bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integration of Borehole Image Analysis, Open Hole Logs and Core Data to Unlock Stratigraphic & Sedimentological Analysis of a South Eastern Algeria Field.
Authors: Rezig Drifa , Hadjar Imane Ouarda , Nettari Ferhat , Hertz Matthew , Boukhenifra Messaoud , Bouacida Djamil , Hadjarab Hedi , Salmi Omar 
Published: February 2022

Abstract
The identification of the depositional environment is critical to the delineation and prediction of the best quality reservoir. It often starts with a detailed core description, which is based on number of features. Borehole image augments the core data by providing important information for orienting features, filling in gaps between cores, recognizing sedimentary structures and sorting for facies analysis and identifying depositional environments.
Oil-Based Micro-resistivity Images and Ultra-sonic Borehole Images were successfully applied to reservoir modeling by introducing a statistically correct model that obeys facies association rules and facies contacts and improves the dynamic history match.
The principal hydrocarbon reservoir of field-A in the South Eastern Algeria basin, TAGI, is part of a fluvial system. The microfacies were analyzed with a pseudo-grain size profile and textural analysis of the borehole resistivity and ultrasonic images. The TAGI sits unconformably on the Paleozoic rocks, it consists of variable sequences which have been sub-divided into four fluviatile cycles. The depositional environments are mainly amalgamated channels passing laterally to flood plain, crevasse splay and sheet flood deposits. The correlation of the cycles combined with empirical functions enabled estimating the geometry of the sandstone bodied for each deposition element. This is required input for object modeling.
This study showed the value of borehole image logs in sedimentology analysis, which progressed from single-well borehole image interpretation to conceptual model construction and channel dimension estimation.
Discrete Fracture Network Modeling of Saline Lacustrine Tight Oil Reservoirs Severely Deformed by Tibetan Plateau Neotectonism
Authors: Chen Xiaodong , Tong Yanming , Zhang Qinghui , Wu Chuan , Tan Chenqing , Gao Farun , Guo Ning , Tan Wulin , Zhang Gaige 
Published: February 2022

Abstract
The study area is located in Qaidam Basin on Tibetan Plateau, which has very complex geological background sedimentologically and structurally. Building the discrete fracture network (DFN) of study zone is a critical work step for subsequent dual porosity / dual permeability (Dp/Dp) dynamic simulation which further enables the optimized design of field development plan (FDP).
The saline lacustrine tight oil reservoirs in study zone were severely deformed by the Neotectonism coupling with the far-field collision between the Indian and Eurasian plates. There were relatively abundant fracture interpretations from image well logs with core calibration and relatively amplitude preserving seismic cube. First, statistics of well fractures were performed in terms of their types and attitudes, which enabled proposing their genetic mechanism together with information of other references and dividing fracture sets more reasonably for subsequent DFN modeling. Then, many efforts were made on fracture driver attribute screening with the aid of neural network (NN) and principal component analysis (PCA) functions. Dozens of possible fracture driver attributes were examined, which were mainly geometric attributes, edge-detection attributes, amplitude/frequency related attributes and lithology/porosity related attributes. Meanwhile, microseismic monitoring (MSM) data were also used to help screen the pertinent fracture drivers. Three fracture driver attributes were finally screened out and they were combined together to produce a fracture intensity trend which was finally used as co-kriging secondary variable together with well fracture intensity logs for modeling the 3D-grids of fracture intensity based on gaussian random function simulation algorithm.
Besides the existed fault model (as large-scale fractures) generated when building matrix geomodels, a medium-scale fracture set was built deterministically with "Fault Patch" extraction method based on the seismic edge-detection Ant Cube. Then for small-scale fractures, totally four fracture sets were built stochastically based on split 3D fracture intensity and their own parameters of geometry, orientation, aperture. These five fracture sets were then upscaled to produce the fracture properties with porosity and permeability constraints from wells, i.e., usually less than 0.1% and hundreds of millidarcies respectively. Then these fracture properties were further calibrated and used in Dp/Dp dynamic simulation process.
Genuine discrete fracture network and Dp/Dp dynamic simulation were built up and performed for the first time for the complex oil reservoirs on Tibetan Plateau, based on organic multi-disciplinary integration. But more importantly, many useful conclusions and decisions were reached based on the Dp/Dp dynamic simulation which made the field development plan more robust and cost-effective.
Machine Learning for Sonic Logs Prediction: A Case Study from the Niger Delta Basin in the Gulf of Guinea
Authors: Tahiru Ibrahim Tinni , Olagundoye Olatunbosun , Alabere Abdulquadri Olalekan 
Published: February 2022

