechanical Properties Suited for the Mid Temperature Range (MTR) in Oil and Gas Well Cementing Operations
Authors: Ohochukwu Chioma , Mathew Samuel , Liang Zhang
Published: February 2024

In field operations with Bottom Hole Circulation Temperatures (BHCTs) ranging from 240F to 280F, a range of cementing retarders have been noted to exhibit shortcomings, particularly in their ability to effectively address the entire temperature range, particularly at the higher end. This research proposes a formula that offers greater consistency, reliability, and excellent mechanical properties throughout the entire temperature spectrum.

During the laboratory analysis of this study, the API 10B-2 method was selected as the preferred approach. This method was used to examine the thickening times associated with different concentrations of commonly employed mid-temperature retarders, with the aim of determining the temperature range at which the retarder exhibits its best performance efficiency. Subsequently, the recommended recipe, which combines Boric acid and a lignosulfonate-based product, was subjected to the same testing conditions to determine the highest achievable temperature at which it remains effective. The mechanical properties of the proposed recipe were also determined and compared to the industry minimum requirements.

The laboratory findings indicated that, when testing various concentrations of the reference mid-temperature retarders (MTRs) at different mid-temperatures, it was challenging to achieve extended thickening times, especially as the test temperatures approached the higher end of the spectrum (260F-280F). Some of these reference retarders, despite their claims to be suitable for mid-temperature use, fell short in extending thickening times beyond 220F. Others, which performed well at lower temperatures, lost their desired efficiency as the test temperatures increased, reaching up to 250F. However, the recommended recipe under investigation, which combines a consistent concentration of the lignosulfonate-based product with varying levels of Boric acid, proved to be reliably effective with improved thickening time performance across the entire temperature range, spanning from 240F to 280F, as well as satisfying and exceeding the minimum required mechanical properties in the industry.

This advancement introduces an industry-dependable mid-temperature retarder (MTR) formula that spans the entire mid-temperature range, enabling the design of both shorter and longer thickening times as needed which satisfies the minimum required mechanical properties for oil and gas well cement fluids.
A Systematic Cementing Approach to Improve the Shoe Track Integrity: Case Studies from Saudi Arabia
Authors: Ali Wajid , Al Turki Faisal Abdullah , Bouaraki Mouloud , Lawrence Don Woody
Published: February 2024

Incompetent shoe tracks are typical in oil well cementing and cost many hours of lost rig time for remediation. An incompetent shoe track results from unset, severely contaminated, or no cement inside the casing section between the float collar and shoe after a primary cement job. This paper will address several case studies where a systematic and engineered approach was utilized to apply various solutions that helped to improve the shoe track integrity.

The wet shoe has been of the utmost attention to oil and gas companies, as expensive remedial cementing operations are needed to repair the deficiency in shoe track integrity. After a thorough process review, many opportunities were identified to improve the cementing basis of design, such as lead and tail slurries for liners and multiple stage jobs, increased length of shoe track, the addition of bottom wiper plugs, and the use of lost circulation material in the spacer and cement slurries. This paper illustrates the case studies where the above-stated methods were successfully applied to improve the shoe track integrity.

Some of the major contributing factors to incompetent shoe track integrity were identified as attempting to cement the long sections with a single slurry, excessive thickening time requirements to accommodate the operation of liner hangers and stage tools, over-displacement of cement during placement, overestimated bottom hole temperatures, severe or total losses during cement placement, cement slurry contamination by the lack of a bottom wiper plug, and picking weak casing point. It was also observed that the consequences of poor shoe track integrity were amplified in challenging drilling environments where formations were either reactive, hard and abrasive, abnormally pressured, high downhole temperature, or prone to lost circulation. As a result, an increased effort was put in place to eliminate the poor shoe track integrity by implementing the opportunities identified during the process review. Cement inside the shoe track was found to take more weight on bit and have a slower penetration rate during drill out. Also, the required casing and formation integrity tests were achieved even in areas historically prone to compromised shoe track integrity. This confirmed the success of this systematic cementing approach and helped revise the basis of design.

This paper presents a detailed study of the novel engineering process that was successfully deployed to plan and execute the primary cement jobs with the assurance of shoe track integrity. In addition, this paper highlights the systematic approach utilized to eliminate or mitigate the occurrences of incompetent shoe track integrity with observed improvement in field deployment results.
Integrated Subsurface Development & Planning (SSDP) Dashboard for Surveillance, Optimization, Cost Reduction and Streamline the Decision-Making Process in Mature Field, Pertamina Hulu Rokan Zona 4
Authors: Gilang Alfian , Saribu Juanda Dolok , Renditya Ardiansyah , Fariz Muhammad , Fernando Elrey
Published: February 2024

In the midst of digital transformation, Pertamina’s management and workers are required to be able to adapt to the new environment in achieving company goals. One of the tools to make it easier to monitor and make quick and precise decisions is the use of an integrated dashboard. This increases the optimization of the execution of a work plan and saves costs from work plans each year.

