bluuebunny/crossref_metadata_2025_split huggingface dataset:
Origins and Control Factors of Varying Oil Properties in the Lower Cretaceous Zubair Formation, Central Iraq
Authors: Li Yuyuan , Mi Zhongrong , Saeed Ahsan Mohammed , Qu Jianhua , Zhang Bo , Xie En , Zhang Zhenghong , Zhang Ke , Jaed Mustafa A. , Xiao Yong , Li Yang , Hu Guang 
Published: February 2024

Abstract
This research targets an in-depth understanding of the considerable disparities in petroleum properties of the oil produced from the Lower Cretaceous Zubair Formation in Central Iraq, an aspect currently lacking systematic knowledge. Utilizing newly obtained samples from various oil-bearing reservoir locations within the Zubair Formation core, we embarked on comprehensive component analysis and applied GC-MS testing for saturated and aromatic hydrocarbons. By identifying the characteristics of petroleum biomarkers, comparing the features of potential regional hydrocarbon source rocks (including hydrocarbon generation potential and biomarker composition), and considering the differences in saturated hydrocarbon content, we determined the origins of different oil properties and the controlling factors of these variations. Substantial disparities exist in the petroleum properties of oil from the Zubair Formation reservoir, with saturated hydrocarbon content ranging between 4.8% and 85%. Even within closely situated reservoirs, significant differences are observable. Distinct variances are present in the composition of saturated and aromatic hydrocarbon biomarkers in oils with differing properties. Oils with lower saturated hydrocarbon content evidently originate from carbonate-rich source rocks, predominantly marine algae organic matter, with an older sedimentary age and lower maturity. In contrast, oils with higher saturated hydrocarbon content largely derive from marine mudstone source rocks, with a more significant contribution from terrestrial plants, a more recent sedimentary age, and higher maturity. Our geochemical analysis of potential regional hydrocarbon source rocks suggests that oils with lower saturated hydrocarbon content (lower API) are products of the Jurassic Chia Gara and Sargelu formations at the immature stage of Type II kerogen. Oils with higher saturated hydrocarbon content (higher API) result from hydrocarbon mixing at the mature stage of the Zubair Formation source rock. Previous research predominantly attributes the oil from the Cretaceous reservoir to the Chia Gara and Sargelu formations. Our study contends that the contribution from the Zubair Formation source rock to the Lower Cretaceous reservoir oil is noteworthy and significantly influences the petroleum properties, particularly API gravity. This finding enriches the existing understanding within the petroleum industry.
Tortuosity Assurance for Safe Well Delivery Via High-Definition Dynamic Surveys
Authors: Oliveira Victor , Al Dossary Abdullah M. , Elsadig M. A. , Osman A. M. 
Published: February 2024

Abstract
The completion operation is the most important step in the well construction life cycle after drilling is completed. The success of completion operations highly depends on how the well is drilled. Having a high tortuosity well can have a significant impact on casing and completion string running to the bottom of the hole. Thus, understanding the well path tortuosity precisely is critical and one of the main objectives during a drilling operation.
Dynamic definitive surveys offer precise micro-dogleg severity (DLS) mapping and enable drilling engineers to identify potential issues such as high doglegs or key seats, which can lead to equipment failure or wellbore collapse. This allows for real-time corrective action, resulting in improved drilling performance. Additionally, better recognition of the well path trajectory through dynamic surveys helps with geosteering for maximum reservoir exposure. Dynamic surveys provide improved torque and drag modeling, aiding in predicting drilling behavior and identifying abnormal behavior for timely corrective actions during drilling operations.
Dynamic definitive surveys have become an essential component in the drilling process. This paper will present a comparison between dynamic surveys and static surveys during drilling operations. The analysis demonstrates significant benefits in micro-DLS mapping, well-path trajectory recognition, and torque and drags modeling. The dynamic definitive surveys were able to recognize micro-DLS leading to a ~15% increase in well path accuracy per stand, and also providing better TVD accuracy of ~1 ft-TVD for every 2,000 ft drilled. This is crucial for identifying formation tops and landing/geosteering the well for maximum reservoir exposure.
In conclusion, dynamic definitive surveys offer numerous advantages for drilling operations by improving overall drilling efficiency, reducing the risk of stuck piping, optimizing drilling performance, and, most importantly, ensuring the completion string reaches safely to the bottom. These surveys enable engineers to have a better understanding of the drilled well path tortuosity, resulting in cost savings and improved well delivery.
Rock Compaction Dynamic Modeling for Unconventional Reservoirs
Authors: Abdelrahman Moemen , Belaifa Elhadi , Almubarak Abdullah , Adebamiro Adedayo 
Published: February 2024