Abstract
Sonic logs are very essential for rock type identification, hydrocarbon typing, rock physics modelling, and reservoir characterization. However, they are seldom available due to high costs of acquisition or measurement errors. Empirical formulas and petroelastic models that are often used to predict missing sonic log data may not produce accurate velocity profiles and are limited to specific geologic settings. Using sonic logs from wells in the CONDA field located in the deep offshore Niger delta basin of the Gulf of Guinea, we demonstrate that machine learning algorithms can be used to predict sonic log data if suitable quantitative relationships exists between it and available well logs. Preprocessing such as outlier removal, missing data filling and normalization was applied to the well logs before using them as training datasets for the model prior to applying several machine learning algorithms to build a predictor model for missing DTP and DTS sonic logs. The results of the training using several machine learning algorithms showed that the Gradient Boost Regressor (GBRT) Algorithm was more robust based on higher accuracy and lower root-mean-squared errors (RMSE). Validation of the prediction model at blind wells was quite good, with coefficient of determination or goodness-of-fit (R2) scores of 0.88 to 0.99 and generally low root mean square errors (RMSE). QC of the predictive model performed using qualitative well correlation analysis between a well with actual DTP and DTS sonic logs and another with predicted DTP and DTS sonic logs gave very satisfactory results based on similarities in log character and trend. The results of our study show that in comparison to sonic log prediction using empirical formulas and/or petroelastic models which is fraught with limitations, machine learning can be used as a robust alternative.
Conditioning Distributed Acoustic Sensing Measurements for Borehole Seismic Imaging
Authors: Sayed Ali Yawar , Khaitan Manish Lal , Martinez Alejandro 
Published: February 2022

Abstract
Distributed acoustic sensing (DAS) differs from particle velocity measurements in both amplitude and frequency response. DAS data are affected by the apparent velocity of the incident energy relative to the fiber as well as the gauge-length at which the fiber is interrogated. We develop a generalized relationship for dependence of the DAS amplitude response on the incident elastic waves in terms of the angle of wave vector, angle of polarization, and phase velocity. Velocity and DAS sensor synthetic data are generated to comprehensively evaluate the conditioning methods needed to prepare DAS data for imaging. DAS sensor images, using data-driven and model-driven approaches, are shown to be consistent with the reference velocity sensor image.
A Nonparametric Estimation Method for Acoustic Dispersion and Attenuation Analysis
Authors: Wang Bing , Li Wei 
Published: February 2022

Abstract
Dispersion and attenuation analysis can be used to determine formation anisotropy induced by fractures, or stresses. In this paper, we propose a nonparametric spectrum estimation method to get phase dispersion characteristics and attenuation coefficient. By designing an appropriate vector filter, phase velocity, attenuation coefficient and amplitude can be inverted from the waveform recorded by the receiver array. Performance analysis of this algorithm is compared with EPM and FBMP, based on the analysis, the proposed method is capable of achieving high resolution and precision as the parametric spectrum estimation methods in the meantime, it also keeps high stability as the other nonparametric spectrum estimation methods. At last, applications to synthetic waveforms modeled using finite difference method show its efficiency.
The Numerical Simulation Study on the Dynamic Variation of Residual Oil with Water Drive Velocity in Water Flooding Reservoir
Authors: Sun Zhaobo , Ma Kuiqian , Cai Hui , Gao Yue , Wang Lian , Jiang Ruizhong 
Published: February 2022

