bluuebunny/crossref_metadata_2025_split huggingface dataset:
Changing the Game in Mature Field Development by Means of Advance Pulsed Neutron Logging as a One-Stop-Shop Solution for Formation Evaluation Behind Casing
Authors: Tanjung Heri , Cavalleri Chiara , Sianturi Julfree , Suwito Edy , Yasa I Made Agus , Rushatmanto Moch , Karana Anang , Suardiputra Aditya , Hardita Dimas , Wijaya Geraldie Lukman , Manalu Dasa , Sinaga Humisar Alprialdus , Lodiman William , Dewanda Ratna , Payung Amos 
Published: January 2023

Abstract
Nowadays, the stakes of operating hydrocarbon producing wells in mature field are getting higher. Advanced technologies are needed, and the industry must improve the cost efficiency of maturing assets to compensate for declining production and high fixed costs. One of the methods developed for efficient operation in producing hydrocarbon in mature field is one-phase-well (OPW), which is a well architecture without 9-5/8" surface casing. For safety reason, the conventional pressure temperature fluid analysis (PT-FA) logging can no longer be performed in OPW; alternative approaches are required to determine the potential of reservoirs. Pulsed neutron log (PNL) is proposed as a one-stop-shop solution to determine main reservoir characteristics and fluid status in anticipation of future OPW implementation. Latest generation PNL technology utilizes high-counting neutron generator coupled to high-resolution nuclear detectors to measure accurate oil and gas saturation by means of carbon/oxygen ratio (COR), in-situ total organic carbon, sigma, neutron porosity and novel fast neutron cross section (FNXS) measurements, while simultaneously providing accurate lithology volumes and porosity by means of advanced elemental spectroscopy combined with cased-hole porosity (TPHI).
To evaluate the robustness and applicability of the method, the latest generation PNL was run in three recently drilled wells which have complete open-hole (OH) logs dataset along with fluid analysis (FA) and mudlog information. The PNL data were processed and interpreted independently, without utilizing any input from the OH log data and without the support of fluid analysis and mudlog information. A criterion based on comparison and correlation between fluid volumes and saturation defined by the PNL and the fluid analysis from FA was defined. For all the wells, the PNL interpretation results matched the hydrocarbon information from FA with success ratio higher than 90 percent over the logged interval, confirming its ability to perform accurate standalone evaluation and its value as alternative technology for effective fluid analysis. Because of the complexity of the system, conditions and potential risks must be properly analyzed case-by-case to encourage more massive application in the future.
A Numerical Study of Mineral Dissolution in Deep Heterogeneous Carbonate Reservoirs: Implications for CO2 Geo-sequestration
Authors: Fathy Ahmed , Arif Muhammad , Adila Ahmed Sami , Raza Arshad , Mahmoud Mohamed 
Published: January 2023

Abstract
CO2 geo-sequestration has shown potential to mitigate global warming caused by anthropogenic CO2 emissions. In this context, CO2 can be immobilized in subsurface formations due to chemical dissolution/precipitation via mineral trapping. However, long-term mineralization involves interdependent complexity of dissolution and precipitation kinetics. In this study, a numerical approach is developed and implemented to analyze the effect of rock type, reservoir temperature, brine salinity on CO2 mineral trapping in compositionally distinct subsurface carbonate reservoirs.
Here, we simulated field-scale models for three different subsurface reservoirs’ compositions (calcite, dolomite, and siderite) to assess the mineral trapping capacity. The base case of a 3D carbonate formation was created. The petrophysical parameters were then upscaled (Sw, Sg, K, and φ) to capture the subsurface conditions. Subsequently, CO2 mineral trapping capacity was computed for different rock compositions mimicking carbonate/brine/CO2 systems. Moreover, the CO2 geo-storage potential was assessed under reservoir temperature, salinity, storage duration, and cumulative injected CO2.
The effect of reservoir mineralogy was analyzed via the amount of CO2 mineralized within 100 years of storage duration following 2 years of injection as a base case. The results revealed significant variation in storage capacity as the mineral type changed. In particular, 100% calcite surface showed the highest CO2 storage capacity compared to both dolomite and siderite. The results could be attributed to the distinction of each mineral in terms of its relative cations dissolve-out rate. Moreover, increasing the reservoir temperature resulted in a monotonic increase in mineralization potential with an insignificant increase in case of siderite. Notably, calcite outperformed both siderite and dolomite as a preferable medium for CO2 mineralization as the injection duration increased over both 100 and 200 years of storage. Additionally, the increase in salinity either significantly decreased the amount of CO2 mineralized in case of calcite and siderite or showed no effect at all in case of dolomite.
This work provides a new insight for underpinning the effects of carbonate reservoir composition on CO2 mineral trapping capacity which has not been investigated much. Overall, the results showed that CO2 trapping in subsurface carbonates immobilized CO2 for a long-term stable geo-storage.
CCUS Numerical Simulation Technology and its Application in a Carbonate Reservoir of the Middle East
Authors: Li Qiaoyun , Wu Shuhong , Jia Han , Wang Baohua , Deng Xili , Li Hua , Fan Tianyi , Xu Mingyuan 
Published: January 2023