Abstract
The quantification of rock mechanics impact represents critical factor for unconventional resources (UR) evaluation and how it contributes into the total UR well's production. This quantification is a vital factor to various reservoir engineering analyses such as history matching, production forecasting, reservoir modeling and reconciling with estimated ultimate recovery (EUR) of fields. To address the rock mechanics impact, a simulation workflow was designed to capture the dynamic change of pore volume and permeability as a function of pore pressure depletion while producing from the basin. The workflow was performed as a pioneer study to integrate advanced core lab experiments that measures different rock compaction scenarios into a dynamic simulation workflow using full physics reservoir simulator. This work used a conceptual dynamic sector model instead of using actual field data. It represents unconventional horizontal wells completed using multi-stage hydraulic fractured stimulation technique. The conceptual model is used to run sensitivity assessment to evaluate different compaction trends. This assessment capitalized on advanced core lab experiments that measure different rock compaction scenarios for unconventional core plugs; i.e., the change the stress dependent parameters (porosity "β" and permeability "α") as function of the pore pressure depletion. As results, this tailored process of integrating lab measurements with dynamic simulation enables the evaluation rock compaction and its impact on wells’ EUR. In general, based on the simulation results, the change of the stress dependent parameters shows different well's EURge. While depleting the reservoir, having higher stress dependent porosity "β" parameter will add more energy into the system and will have a slight increase the EURge. On the other hand, having higher stress dependent permeability "α" parameter, will cause more permeability degradation with pressure depletion and this will reduce the well's EURge significantly.
XRF Loose Powder Method Enables High Quality Near-Real-Time Analyses - Comparison to Pressed Pellet Method
Authors: Fischer L. A. , Scola M. , Erdmann S. , Says I. P. 
Published: February 2024

Abstract
X-Ray fluorescence (XRF) analysis is a common technique to obtain the elemental composition of geological samples and is frequently applied in drill cutting analysis used for e.g., chemostratigraphy, geosteering and drilling optimization. This often requires application at the rig site and delivery of high quality, near-real time data. The overall time from sample catching to data delivery can be reduced or extended depending on the sample preparation procedure. Traditionally, the samples are powdered and prepared as pressed pellets. However, this procedure is time-consuming and requires interim steps for mixing with a binder and compressing which are potential error sources.
In this study we evaluate the effect of the loose powder method for XRF on the data quality in comparison to the conventional, but timeconsuming, pressed pellet method. Nine certified reference materials were prepared as pressed pellets and loose powder and measured with a benchtop energy dispersive XRF analyzer. Obtained intensities for 36 geo-relevant elements between Na and U are presented as intensity ratios (intensity of elementx measured in pressed pellet sample divided by intensity of elementx measured in loose powder sample) to compare both methods. Elements showing intensity ratios close to 1 can be regarded as equal quality.
Data show that elevated intensity ratios as a result of sample preparation method can only be observed for Na and Mg and intermediate values for Al, which is explained by higher absorption of loose powder samples by the foil barrier of the sample cup and the lower and variable packing densities. Analytical and experimental precision, as well as the limits of quantification show a similar trend with elevated values for Na and Mg. However, the discrepancies are marginal and do not justify the higher preparational effort nor the introduced uncertainties from additional preparation steps associated with the pressed pellet method. This study shows clearly that the loose powder method delivers high-quality elemental data and is a key to deliver near-real time XRF data for rig site applications.
Formation Evaluation of Condensate Reservoir Using New-Generation NMR T1-T2 Logging and T2-D Mapping: Case Study in the Permian in China
Authors: Zhang Bo , Zhang Yanning , Yu Jinfeng , Luo Gang , Wang Xiaoqiang , Cai Liang , Wang Wei , Wang Yue , Xian Xiu Ming , Zhao Xianran , Wu Jin Long 
Published: February 2024