Abstract
The results of core displacement experiments show that increasing the water drive velocity when it is bigger than a limit value can effectively reduce the residual oil saturation and improve the oil displacement efficiency under the same PV. Meanwhile oilfield development experience have proved that raising liquid production rate can effectively enhanced oil recovery. However the existing commercial simulators (Eclipse, CMG, et al) cannot simulate the continuous variation of reservoir properties during the simulation process and the oil-displacement mechanism in high-velocity development is not characterized effectively.
In this paper, a new reservoir numerical simulator is established which captures the dynamic variation of residual oil with water drive velocity in water flooding reservoir, based on the black oil model. Capillary number(Ca), defined as dimensionless ratio of viscous force to capillary force, is used to characterize the relationship between water drive velocity and residual oil. Increasing the water drive velocity can improve viscous force to further increase the Ca. When the Ca is larger than a certain critical value (first critical value), larger Ca lead to lower residual oil saturation. until after the number of Ca continues to increase to a certain critical value (second critical value), the residual oil saturation no longer changes with increasing of Ca. A new BG equation is proposed to match the nonlinear relationship between Ca and residual oil. The BG equation is a continuous function, which is very beneficial to the stability of numerical calculation. Higher curve matching is obtained based on the BG equation than the existing models.
The validation results of the new simulator against the commercial simulators showed that good consistence was obtained between the new self-developed numerical simulator and Eclipse. With consideration of the influence of residual oil change in the new self-developed numerical simulator based on BG equation, the results indicate lower remaining oil saturation in the mainstream area and the higher recovery degree of production wells. The history matching of the SZ oilfield in Bohai Bay is achieved with the new simulator, and the history matching accuracy is obviously higher than that of Eclipse. The research results have good theory and application value for water flooding offshore oilfields.
Inclusion of Microporosity in Numerical Simulation of Relative Permeability Curves
Authors: Lanetc Zakhar , Zhuravljov Aleksandr , Shapoval Artur , Armstrong Ryan T. , Mostaghimi Peyman 
Published: February 2022

Abstract
Advances in high-resolution micro computed tomography (micro-CT) allow obtaining high-quality rock images with a resolution of up to a few micrometres. Novel direct numerical simulation methods provide the opportunity to precisely predict the flow properties in the resolved pore space. However, a large fraction of porosity lies below the resolution of modern micro-CT scanners. These, so called, micro-pores may significantly affect the physics of flow in geologically complex dual-porosity heterogeneous formations (carbonates, shales, and coals) and are currently not accounted for in traditional micro-CT based simulations. In this work, we have employed a multiphase multi-scale Darcy-Brinkman approach to simulate immiscible two-phase flow in a hybrid system containing both macro-porous solid-free regions and a micro-porous permeable matrix. This approach solves the Navier-Stokes based volume of fluid equations system in macro-pores and accounts for multiphase Darcy equations in micro-porous regions. By combining available information on micro-porosity with relative permeability curves estimated from the synthetically generated image with both macro- and micro-porous regions fully resolved, we solve the inverse problem to account for micro-porous contribution in our Darcy-Brinkman simulation. This approach allows us to estimate relative-permeability curves in the micro-porous region and correct the multi-scale simulation so it coincides with the data from the fully-resolved image. As a result, we were able to account for the impact of micro-porosity on the residual saturation and correct the shape of relative permeability curves and their end-points in the micro-porous domain. The proposed approach provides a workflow which can be used to history-match the Darcy-Brinkman pore-scale simulation with core-scale petrophysical data with respect to the relative permeability. Thus, it is possible to account for heterogeneity in complex rock formations by incorporating the whole range of porosity. The inclusion of micro-porosity in pore-scale image-based simulations for predicting relative permeability curves may help in a more reliable modelling and estimation of filed-scale subsurface flows, production profiles, recoverable reserves and carbon capture and storage mechanisms.
Enabling Well and Reservoir Surveillance in Dual Water Injectors Through Distributed Fiber-Optic Sensing
Authors: in 't Panhuis Peter , Harthi Zena , Al Hashemi Mohamed , Hemink Gijs , Spivakovska Daria 
Published: February 2022