Abstract
Carbon dioxide Utilization and storage technology (CCUS) plays an important role for oil and gas field to further improve oil and gas recovery and achieve the goal of "double carbon" in recent years. Numerical simulation is an essential means for reservoir engineers to study the flow mechanism of CO2 flooding and storage, screen the CCUS technical indicators, predict the enhanced oil recovery and evaluate storage potential. This paper discusses the multiphase and multicomponent mathematical model based on the seepage theory of carbon dioxide flooding and storage, the calculation method of gas-liquid equilibrium based on EOS equation, the miscibility determination technique and two phase P-T flash calculation method. Meanwhile the CCUS numerical simulator developed based on above theoretical model and calculation method. Applying the simulator to CO2 miscible flooding in a carbonate reservoir of the Middle East, the results show that the model and software accurately describes the CO2-EOR seepage mechanism and CO2 miscible displacement process. It effectively predicts the effect of CO2 injection on EOR and the storage potential after CO2 flooding. It can provide feasible technical guidance for the optimization of CO2 utilization and storage programs.
An Efficient Simulation Approach for Long-term Assessment of CO2 Storage in Complex Geological Formations
Authors: Zhang Ziliang , Wang Yuhang , Vuik Cornelis , Hajibeygi Hadi 
Published: January 2023

Abstract
We present an efficient compositional framework for simulation of CO2 storage in saline aquifers with complex geological geometries during a lifelong injection and migration process. To improve the computation efficiency, the general framework considers the essential hydrodynamic physics, including hysteresis, dissolution and capillarity, by means of parameterized space. The parameterization method translates physical models into parameterized spaces during an offline stage before simulation starts. Among them, the hysteresis behavior of constitutive relations is captured by the surfaces created from bounding and scanning curves, on which relative permeability and capillarity pressure are determined directly with a pair of saturation and turning point values. The new development also allows for simulation of realistic reservoir models with complex geological features. The numerical framework is validated by comparing simulation results obtained from the Cartesian-box and the converted corner-point grids of the same geometry, and it is applied to a field-scale reservoir eventually. For the benchmark problem, the CO2 is injected into a layered formation. Key processes such as accumulation of CO2 under capillarity barriers, gas breakthrough and dissolution, are well captured and agree with the results reported in literature. The roles of various physical effects and their interactions in CO2 trapping are investigated in a realistic reservoir model using the corner-point grid. It is found that dissolution of CO2 in brine occurs when CO2 and brine are in contact. The effect of residual saturation and hysteresis behavior can be captured by the proposed scanning curve surface in a robust way. The existence of capillarity causes less sharp CO2-brine interfaces by enhancing the imbibition of the brine behind the CO2 plume, which also increases the residual trapping. Moreover, the time-dependent characteristics of the trapping amount reveals the different time scales on which various trapping mechanisms (dissolution and residual) operate and the interplay. The novelty of the development is that essential physics for CO2 trapping are considered by the means of parameterized space. As it is implemented on corner-point grid geometries, it casts a promising approach to predict the migration of CO2 plume, and to assess the amount of CO2 trapped by different trapping mechanisms in realistic field-scale reservoirs.
Novel Completion and Stimulation Technologies from Planning to Execution Tripled the Injectivity Index for the First Water Injectors in a Giant Tight Carbonate Reservoir, Onshore Abu Dhabi
Authors: Farnetano Ruben P. , Daoud Ahmed M. , Mogensen Kristian , Fawzy Ahmed , Alnuaimi Eiman , Al Sereidi Bothainah 
Published: January 2023