Integrated SSDP Dashboard is a Zone 4 workplan monitoring dashboard that integrates rig barchart data, production, development (Plant Of Development, investment decisions, reserves & resources) and well realization with the following stages (1) Input – gathering data from any source file, (2) Process – Analysis and formulate integrated data and calculation, (3) Output - Dashboard finalization with executive results in accordance with standard templates, interactive visualization to facilitate data analysis and decision making, dashboards are updated regularly. Also streamlines reporting to regional/central offices.

This dashboard provides the ability to take standardized data at a high level so as to save time in presenting reports. In addition, integrated data can help workers to the management level in determining planning after which it will increase company profits. Its massive use can have a positive impact on business processes in the company.

The dashboard is generated from the integration of data from various divisions in Zone 4 which is interactive, user-friendly and can facilitate the needs of the worker level to management so that the productions & resources monitoring process runs optimally. The optimization rate in management decision making using SSDP Dashboard is 96%. Dashboard succeeded in making cost efficiency related to drilling costs (rig rental, materials, and services) cost allocation of ± $65 million OTOBOSOR (on time, on budget, on schedule, on return) in the current year and loss of production due to Drilling & WO work plan which retreated ± 6,200 BOEPD. Reports received by management are dynamic (Power BI through Ms Team) where the process of retrieving supporting graphs and tables takes ± 5 seconds. Data is successfully protected through Pertamina’s corporate account authorization to the share folder. The level of ease of evaluation process for monitoring workplan reached 97% more than the target of 85%.
Using Data-Driven Analytics Workflow to Find out Highly Watered-Out Mechanism and Novel Solution in Horizontal Wells for Heterogeneous Carbonate Reservoir
Authors: Hu Dandan , Li Wenhuan , Li Qianyao , Chen Yihang , Wu Yuanbing , Hu Songhao
Published: February 2024

K reservoir is a highly heterogeneous pore carbonate reservoir with thin layer and high permeability zone at the top. It adopted the overall horizontal well pattern, the water cut rose rapidly and "double-inverse" water flow dominant channel formed subsequently after water injection. The water cut of most producers rose rapidly to more than 85%, resulting in a large decline of oil production and poor sweep efficiency.

In the paper, a novel methodology and data-driven analytics workflow was established for detecting the characteristics of watered-out horizontal wells, revealing the highly watered-out mechanism, describing the residual oil mode on different main factors and proposing the solution for highly watered-out horizontal wells. The paper analyzed the rules and characteristics of water cut change after water injection and clarified the effect of the matching relationship of horizontal well trajectory and the main factors on the rapid rise of water cut. To diagnose the mechanism and reasons for the rapid rise of water cut, the watered-out conditions have been described for producers, injectors and inter-wells in longitudinal direction at different times through passing wells from lower formation based on logging data. The paper put forward the theoretical calculation formula for liquid effusion of horizontal well bore and the prediction formula of liquid discharge time. By discharging the accumulated liquid from the well trajectory at the high permeability zone, the residual oil with the well trajectory in other layers could be used to expand flooding volume, reduce the water cut of the producer, and restore the normal production for these high water cut wells. It was indicated that the actual incremental oil result for these wells were decided by the relationship of well trajectory and the main controlling factors and the remaining oil distribution.

This workflow has successfully been applied to a giant heterogeneous carbonate reservoir. The water cut of most wells was significantly reduced, with an efficiency of more than 90.0%. The time of liquid discharging and water cut controlling was 1 and a half months to 4 months, and the water cut decreased between 8% and 24%, and the total incremental oil of 2 million barrels has been achieved.

Strong heterogeneity in carbonate reservoirs of Middle East generally develops and easily causes high water cut for producers, the innovative strategies in the paper has good adaptability and reference for these reservoirs.
Application of Multi-Scale Fracture Identification in a Shale Gas Reservoir in Southwest China—A Case Study
Authors: Qin Qiuping , Jiang Tingxue , Zeng Yongjian , Bian Xiaobing
Published: February 2024

With the development of seismic acquisition methods, research theories, and application of various interactive interpretation software, the application of seismic technology has developed from structural interpretation to reservoir evaluation [1], lithology interpretation, reservoir description, fluid identification and other aspects. Multi-scale fracture identification driven by seismic data has been widely used in the development of shale oil and gas reservoirs. Due to the introduction of coherent data, artificial intelligence and visual interpretation software in recent years, the ability and accuracy of fault structure identification based on seismic data have been greatly improved. The methods used to predict fractures with seismic data include shear wave splitting detection [2, 3], conversion wave fracture detection [4], longitudinal wave anisotropy detection and post-stack seismic attribute method. Post-stack seismic attributes contain rich lithology and physical property information, which is the most widely used fracture prediction method at present. However, its structural interpretation is mainly based on the seismic waveform characteristics of Inline and Crossline profiles extracted from seismic data. Due to the small fault distance, the characteristics of in-phase axial dislocation in time profiles are not obvious. In addition, part of the time section is missing in the seismic interpretation grid line, which determines that the interpretation precision of micro-structures such as small faults is low.