Abstract
China is accelerating the exploration and development of tight sandstone and shale reservoirs of the Permian Fengcheng Formation targeting condensates. The formation evaluation is challenged because of the complex mineralogy, low porosity, and unknown formation water salinity. In addition, the operator requires a technique for fluid typing of the condensate reservoir at subsurface conditions for the optimization of the development strategy. This paper introduces a new method combining nuclear magnetic resonance (NMR) T1-T2 and T2-D mapping for formation evaluation and subsurface fluid typing of the condensate reservoir. The NMR relaxation-diffusion (T2-D) mapping successfully addresses the problem of fluid typing, by differentiating gas from oil. The measurements of continuous two-dimensional NMR T1-T2 enable the quantitative estimation of the bound and movable fluid volumes in the pores. The integration of wireline NMR, induced gamma spectroscopy, and the borehole image logs provides insight of the potential of the condensate reservoir in the Permian Fengcheng Formation. In case studies from tight sandstone and shale reservoirs in the Junggar basin, NMR T2-D mappings prove the pore fluid is dominated by gas (at reservoir conditions) in the condensate tight sandstone reservoir, for the first time confirmed by wireline logging. However, the reservoir will produce both gas and oil because of the drop in temperature and pressure. A robust methodology derived from the concept of blind source separation for extracting signals from two-dimensional NMR T1-T2 measurements is proposed. Clay-bound water volume and porosity derived from cluster volumetric analysis of NMR T1-T2 match well with those from spectroscopy and core experiment results. The movable hydrocarbon saturation proves to be effective and robust in sweet zone identification. This paper discusses an integration of NMR T1-T2 logging and T2-D mapping methods from a new-generation wireline NMR tool in the unconventional reservoir. It helps to understand the potential of the reservoirs. The subsurface fluid type is extremely meaningful for the decision of the development strategy. The condensate sweet zones identified by the new method have encouraging gas and oil productions.
Delivering Challenging Wells with Reduced NPT Using Real-Time Geomechanics: A Middle Eastern Perspective
Authors: Baghdadi Ahmed Ashraf , Vossen Johannes , Sen Souvik , Chakrabarti Prajit , Podder Tuhin , Mitra Sourav , Alabdulmuhsin Eman 
Published: February 2024

Abstract
Subsurface geomechanical assessment has critical implications for optimum drilling and completion design and successful well delivery to efficiently mitigate drilling challenges as well as avoid non-productive time. The present study focuses on the carbonate-dominated prolific hydrocarbon field of the Arabian Peninsula which exhibits significant wellbore instability challenges owing to high in-situ stress, and partial to total mud losses in naturally fractured and vuggy carbonates. Commonly faced challenges include differential sticking, drill string vibration, poor LWD (logging while drilling) log quality and subsequent wellbore instability. Being in a strike-slip tectonic regime, drilling long multi-laterals towards the minimum horizontal stress (Shmin) is associated with increased hole instability challenges, hard reaming, and mechanical sticking, which is leading to BHA (bottom-hole assembly)/ tools lost in hole and accidental side-tracks. Those contribute to significant NPT (non-productive time) and compromised drilling performance. This study discusses the benefit of integrating geomechanical modeling and real-time monitoring into the drilling operations: those helped to overcome the aforementioned challenges and reduce NPT by enhancing drilling performance.
Comprehensive geomechanical modeling and wellbore stability analyses are carried out to study the impact of in-situ stresses, and pore pressure on the stability of the rock/ wellbore wall. Along with the safe mud weight window recommendation and supporting customized drilling fluid and bit design, the study also identified potential sub-surface and drilling risks, which were quantified to optimize the drilling practices and mitigation plans. The predrill models were updated in real-time to fine-tune the predictions on each well and to better constrain the regional geomechanical understanding. During real-time GeoMechanics monitoring we are using LWD logs and drilling parameters to aid in inferring early indicators about the wellbore condition, mud invasion into the formation and other drilling challenges; the real-time GeoMechanics group facilitated timely advisory and effective communication with the rig and relevant parties. Implemented recommendations based on the symptoms of wellbore failure (i.e., early, time dependent failure) exhibited measurable- and significant improvements in drilling performance, penetration rate, overall wellbore quality towards achieving well objectives with minimized NPT. Furthermore, by establishing new communication protocols and adhering to them, a proactive response culture has been developed in order to make informed and collective decisions timely and effective.
Digital Wellbore Stability Prediction with Machine Learning
Authors: Liu Peng , Li Jian , Chen Bo , Yan Gongrui , Lei Qihong , Liang Lin , Huang Yansong , Zhao Haipeng , Wang Gaige , Sun Maoyou 
Published: February 2024

Abstract
One of the main challenges during drilling is wellbore instability. Traditionally, geomechanical model construction and wellbore stability (WBS) analysis are manually executed by geomechanics experts for well planning and drilling. The procedures are usually complicated and time-consuming due to subsurface complexity, and the results highly depend on the executor's expertise. This makes WBS analysis far from ideal and automatic. In this study, we present a physics-incorporated machine learning method that performs WBS analysis in a simple and automatic way. First, it characterizes and digitalizes subsurface geostructures geometry by labeling formations and its lithology. Then, it trains a digital geomechanics model using a series of machine learning algorithms with existing data, such as geology, well logs, drilling data, and geomechanical data. The rock mechanical properties, including rock elastic modulus and rock strength, are trained as formation material property models which describe the changing patterns in each formation. The formation pore pressure and in-situ earth stresses are trained using a physics-based hybrid algorithms, taking into account formation compaction and tectonic settings. Lastly, wellbore stability along any planned well trajectories can be predicted using this digital geomechanics model to identify drilling risks, optimize safe mud weight, and hence improve drilling practices.
This digital approach was tested and validated in a shale oil field in Ordos Basin, China. In this field, horizonal wells are drilled targeting a shale oil reservoir, this requires pre-drill WBS analysis, which usually takes several weeks following a manual methodology. With the developed new method, the digital geomechanical model was trained with seven surfaces representing different geological formations and well data from six existing vertical wells. The digital model and WBS results, including formation collapse pressure, mud loss pressure and breakdown pressure, were then compared against manual results calculated by geomechanics experts using traditional methods. The digital results matched well with manual results. The comparison demonstrated the applicability and reliability with a learning accuracy of over 99%. With this digital model, the geomechanical properties and WBS analysis of five planned horizontal wells were accurately predicted and proved consistent with actual drilling results. Another significant advantage is the high computational efficiency and reduced need for supervision. In this case, the digital machine-learning method reduced the WBS analysis time for five wells from weeks to hours. This field case confirms the effectiveness and efficiency of transferring domain knowledge and data into digital models, it enables support for massive cluster horizontal drilling activities on well pad and field scale.
Identify Thin Reservoir Thicker than One Meter by Integration of Seismic and Logging Data
Authors: Gan Liqin , Chen Jianbo , Hou Yawei , Xie Yue , Shi Hongfu 
Published: February 2024