Abstract
Unit R is a tight carbonate reservoir onshore Abu Dhabi currently undergoing redevelopment with the aim to substantially improve the ultimate recovery factor. Better pressure support is required to increase the production. To this end, two water injectors were drilled in tight areas where wells suffer from low injectivity index and high well head injection pressure (WHIP). Reaching the expected injection rates therefore required very aggressive matrix-acid stimulation techniques.
Acid wash is a common stimulation practice for medium-high permeability wells in ADNOC when the purpose is merely to remove drilling damage without creating large negative skins. For low permeability reservoirs such as Unit R, more aggressive stimulation techniques are needed to deliver the expected production and injection target rates. We tested two such methods; Well A1 was treated using Abrasive Jetting (JA), which is conveyed by coiled tubing whereas in Well A2, we deployed a Smart Liner (SL) where acid can be bullheaded at high rate from surface.
In Well A1, the Abrasive Jet CTU in Open Hole doubled the injectivity index. However, the Injection Logging Test (ILT) revealed an uneven injection profile along the horizontal section (more injection in the better properties zone).
In well A2, Smart Liner bull-head acid stimulation was able to triple the injectivity index. The ILT shown an even injection profile across the horizontal section, actually slightly more in areas with poor rock properties due to a large number of holes in those intervals.
The cost of the Abrasive Jet is 40% less than the Smart Liner stimulation but the latter has more medium/long term advantages:
Even injection along horizontal section (improving sweep efficiency) Ensure 100% accessibility to the well (avoiding formation collapse issue) Stimulation from surface, no need CTU (saving cost), useful for potential future re-stimulations.
After only 10 months of injection the reservoir pressure has increased 50-100 psi in surrounding nearby oil producers, resulting in 20% more oil while honoring all operational guidelines.
It is quite exceptional to be able to assess with real data the effectiveness of two different stimulation techniques. The two pilot wells have same horizontal length, almost same rock properties, and are drilled parallel to each other.
Both Smart Liner and abrasive jetting substantially improve water injectivity but the more uniform flow profile observed in the Smart Liner is a distinct advantage when selecting an appropriate completion-stimulation design for future water injectors.
A Characterization of Tight Sandstone: Effect of Clay Mineralogy on Pore-Framework
Authors: AlKharraa Hamad Salman , Wolf Karl-Heinz A. A. , Kwak Hyung T. , Deshenenkov Ivan S. , AlDuhailan Mohammed A. , Mahmoud Mohamed A. , Arifi Suliman A. , AlQahtani Naif B. , AlQuraishi Abdulrahman A. , Zitha Pacelli L. J. 
Published: January 2023

Abstract
Macro-, meso-, micro-pore systems combined with clay content are critical for fluid flow behavior in tight sandstone formations. This study investigates the impact of clay mineralogy on pore systems in tight rocks. Three outcrop samples were selected based on their comparative petrophysical parameters (Bandera, Kentucky, and Scioto). Our experiments carried out to study the impact of clay content on micro-pore systems in tight sandstone reservoirs involve the following techniques: Routine core analysis (RCA), to estimate the main petrophysical parameters such as porosity and permeability, X-ray diffraction (XRD), and scanning electron microscopy (SEM) to assess mineralogy and elemental composition, Mercury Injection Capillary Pressure (MICP), Nuclear Magnetic Resonance (NMR), and Micro-Computed Tomography (Micro-CT) to analyze pore size distributions. Clay structure results show the presence of booklets of kaolinite and platelets to filamentous shapes of illite. The Scioto sample exhibits a micro-pore system with an average pore body size of 12.6±0.6 μm and an average pore throat size of 0.25±0.19 μm. In Bandera and Kentucky samples illite shows pore-bridging clay filling with an average mineral size of around 0.25±0.03 μm, which reduces the micro-pore throat system sizes. In addition, pore-filling kaolinite minerals with a diameter of 5.1±0.21 μm, also reduce the micro-pore body sizes. This study qualifies and quantifies the relationship of clay content with primary petrophysical properties of three tight sandstones. The results help to advance procedures for planning oil recovery and CO2 sequestration in tight sandstone reservoirs.
Developing a Generalized Correlation to Obtain Steady-State Based Permeability Using a Probe Permeameter
Authors: Abdullah Eassa , Baatiyah Mobarak , Aljabri Jaber , Alfaraj Mashaer , Al-Otaibi Mohammed , ElHusseiny Ammar , Alade Olalekan 
Published: January 2023

Abstract
The importance of permeability cannot be under-stimated. It is used in crucial equations used to determine quantities analysed by reservoir, drilling, and production engineers. Using permeability along with other properties is important to understanding reservoir behaviour when wells are drilled, to calculate the rate of the fluid flow, as illustrated by Darcy's equation that relates fluid flow to permeability. Measuring permeability in the laboratory with the conventioanl available steady-state equipment can be time consuming, especially if it was done by gas injection which requires measuring at different pressure points to satisfy Klinkenberg equation. A quick measuring equipment called the prob permeameter have been used for many years, it quantitatively performs a permeability point measurement as a function of position on either a whole core, slabbed core or a rock slab. However, despite of its prompt and easy measurement, most of the results represents a general idea about the actual permeability and sometimes even falls out of the range, which makes it unrelaiable. Series of experiments were conducted for a variety of rock samples with a wide range of permeability ranging from tight to permeable, to compare the generated results between both of the above equipment. The results were graphed and been compared using different point of views, mathematicalwise, petroleum engineeringwise, and geologicalwise. Ultimately, an equation to correlate between the results was developed graphically and using logistic regression techniques.
Accounting for Regional Aquifer Data in a Simulation Model of the Burgan Minagish Reservoir – A New Approach
Authors: Al-Faresi Fahad , Monfared Hashem , Evro Solomon , Ali Sher , Madhavan Sethu , Yaser Muhammad , Yunusov Manuchehr 
Published: January 2023