Based on the 3D post-stack seismic data, well logging and 5 horizons interpretation data a shale gas reservoir in southwest China, we carried out the multi-scale fracture identification research. The whole working area is about 200km2, and the fracture development of the Longmaxi Formation buried to a depth of 3700 ~ 4200m is the focus of the study. In order to achieve a more accurate and effective interpretation of small and medium-sized fractures and other micro-amplitude structures, the research on seismic multi-scale fracture identification of small and medium-sized fractures is carried out on the three-dimensional seismic data in the study area. Combined with the seismic and geological data, the fracture display of the whole area is enhanced by structure-oriented filtering. The machine learning method has a good application effect on large fracture identification. The fracture identification algorithm based on CNN (Convolutional Neural Network) image segmentation transforms the problem of image classification into the problem of image segmentation. The CNN network based on U-net is used to identify large-scale fractures. And then d-LoG (Laplacian of Gaussian Operator) coherent sensitive to medium-small scale fractures are extracted. Finally, the identification results of large, medium-small scale fractures are fused to evaluate the development of fractures in the working area.
Utilizing Advanced Rotating Control Heads Technology to Enhance Safety While Drilling a Challenging Exploratory Well - A Successful Case History
Authors: Haq Mohammed Aleemul , Omer Mohammed
Published: February 2024

The drilling operator wanted to improve hydrocarbon recovery during drilling a development well using rotating control devices (RCD) for the upper 17-1/2" hole section.

The challenge to drill this section was shallow gas that can lead to a kick. To drill these formations conventionally would increase the risk of the well taking a kick that could directly affect the time required to drill the well to its target depth. A closed-loop system was used to anticipate the well taking an influx of shallow gas while drilling this formation. In the event of the well taking an influx, the influx can be safely diverted with RCDs away from rig floor.

A closed-loop drilling system was created by installing the Rotating Control Device on top of a 21-1/4" 2K Annular BOP prior to drilling the 17-1/2" section. With this closed-loop system any shallow gas influx can be diverted away from rig floor, thus improving safety to personnel. Another advantage of using a RCD is that the operation can be switched to conventional mode directly without have to rig down the RCD system. Also, using RCD will not interfere with the rig’s well control system.

The primary objective of utilizing the RCD was to enhance safety while drilling the development well which contained known hazards already assessed from drilling the previous well. RCD 7800 was utilized to mitigate drilling hazards generated from the loss circulation, gas migration, influx, and the presence of shallow gas. All the objectives were achieved: establishing a closed circulation system, additional safety in drilling a formation containing gas, and ensuring control of return flow.
A Novel Approach to Time-Lapse Logging in Producing Horizontal Wells Using Logging While Tripping (LWT) Technology - A Case Study Review in a Middle East Reservoir
Authors: El Wazeer F. , Berdiyev Y. , Bazuhair M. , Al Kaabi R. , Propper M. , Lentz C.
Published: February 2024

Naturally flowing horizontal oil producers typically suffer from increasing Water-Cut within 5 to 7 years of commencing the production. This paper will describe the application of Logging While Tripping (LWT) technology in identifying water-producing sections and hence isolate them effectively by installing Adaptive Inflow Control Devices (AICD) in the permanent completion.

This paper will describe the method of deployment of LWT technology which can measure resistivity, caliper, density, neutron porosity, and gamma-ray in the open hole lateral section from inside the drill pipes. LWT logging tools are pumped down inside the drill pipes and locked into place in the LWT collars and data will then be acquired while tripping out of the well with virtually no extra rig time required. This paper will also describe how this technology can be used in time-lapse logging to be compared with the original saturation profile at well day 1 and identify new water sweep sections in the horizontal oil production wells.

This approach has been applied in more than 10 horizontal wells in the Middle East; timelapse logs have been successfully used to install AICD devices and improve oil productivity. Results from some wells shall be presented. The study showed that with LWT, it became possible to monitor the horizontal/deviated producing well’s water saturation with the following advantages when compared with the conventional method:Using LWT reduced well intervention time by not less than 200% and hence it also significantly reduced the overall well intervention cost and all the associated non-productive time (NPT) and lost-time incidents (LTI).Measuring time-lapse saturation with deep resistivity tools with a depth of investigation of 50-60 inches; which is greater than the conventional sigma saturation tools of 15-17 inches.Measuring time-lapse porosity to observe the effect of acid treatments if any.Caliper data was used to avoid sections of the borehole where the AICDs most likely will not achieve isolation.Virtually zero risk during logging since the radioactive chemical sources are kept safe inside drill collars and can be retrieved in case of stuck pipes.