Abstract
Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS) are novel surveillance technologies which are increasingly being used for in-well surveillance, including in injector wells. Some of the applications include injection profiling, acid-stimulation optimization, well-integrity monitoring, and fracturing diagnostics. Our goal here is to demonstrate how this can be applied to a particular type of water injectors that use dual injection lines to improve conformance by decomingling the injection between shallow and deeper reservoir targets. Specifically, annulus injection will be used to target the shallow reservoirs and tubing injection to target the deeper reservoirs.
Several case studies will be presented from water injectors located in the South of the Sultanate of Oman. This required integrated evaluation combining data from surface meters, downhole gauges, open-hole formation evaluation, as well as DAS and DTS. It will be shown how the data was analyzed to assess the efficiency of the waterflood, to optimize the water injection operating envelope, to identify fracture initiation or plugging, but also to analyze the effectiveness of the well and completion design.
Through its high sample rate and narrow spatial resolution, DAS is particularly effective at monitoring changes to injectivity in real-time. This is especially helpful for identifying the onset of fracture initiation and monitoring the growth in fracture height, which is difficult to achieve with other technologies. DTS warm-back analysis was also performed to complement the DAS interpretation and monitor changes in conformance with a deeper depth of investigation than DAS.
The unique value of the fiber-optic sensing technology is that it enables the implementation of the dual annulus-tubing injection completion design without limiting surveillance capabilities, as conventional surveillance in this well design is either impractical, not feasible, or too costly.
Foam Cementing Technology: Addressing a Lost-Circulation Issue in the East Siberia Region
Authors: Tcibulskii Mikhail , Trofimenko Ivan , Yagudin Marat , Lodin Alexey , Khohryakov Vladimir 
Published: February 2022

Abstract
Lost circulation (LC) is commonly encountered in drilling and cementing operations and can significantly contribute to non-productive time (NPT). An operator in the Kyumbinskoe Field faced this challenge in a fractured production section of the formation, and conventional LC solutions had been ineffective at achieving strict regulatory top of cement (TOC) requirements and satisfactory cement bonding. This paper describes the experience of utilizing foam cementing technology as a primary solution to solve a lost circulation issue on the project. For this project a foam cementing solution was designed to meet operational parameters for cementing a production casing in one stage (multi-stage tool was eliminated).
Use of foam cementing technology helped to minimize losses experienced in all cementing operations previously on this project. CBL results were also improved. All Customer requirements were met: Planned Top Of Cement (TOC)Minimum losses during cementing operationsRig time savingImproving CBL results.
First Smart Liner Mono-Bore Completion in Giant Carbonate Reservoir in Abu Dhabi Provides New Opportunities for Tight Reservoirs Development
Authors: Barragan Ernesto , Jimenez Alvaro , Ramarao Subba , Mogensen Kristian , Albarracin Ruben , Quintero Fernando 
Published: February 2022