Abstract
As the oilfield development progresses into the middle and later stage, thick sand reservoir with good quality has reached high water-cut. More attention has been paid in thin reservoir development but its characterization is very difficult. At present, the lower limit of reservoir thickness detected by seismic is five meter. This paper proposed a new method to identify thin sand thicker than one meter by integration of seismic and logging data.
Seismic data has a high lateral resolution which can reflect lateral changes of reservoir, while logging data has a highed to integrate logging and seismic data to predict thin reservoir thicker than one meter vertical resolution which can identify reservoirs thicker than one meter. Therefore, it is propos. The first step is to screen out natural gamma ray (GR) which can differentiate sand and shale well then standardize, and transform wavelet to obtain low and middle frequency information which can reflect lithology. Secondly, well/seismic calibration, synthetic, and singular value decomposition were conducted to realize dynamic clustering of seismic waveforms. Then the common characteristics of seismic waveform and GR of the same layer and depositional microfacies were analyzed, and the database for microfacies, waveform and GR at well location was established. Finally, the initial model was obtained by simulation of the original 3D seismic volume track by track, comparison of the sample group with highest correlation, and weighted average of correlation of GR. Then the final inversion result was achieved through the iterative inversion under the guidance of Bayesian theory.
This method relies on high quality of GR data and has a good characterization effect on shallow water delta sedimentation in gentle slope areas. Taking P oilfield as an example, seismic inversion by above process showed that sand reservoir thicker than one meter can be detected. Five verified wells showed that the coincidence rate of reservoir prediction can reach up to 87%.
Improving Wellbore Stability by Leveraging Real-Time Spectral Gamma Ray Logs
Authors: Qatari Ammar 
Published: February 2024

Abstract
The objective of this paper is to examine the quantification effect of clay content on wellbore stability. Clay Content is known to have direct impact on hydrocarbon petrophysical modeling. The major factor to quantify clay content is to acquire spectral gamma ray logs. Utility of standalone gamma ray readings provides only qualitative clay content model in a form of clean and clay filled fashion rather than a quantified clay content. Assessing spectral gamma ray logs in real-time can be a potential factor contributing optimized decisions during the drilling operation. Dealing with abrasive sand environment require extra formation knowledge to formulate a better drilling plan that will ultimately result in a good hole condition. Wellbore stability is directly related to the formation matrix type that is being drilled. Clay content can also contribute to the calculation of permeability in the dynamic phase. To quantify clay content, spectral gamma ray logs are vital. Once spectral gamma ray logs are available, a full petrophysical lithology model is calculated featuring quantified clay content by volumetrically identify illite, orthoclase, and kaolinite contents. It directly works as a wellbore stability indicator leading drilling engineers to formulate real-time drilling plans minimizing wellbore stability issues. These plans can involve a better formulation of a mud system, change of inclination/azimuth, change of a drilling parameter such as rate of penetration to accommodate the current quantified clay content that is being drilled.
The use of a quantified real-time formation clay content indicator to minimize wellbore instability is vital to avoid operational complexities and non-productive operational time. A comparison of qualitative and quantitative methodologies of clay content types verses wellbore stability is investigated. This will ultimately showcase the importance of establishing a wellbore instability mitigation plan leveraging real-time spectral gamma ray logs. Formulations of mud systems, rate of penetration recommendations are made based on the results. A representation of potential mitigation of non-productive operation time is showcased highlighting the vitality of the proposed method. This paper examines the direct impact of the quantification of clay content on wellbore stability. The process can add value to reduce the costs associated with wellbore instability. It can also manage to lower the non-productive operational time caused by a changed bit due to an inefficient management of either drilling mud/rate of penetration due to an unquantified formation clay content.