Ultimately, using LWT achieved its objective of identifying water sweeping sections, resulting in a successful and economic reduction of water.

This paper illustrates a case study for the first time for the successful implementation of LWT in water zonal isolation by time-lapse logging. The paper will open the door for a wider range of LWT applications in high-risk wells delivering significant optimizations and improvements to the well intervention operations.
Characterization and Numerical Simulation of Remaining Oil in Water-Wet Sandstones Based on Micro-CT Displacement Experiment and VOF Model
Authors: Ma Kuiqian , Li Chao , Liu Zongbin , Lu Yan , Huang Jianting
Published: February 2024

Eocene sandstones in the Huanghekou Depression, Bohai Bay Basin, China are characterized by highly variable macroscopic petrophysical properties and heterogeneous microscopic pore structures, and thus control fluid flow behavior and remaining oil distribution in porous rock. In this paper, X-ray CT coreflooding experiments were performed on three sandstone samples with different petrophysical properties. In addition, an integrated approach based on image processing, pore network modeling and the traditional volume of fluid (VOF) model served to quantify the fluid flow behavior and remaining oil distribution in porous rocks. Pore throat size and pore connectivity are the key factors controlling the fluid flow in porous rocks. The water phase advances rapidly along the dominant fluid flow channels and results in a rapid increase of oil displacement efficiency in the sandstones with good pore connectivity. The water flooding rate is also a vital factor affecting the fluid flow by controlling the number of capillaries. The findings provide useful insights into the variation of remaining oil during water flooding process and the fluid flow behaviors in heterogeneous sandstone.
Experimental Research of Imbibition Law in the Continental Shale in Sichuan Basin in China
Authors: Zhou Chao , Chen Yashu , He Zuqing , Wang Zhifa , Zhang Wei , Xu Yuzhu
Published: February 2024

Marine shale has been developed successfully in China, however, the exploration and development of the continental shale is still limited. Study about imbibition and influence factors of the continental shale is insufficient. The objective of the proposed paper is to design and conduct an imbibition experiment to research imbibition rate, imbibed volume, induced crack and influence factors in the Jurassic continental shale in Sichuan basin in China. The imbibition experiment is developed based on the low field Nuclear Magnetic Resonance(NMR) and accurate weighting. The permeability, porosity and mineral composition of shale samples of LU Formation and DD Formation are measured and the differences are analyzed. The change of permeability and porosity before and after the imbibition process is set as the evaluation index and the influence factors of imbibition in the continental shale are analyzed. The influence factors include lithology, imbibition fluid, imbibition pressure and clay content. Besides, the wettability of the continental shale is estimated in the experiment. The experimental results show that the imbibition capacity of the limestone sample is weaker than that of shale samples, and the shell limestone interlayer in the continental shale reservoir may inhibit the imbibition and crack propagation in the shale. Oil phase may enhance the crack propagation after the shale samples induced crack in aqueous phase, and the complicated phase imbibition in the continental shale reservoir may be beneficial to the permeability improvement. The forced imbibition has weaker capacity of crack induction and permeability improvement compared to the spontaneous imbibition, and the influence of the reservoir confining pressure on the imbibition should be considered during the well shut-in process after hydraulic fracturing. The higher clay content shale sample has stronger capacity of crack induction and permeability improvement compared to the lower clay content shale sample. The wettability of the continental shale sample is water-wet. The imbibition experiment reveals the imbibition law and the induced crack character of the continental shale samples, whose results fill the gap in existing studies and have a theoretical guidance for the shut-in and flowback design in the continental shale reservoir.
Innovative Wellsite Porosity Analysis of Tight Cuttings by NMR
Authors: Ali Farhan , Mheibesh Yazan , Valori Andrea , Al-Hamad Mohammed , Abdallah Wael
Published: February 2024

Knowledge of petrophysical parameters of a reservoir plays a significant role in reservoir formation evaluation. Most of the current information comes from downhole logging or special core analysis after acquiring reservoir core samples. Drill rock cuttings, however, are available continuously over the entire depth of the drilled well. Such cuttings can be used to obtain petrophysical data which can add a significant value to formation evaluation while drilling the well. In the current study, we introduce a workflow to accurately obtain porosity from irregular shaped and small size cuttings using nuclear magnetic resonance (NMR).

A set of 9 drill cuttings were washed-out to remove the mud contamination, sieved in a sand-shaker, and then 25-50 g of each drill cuttings samples were collected for the particle size above 1 mm. The cuttings were stacked before they were centrifuged at elevated speeds, and the produced reservoir fluids were monitored. NMR was used to measure the porosity of the cuttings. However, the main uncertainty in such measurement was always the presence of fluids on the outer surface of the cuttings, making it very difficult to separate or distinguish from the pores’ fluids. Therefore, an additional step was implemented as part of this study, to overcome such difficulties.