Abstract
One of the main challenges in the oil industry is to develop tighter carbonate reservoirs. There are several methods to improve oil recovery (IOR), the adoption of Novel Lower Completions in horizontal wells can be one of the best tools to maximize reservoir contact and to control unwanted fluids (i.e., water or gas). It is especially important in carbonate reservoirs where most of the time it is imperative to provide additional stimulation in order to produce the reservoirs economically. The main objective of the presented work is to provide an alternative type of completion that creates better flow and stimulation distribution along the horizontal hole, In addition, the movable parts were eliminated to reduce the integrity risk while injecting the acid job stimulation.
In carbonate reservoirs, the standard method to improve reservoir permeability is through acid stimulation utilizing coiled tubing to place acid into the reservoir rock and improve the flow within the near wellbore area. This technique is costly and time consuming. Furthermore, in the specific case presented, there is the constraint of limited number of coiled tubing units where many times acid stimulation is delayed due to this fact. Installing the mono-bore segmented completion provides the capability to perform the job without the rig, only bull heading the acid utilizing high pressure pumps.
There are several options to install lower completions in the oil industry for horizontal wells. Smart liner is presented as an alternative to the conventional pre-perforated liner. The smart liner design was done with a proprietary software and consists of a specific number of small holes distributed along the horizontal section to distribute the flow and provide better stimulation placement at higher rates improving "worm holes" creation and extension. The lower completion is equipped with swellable packers to provide segmentation in the horizontal hole for future requirements if needed such as zones shut off. After the successful installation in a water injection well, water injection was initiated to define a baseline to compare with the results after the acid stimulation. The paper presents the lower completion design, the acid stimulation program and the results before and after the stimulation is done without rig on site. Initial results after the stimulation are showing more than twice the injection rate after the job. This job was done without the use of coiled tubing providing a better acid stimulation along the horizontal hole.
The 4-½ inches mono-bore completion is the first time that was done in the Asset, creating new opportunities to improve the stimulation and injectivity / productivity of the wells and consequent future Field development.
Uplifting the Productivity of a Mature Gas Giant in Pakistan Using Integrated Asset Modelling
Authors: Ahmed Sheraz , Muhammad Waqas Ghulam , Sheikh Hafiz Mustafa Ud Din 
Published: February 2022

Abstract
It's almost certain that the oil & gas industry has passed its plateau for large field discoveries. This places an extra burden on the efficient handling of our mature assets, as reasonable amount of hydrocarbons still exist in such reservoirs. However, the ever-increasing cost of new projects and low production gains hardly justify the economics. This study presents a novel approach applied on a mature gas giant, in order to revitalize old wells, optimize surface network and exploit the scattered sweet spots still prevailing in the field, with integrated surface and subsurface engineering strategies.
The field under study has been producing since 1955, with around 112 wells, completed in four independent formations. The primary reservoir (Reservoir-A) is categorized as a depletion-drive gas reservoir and has been on production since the field's inception; the reservoir pressure has depleted from 1,900psi to 300psi. The other formations: Reservoir B, C & D started producing from 1968, 2000 and 2015 respectively. At its peak, the field produced ∼1,000 MMScfd gas; but lately, the production decline rose to around 7-8% annually, mainly due to natural depletion. However, deterioration in well performances and limitations of surface facilities (feederlines, Gas-Gathering-Mains (GGMs) and compressors) have also exacerbated this decline, due to the additional pressure drops amassed in their dynamics with reservoir pressure depletion & water production.
To counter the field's rapid decline, a comprehensive workflow and an Integrated Asset model was developed, with an absolute focus on the NPV for each development. At the subsurface level, Reservoir-B (still under-developed) was the first targeted, as most of its wells were producing at uneconomical rates. An ant-tracking algorithm was run on the newly acquired 3D-seismic; and natural fractures - near the 02 high producers in Reservoir-B, were analyzed. A workflow was then developed to target similar fractures and the integrated impact, on surface facilities, was evaluated. Finally, three successful pilots were drilled in Reservoir-B and Reservoir-C, to evaluate the post-drill dynamics. Based on the real-time performances of these pilots with existing producers and surface facilities, the integrated field model was updated, coupling the wells, surface facilities and all four reservoirs (with independent reservoir models). As a result of this integrated model, 12 more wells, 09 workovers, 02 GGM optimizations and 03 compressor modification jobs were finalized; giving an overall increase in EUR by 800 BCF, while the NPV of the field increased by 131 $MM.
This study offers an innovative approach that has been followed to utilize each data-set systematically, in order to re-vitalize a field even after 84% depletion. The paper also describes the evaluation process for all the optimization opportunities and their impact on the NPVs, to reap the maximum reward from such an old field.