Abstract
Burgan Minagish (BGMN) reservoir in the Greater Burgan field, is one of the reservoirs among others that has been producing from Minagish formation. It has been in production intermittently since 1960's though full development was delayed due to high H2S content and the need to construct sour processing surface facilities.
The analysis of reservoir pressure over time indicated that the main reason of reservoir pressure decline in BGMN was production from three neighboring reservoirs producing from the same formation. This was clear as pressure decline continued for the period of 2005-2009 while Burgan-Minagish was not in production. Reservoir pressure dropped below bubble point in 2011 and made it necessary to design and implement a pressure maintenance program. This included a water injection scheme which has been implemented since 2018.
In 2012, using a novel approach (Al-Faresi et al, 2012), two Fast and Slow Loop simulation models were built to model a regional aquifer and quantify flux exchange between Burgan-Minagish, regional aquifer and surrounding reservoirs. While the Fast Loop coarse model was used to match field level production and pressure data, the detailed BGMN Slow Loop model would solely focus on modeling of BGMN having incorporated the impact of neighboring reservoirs via calculated flux derived from Fast Loop model. The drawback, however, is that every time the model needs updating, a tedious and manual process must be performed to calculate flux rate across the BGMN boundaries from the Fast Loop and then incorporate it explicitly into the Slow Loop model.
10 years after the previous study, a new approach for regional aquifer modeling has been utilized to integrate two existing simulation models in a combined one that serves for both purpose of modeling the regional aquifer and surrounding reservoirs as well as history matching of high resolution BGMN model. The history matched combined model has been used to extensively evaluate BGMN reservoir production performance under different development scenarios. We have compared the results with existing two-model solution, and it is clear from the analysis that the impact of neighboring reservoirs as well as the regional aquifer is captured in the new approach.
The novelty of the new approach is that it allows a seamless interaction between three surrounding reservoirs with BGMN. The unified simulation model is more convenient to use and eliminates the manual work of influx calculations. It is also more flexible and repeatable as systematic updates on both static and dynamic modeling sides for any reservoir in the area of interest could be easily implemented.
A Hybrid Neural Workflow for Optimal Water-Alternating-Gas Flooding
Authors: Singh Gurpreet , Davudov Davud , Al-Shalabi Emad W. , Malkov Anton , Venkatraman Ashwin , Mansour Ahmed , Abdul-Rahman Rosemawati , Das Barun 
Published: January 2023

Abstract
Water-alternating-gas (WAG) injection is a gas-based enhanced oil recovery (EOR) technique used to overcome problems related with gas injection including gravity override, viscous fingering, and channeling. The WAG EOR technique is used to control gas mobility, which boosts project economics. Water alternating gas (WAG) has the dual benefit of higher recovery than continuous gas injection and CO2 sequestration. Higher sweep efficiencies and conformance control have been shown to increase the life cycle net present value (NPV) for improved field development and deployment planning. Nevertheless, a poor WAG design often results in unfavorable oil recovery. This study investigates WAG optimization in a sandstone field using a hybrid numerical-machine learning (ML) model. In this work, we present a hybrid neural approach for optimizing the WAG injection process that can be easily integrated as a workflow with any existing reservoir simulator for optimal WAG parameters to maximize reservoir life cycle cumulative recoveries.
The reservoir simulator is treated as a sample generator to form an ensemble of recovery scenarios with the WAG parameters as inputs to a dense neural network (DNN) and outputs/labels as cumulative recoveries. The neural network then serves two roles: 1) a readily available map between WAG parameters and cumulative recoveries for reduced computational cost and hence faster on-demand evaluation, and 2) as a repository condensing important correlations that can be appended with additional samples or reduced by removing redundant samples (simulation runs). Consequently, the hybrid neural approach also provides a clear picture of which simulation runs (or samples) are more conducive to optimal recovery predictions for an effective strategy to sample the high dimensional WAG parameter space and reduced compute times. This becomes especially important when we consider field scale optimization scenarios with multiple wells each with their separate injection schedules requiring exponentially increasing samples with a brute force ensemble approach (add an example in the introduction section or later and cross-refer here).