The stacked rock cuttings were centrifuged, to significantly remove the excess fluids at the cuttings surface, allowing accurate determination of the total porosity. Using the cuttings particle size and the centrifuge arms-length, a threshold capillary pressure value was obtained. At such threshold pressure value, only the excess fluids are removed, without displacing any of the fluids from the pores. It has been observed that only minimal pressure or centrifugal speed is needed to remove the excess water, upon investigation this speed was found to be 730 RPM which was equivalent to 0.016 psi. NMR measurements were performed before and after centrifugation, a clear differentiation in the signal was observed. The measured NMR porosity at the end of centrifugation cycle was found to correlate well with the measured porosity from the reservoir.
Smart Computational Algorithms for the Prediction of Interfacial Tension between Water and Hydrogen – Insights into Underground Hydrogen Storage
Authors: Kalam Shams , Khan Mohammad Rasheed , Arif Muhammad
Published: February 2024

Hydrogen has the potential to play a critical role in the energy transition economy for the next decade, aiding in decarbonization. Hydrogen has a two-pronged utility in the energy mix by acting as a fuel and supporting the distribution of other renewable sources through electrolysis. Nevertheless, a critical hurdle in achieving autonomous hydrogen-based energy transition is the safe, reliable, and economical methods of underground storage mechanisms. Consequently, this requires comprehending interaction processes between hydrogen and subsurface fluids that can affect the storage capacity with a major role of interfacial tension (IFT). Accordingly, this work used smart computational intelligence methods to delineate IFT predictions between H2 and H2O mixture for various pressure/temperature conditions and density variance.

A systematic approach was adopted to implement predictive models for IFT prediction by utilizing an experimental data set. A comprehensive statistical analysis is performed to achieve model generalization capabilities and improve control over the most relevant input parameters. Consequently, IFT is demarcated as a function of two readily available inputs of pressure, temperature, and calculated density difference. Various smart approaches in this work are proposed by developing an IFT predictor using Support Vector Regression, XGBoost, and Decision Tree algorithms. Machine learning model training is enhanced using a k-fold cross-validation technique combined with the exhaustive grid search algorithm. Post-training, the developed models are tested for reliability using blind datasets reserved for this purpose.

A fair comparison between model efficiency is ensured by using an in-depth error analysis schema that includes various metrics like the correlation of determination, average error analysis, graphical error analysis, and scatter plots. This generates a relative ranking system that weighs various factors to classify one model as the most efficient. For the IFT prediction problem, it was found that the XGBoost was aptly able to yield high efficiency and low errors. This stems from how XGBoost functions map the non-linear relationship between pressure, temperature, density difference, and the IFT. It was also observed that enhanced intelligent model training through multiple techniques resulted in optimized hyperparameters/parameters. Lastly, a trend analysis was conducted to confirm the robustness of the developed XGBoost model.
Anomaly Detection of Sensor Measurements During a Turbo-Machine Prototype Testing - An Integrated ML Ops, Continual Learning Architecture
Authors: Palaniappan Somasundaram , Veneri Giacomo , Gori Valentina , Pratelli Tommaso , Ballarini Valeria
Published: February 2024

Building a reliable Machine Learning infrastructure in the Energy domain is a complex task; indeed, it requires a full data integration, continual learning, continual prediction, and the integration of human feedback. Continual learning is a challenging task due to the risk of machine learning to forget former data while learning from new ones (catastrophic forgetting). We present a Machine Learning Operations (MLOPS) architecture able to perform continual learning every day on more than 500 models, to perform inference on new data using such models and to take human feedback and data shift into account. More in detail, we continuously train a recurrent Deep Neural Network to build a virtual sensor from other signals and we compare the prediction versus the real signal to raise (in case) an anomaly. Furthermore, Kullback-Leibler (KL) divergence is used to estimate the overlap between the input distributions available at training time and the distributions seen at test time to estimate the confidence level of the prediction. Finally, we integrate human feedback to tune model retraining. The tool has been applied on a set of about 500 sensors on a three-months long test campaign. Results report 100% recall and 94% accuracy. Moreover, using a recurrent neural network, the system is self-explainable (XAI) by design: indeed, the user can compare the predicted vs real signal to understand the performance of the model. We propose a data intensive MLOPS architecture integrating continual learning, anomaly detection and user feedback. The architecture is based on a standard cloud, it is event-driven and integrates retraining based on GPU capabilities.
Formation Evaluation Through Stuck Heavy Weight Drill Pipe for Drilling Optimization: A Case Study
Authors: Adedamola A. , Ijeh O. R. , Ibironke O. , Afolabi A. , Guo W. , Oaiya L. , Chiroma A. A.
Published: February 2024

Formation evaluation plays an important role in the planning and design of a well. Understanding subsurface reservoir and fluid properties are critical in the efficient management of subsurface resources. During drilling, several challenges including failure of Logging While Drilling sensors could limit the gathering of formation evaluation data, particularly well logs. In this paper, a detailed case study is discussed showcasing an unconventional application of pulsed neutron logging for drilling optimization.

A multidetector pulsed neutron tool was logged through stuck heavy weight drill pipe (HWDP) in an unknown environment with limited data. Significant focus was placed on real time data monitoring to ensure high amount of neutron interaction could be generated for measurement. Pulsed neutron data was acquired in both inelastic and capture modes. Due to the wellbore environment, customized environmental fan charts were modeled to specifically correct for the impact of the heavy mud and HWDP to assess the response from the formation behind the pipe.

The pulsed neutron data was acquired along with gamma ray across the newly drilled formations through the HWDP. The natural gamma ray data was highly attenuated and thus, could not be used for lithology identification. Sigma data along with pulsed neutron porosity indicators were used for lithology identification, shale volume estimation and porosity calculations. Slow capture data from the third detector of the pulsed neutron tool combined with inelastic count rate was used for gas saturation analysis while carbon-oxygen data was used to evaluate the presence of oil. Proper environmental corrections were applied during data analysis using pre-modeled fan charts for the specific wellbore environment. The results of the interpreted pulsed neutron data confirmed the presence of light hydrocarbons within the encountered reservoir along with the associated pay thickness, saturation and formation properties. Consequently, invaluable data was gathered in the untested fault block within the field despite the attendant challenges. Furthermore, drilling operations and recovery plans were optimized based on the pulsed neutron interpretation, thereby avoiding unnecessary well costs associated with making wrong decisions.

This paper demonstrates the application of pulsed neutron logging for formation evaluation through heavy mud and stuck heavy weight drill pipe in order to make efficient corporate management and drilling decisions. The impact of the wellbore drilling environment was assessed real-time to ensure logging parameters were optimized. The value of pulsed neutron logging in this unconventional application was successfully illustrated in this case study despite the limited data and unfavorable logging conditions.
Machine Learning-Assisted Prediction of Electrical Properties for Heterogeneous Reservoirs: Case study in Mamey Field, Northern Colombia
Authors: Moya C. , Prado R. , Caycedo H. , Perez D. , Jimenez C. , Martel L.
Published: February 2024

Petrophysical characterization in reservoirs with high heterogeneity is always a challenge and the application of state-of-the-art technologies plays an increasing role in achieving accurate and timely results.

The target reservoir is composed of interlaminated mudstones and very fine to fine sandstones enclosed in a deltaic environment and capped by cross-stratification sandstones associated with incised valley deposits. The depositional environment creates the geological and petrophysical complexity of the field.

This case study describes an automatic learning technique or "Machine Learning" to determine the electrical properties "m" and "n". The methodology combines logs, rock types, facies and digital core analyses from Mamey field, Lower Magdalena Valley basin, northern Colombia.

An artificial neural network (ANN) methodology based on a self-organizing map (SOM) was applied. The ANN was trained via unsupervised learning to produce a low-dimensional discrete representation of the input space of the training samples called a map. The method does achieve a reduction in dimensionality and creates a continuous curve. An SOM output is typically a branch based on the cluster.

The results obtained indicate that the machine learning technique is feasible to estimate a continuous curve of the Archie parameters "m" and "n" associated with the textural changes identified in the images and computed tomography. The variables "m" and "n" strengthened the resistivity-dependent water saturation model that affects in-situ gas and hence reserves calculations. In addition, the constructed rock electrical properties model reduces costs associated with special core analyses, especially in highly heterogeneous and complex formations.
Fast and Accurate Determination of Reservoir Fluid Interfacial Tension Using FTIR Spectroscopy
Authors: AlRadhwan Azizah , Al-Hamad Mohammed , Abdallah Wael
Published: February 2024

The interfacial tension (IFT) between crude oil and water is an important parameter that helps to understand oil reservoir behavior for reserve estimation to fluid distribution and its recovery mechanism. IFT is usually determined in laboratories, where established methods are used, such as the pendant drop technique. Measuring an accurate IFT, however, can be difficult because IFT is highly sensitive and can suffer from contamination. The IFT experiments for crude oils require a long time for equilibrium and decay stability. In this study, we explored and developed a quick method to derive the IFT of crude oils, with minimal oil sample volume needed, using the Fourier transform infrared (FTIR) spectroscopy technique. Initially, IFT was measured against deionized water for 13 crude oil samples using the pendant drop technique, and then crude oil samples were analyzed with the FTIR spectroscopy tool. From the results, a strong relation was found between the measured IFT values and the FTIR spectroscopy data, allowing us to build a correlation with a strong coefficient of determination (R2= 0.9029) to predict the IFT of dead crude oils at ambient conditions. The correlation was further validated using eight new crude oil samples, where it showed good results with an average error of less than 1.0 mN/m.
Improving the Quality of Water Saturation Calculation Based on Resistivity Logs for Field Under Steam Injection - Jaguar Field
Authors: Mastoadji Erry
Published: February 2024

Jaguar field is one of the largest oil field producers in the Central Sumatra Basin. Currently, there are more than 11,000 wells drilled in the field and it has been developed by steam flood enhanced oil recovery since the 1980s. Steam flood injection and production performance are being monitored through regular cased hole reservoir surveillance acquired from around 900 Temperature Observation Wells (TOWs). Dynamic reservoir properties of temperature, gas/steam saturation and remaining oil saturation monitored through these TOWs.

In reservoir under steam injection, water saturation calculation based on open hole log (resistivity) will be very challenging. Because the presence of steam in reservoir which makes temperature higher, will affect resistivity value in reservoir, either resistivity log from wire line acquisition or water resistivity (Rw). Resistivity of a saline solution measured at two different temperatures reads differently: it will read lower in high temperatures; higher in low temperatures. The accuracy of resistivity value later will affect water saturation result.

Currently we used formation temperature in Jaguar field based on Gradient Geothermal based on internal study (2004). The formation temperature from this equation gives low temperature, even lower than maximum reading temperature from open hole log. This will make Rw value in the reservoir is higher than it should be. With Rw value higher, oil saturation calculation result will be more pessimistic.

To get the more reliable oil saturation calculation result, we need to get information of temperature that is closer to the actual formation temperature in the reservoir. Several alternative temperatures can be obtained and used to replace the formation temperature of the geothermal gradient.
Enhancing Frac Fluid Recovery in Unconventional Shale and Tight Gas Fracturing with Eco-Friendly Flowback Aids
Authors: Essam Ahmed , Abdelgawad Khaled , Ibrahim Ahmed
Published: February 2024

Hydraulic fracturing, a method used to stimulate oil and gas from shale and tight formations, faces challenges like fluid blockage and fast declining oil or gas production rates due to the significant impact of capillary forces on water retention. To address this, surfactants and microemulsions are commonly employed as flowback additives to reduce surface and interfacial tension, enhancing water recovery during hydraulic fracturing. The effectiveness of a flowback additives is highly impacted by the harsh subsurface conditions, such as high salinity and high temperature. This study aims to assess the performance and effectiveness of methylimidazolium chloride based ionic liquids as flow back additives at high salinities and temperatures and compare it to commercially used flowback additives.

Different experimental analysis was conducted to screen different concentrations of methylimidazolium chloride based ionic liquids (X1,X2,X3). Surface tension measurements were conducted to estimate the critical micelles concentrations (CMC). Spinning drop tensiometer was utilized to measure interfacial tension (IFT), in addition to contact angle measurements were used to evaluate the impact of the flowback additive on the wettability and the displacing behavior. Seawater was used as the base fracturing fluid with a salinity of 57,000 ppm and temperatures up to 90°c for all experiments.

Different formulations were used and yielded surface tension values varied from 30 to 45 mN/m with CMC values ranging between 0.5 to 1 gpt which is similar to commercial flowback additives. The different formulations showed different IFT values with the lowest IFT value of 3 mN/m in the case of X3. In addition, contact angle measurements showed changing the rock surface to be more water-wet after treating the rock with the flowback additives.

According to our results, methylimidazolium chloride-based ionic liquids can be used as environmentally friendly flowback additives especially in harsh conditions of high temperature and high salinity where the conventional additives are not suitable. This will contribute to the development of more sustainable and environmentally conscious practices in hydraulic fracturing operations. Ultimately, the utilization of these additives can help minimize water blockage, and formation damage impacts, and enhance shale gas production.
Automated Plug-And-Perf Decreases Operational Risk and Improves Conveyance Efficiency
Authors: Walden J. , Mishra A. , Ostermann N. , Padilla L.
Published: February 2024

Across upstream oil & gas operations, automation continues to be an increasingly important way to reduce risk and improve efficiencies, even for complex tasks historically requiring close human attention. Traditional manual processes are prone to higher inherent risks and inefficiencies, leading to unplanned non-productive time and cost overruns. However, the integration of advanced technologies such as robotics, closed-loop systems, and digital twins has paved the way for automated systems that are revolutionizing the industry.

Within unconventional completions, wireline conveyed perforating or "plug and perf" jobs are a critical part of the hydraulic fracturing operation. A typical plug-and-perf job requires 6 or more individuals to convey the perforating gun string via wireline winch and pump down units over the course of a multi-well completion. This operation requires focus from all personnel involved since variable downhole conditions can cause costly unplanned events such as pre-set plugs or pumped-off tool strings downhole. These events result in unplanned well interventions such as coil tubing fishing jobs, which can be extremely costly. Natural inconsistencies introduced from different personnel conducting the operation also leads to variation in job efficiency.

Halliburton has developed a novel system that takes real time data from the downhole tool string, the wireline winch, and the pumping units on location to feed a closed-loop system to convey perforating gun strings safely and efficiently within a wellbore. The system enables the winch and pumps to respond in real-time to variable downhole conditions and also predicts tool motion ahead of the string and continuously updates a forward-looking model using a digital twin. This method reduces the risk of unplanned events like pre-set plugs and pumped-off tool strings. Use of automated plug-and-perf has demonstrated up to a 12% faster run time while using less fluid than the same operation run manually.

This paper highlights the benefits of automating the complex and manual task of pump-down perforating, including the reduced risk of unplanned well interventions, improved operations efficiency, and fluids consumption optimization. It has been demonstrated that all of these lead to decreased costs for both service company and operator, based on deployments in both the Permian and Denver-Julesburg Basin of North America. The use of automated perforating operations leads to a safer and more productive oil and gas industry, where human expertise is augmented by technology to achieve better outcomes.
A Four-Dimensional Geostress Evolution Model for Shale Gas Based on Embedded Discrete Fracture Model and Finite Volume Method
Authors: Wang Qiang , Wang Yufeng , Zhao Jinzhou , Hu Yongquan , Lin Chen , Li Xiaowei
Published: February 2024

Stress changes associated with reservoir depletion are often observed in the field. The four-dimensional stress evolution within and surrounding drainage areas can greatly affect completion of infill wells and refracturing. To accurately predict the four- dimensional stress distribution of shale gas reservoir, a coupled fluid- flow/geomechanics model considering the microscopic seepage mechanism of shale gas and the distribution of complex natural fractures (NFs) is derived based on the Biot's theory, the embedded discrete fracture model (DEFM) and finite volume method (FVM). Based on this model, the four-dimensional stress prediction can be realized considering the mechanism of adsorption, desorption, diffusion and slippage of shale gas and the random distribution of NFs. The results show that in the process of four- dimensional stress evolution, there will be extremes of σxx, σyy, σxy, Δσ, α and stress reversal area at some time, and the time of occurrence of extremes is different at different positions. The key to determine this law is the pore pressure gradient with spatio-temporal evolution effect. Different microscopic seepage mechanisms have great influence on the storage and transmission of shale gas, which leads to great differences in the distribution of reservoir pressure and four-dimensional stress. The influence of microscopic seepage mechanism should be considered in the process of four- dimensional stress prediction. The larger the initial stress difference is, the more difficult the stress reversal is. When the initial stress difference exceeds a certain limit value, the stress reversal phenomenon will not occur in the reservoir. This research is of great significance for understanding the four-dimensional stress evolution law of shale gas reservoir, guiding completion of infill wells and refracturing design.
A New Model to Predict the Dielectric Properties by Employing Artificial Neural Networks
Authors: Hassan A. M. , Oshaish A. A. , Al-Ofi S. M. , El-Husseiny A. A. , Mahmoud M. A.
Published: February 2024

Studying the dielectric properties of reservoir systems can provide crucial information such as water saturation, total porosity, and brine salinity. Different models have been developed to estimate the dielectric parameters such as the conductivity and relative permittivity. However, multiple assumptions are used, and considerable computational processes are employed. This work aims to develop a new model to predict dielectric properties utilizing artificial neural networks (ANN).

In this study, the relative permittivity (dielectric constant) and conductivity for shale rocks were predicted based on the raw measured data. Multi-frequency dielectric measurements were carried out using a coaxial dielectric probe. The model input is mainly the reflection caused by the samples at different frequencies. The relative permittivity and conductivity of the samples were predicted using the ANN model at a frequency range of 1MHz to 3GHz, in order to capture multiple polarization mechanisms. Different types of error indexes were determined to indicate the prediction performance. Also, a comprehensive analysis was conducted to optimize the performance of the developed ANN model.

The results showed that the ANN-based model can effectively predict the dielectric parameters. A correlation coefficient of more than 0.94 was obtained. The optimized ANN model consists of one hidden layer with 7 neurons and uses Levenberg-Marquardt (trainlm) function during the training phase. Thereafter, a new equation was extracted from the developed ANN model to allow fast and accurate estimations for the dielectric properties. The developed equation can be applied to a wide range to estimate the relative permittivity and conductivity of shale rocks.

For the first time, an AI-based model is developed to estimate the dielectric properties of shale rocks. The proposed model can predict the dielectric constant and conductivity in less time and with high reliability.