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Rezaeyan, Amirsaman (Heriot-Watt University, the Lyell Centre, Research Avenue South, Edinburgh, UK) | Seemann, Timo (RWTH Aachen University, Clay and Interface Mineralogy, Aachen, Germany) | Bertier, Pieter (RWTH Aachen University, Clay and Interface Mineralogy, Aachen, Germany) | Pipich, Vitaliy (Forschungszentrum Jülich GmbH, Jülich Centre for Neutron Science at Heinz Maier-Leibnitz Zentrum, Garching, Germany) | Leu, Leon (Imperial College London, Department of Earth Science and Engineering, London, UK) | Kampman, Niko (Shell Global Solutions International B.V., Amsterdam, the Netherlands) | Feoktystov, Artem (Forschungszentrum Jülich GmbH, Jülich Centre for Neutron Science, at Heinz Maier-Leibnitz Zentrum, Garching, Germany) | Barnsley, Lester (Forschungszentrum Jülich GmbH, Jülich Centre for Neutron Science, at Heinz Maier-Leibnitz Zentrum, Garching, Germany) | Busch, Andreas (Heriot-Watt University, the Lyell Centre, Research Avenue South, Edinburgh, UK)
To quantitatively analyse the pore structure at a broad pore scale range (~ 2 nm to ~ 2 μm), low pressure sorption (LPS) and small angle neutron scattering (SANS) were conducted on several mudrocks originating from radioactive waste storage sites, hydrocarbon seals and shale gas reservoirs across the globe. These include Opalinus Clay, Switzerland, Posidonia Shale, Germany, and Carmel Claystone, Bossier Shale, and Eagle Ford Shale, USA. Furthermore, upon injection of supercritical fluids (deuterated methane, CD4) into the pore space of mudrocks, the phase behaviour depending on pore size was investigated with subsequent neutron scattering. The results have revealed a vast heterogeneity, which can be related to the high clay contents. Due to the high clay contents, pores smaller than 10 nm constitute a large fraction of total porosity (25-30 %) and up to 80 % of specific surface area (SSA). Moreover, total porosity and SSA are not significantly affected by thermal maturation. However, thermal maturity contributes to different pore size distribution (PSD) related to meso- and macro-pores. Thermal maturation is likely to develop porosity at macroscale range, which can enhance the permeability for continuum flow in organic rich mudrocks. Results obtained from supercritical fluid sorption within SANS experiments demonstrated the formation of an adsorbed phase characterised by a higher density than predicted for the bulk fluid by the equation of state. The effect of sorbed phase is pore size dependent. It implies that the density as well as the volume fraction of the adsorbed phase are influenced by the pore structure; sorbed phase tends to fill small pores, followed by progressively filling larger pores. Mineralogy and maturity interplays contribute to a pore network of few-to-several nano-Darcy permeability in which pore size dependent transport mechanisms can vary from diffusional transport in small pores to slip flow in progressively larger pores. In order to improve pore network models, the incorporation of SANS PSD as well as pore size dependent sorption are important to more realistically understand storage capacity and/or transport phenomena in mudrocks.
Li, Yang (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Yang, Zhaozhong (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Li, Xiaogang (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Jia, Min (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University)
Injection of carbon dioxide (CO2) into coal layers can be a viable strategy for underground CO2 sequestration and enhanced gas recovery (CS-ECBM) in coalbed methane (CBM) reservoirs. Although the CS-ECBM technique have been drawn to research attentions, the microscopic competitive adsorption mechanism of methane (CH4) and CO2 remains to be determined. A better understanding of CO2/CH4 competitive adsorption behaviors in coal systems can help provide useful guidelines for the design of the CS-ECBM project.
In this work, the simulation model was established by low-rank coal (LRC) matrix, which was built by coal realistic molecular model. Then the slit-shaped pore was built by a width of ∼20 Å was constructed by two LRC matrices. The adsorption and diffusion properties of CH4 and CO2 in the LRC slit nanopore were investigated through grand canonical Monte Carlo (GCMC) simulation. The affinity between adsorbates and atoms in the LRC surface was analyzed by computing the radial distribution function (RDF). At last, the molecular dynamics (MD) simulation method was used to explore the displacement efficiency of the adsorbed CH4 displaced by CO2 in LRC slit nanopore at the subsurface condition.
Through simulation, the adsorption capacity, adsorption selectivity and displacement efficiency of CO2 and CH4 were discussed to elaborate the competitive adsorption behavior of CO2 over CH4 in LRC slit nanopore. It was found that gas molecules adsorbed in LRC slit nanopore can be divided into three parts: Np-matrix, Np-surface and Np-central parts. The adsorption density distribution and the mean squared displacement (MSD) of CH4 and CO2 in LRC slit nanopore indicated that gas molecules can adsorb more steadily in the matrix of the nanopore than other parts. The RDF results showed that between adsorbates and atoms in the LRC surface, CO2 had high affinity with the oxygen-containing groups. By analyzing the micro-behaviors of the adsorbed CH4 displaced by CO2 in LRC slit nanopores, it was found that the displacement efficiency was enhanced with the enlarged bulk pressures, accompanied by the sequestration amount of CO2 in LRC slit nanopore during the displacement process.
Our findings and related analyses attempt to provide useful guidance for enhancing CBM extraction by injecting CO2 and can shed light on the details of transport and storage processes at the atomistic level. The methods proposed in this work can assist the future design in the CS-ECBM engineering and the development of shale gas reservoirs.
Li, Ying (Southwest Petroleum University) | Liu, Feihang (Southwest Petroleum University) | Li, Haitao (Southwest Petroleum University) | Chen, Shengnan (University of Calgary) | Zeng, Jie (The University of Western Australia) | Zhang, Jianfeng (Sinopec Northwest Oil and Gas Company) | Meng, Xiangqing (Shengli Southwest Branch) | Jiang, Shikai (Sichuan Gem Machinery Special Vehicleco. LTD)
Dynamic capillary pressure affects the non-equilibrium multiphase flow behavior in porous media. Fractures has been shown to influence the dynamic capillary pressure in tight rocks, but the role of fractures on the dynamic capillary pressure during the production process in tight sandstone reservoirs remains uncovered. This work examines and simulates the dynamic displacement process in fractured tight sandstone oil reservoirs. The dynamic capillary pressure, the dynamic coefficient and the dynamic relative permeability are measured through specially designed experiments to show the effects of fractures on the dynamic fluid flow process. The experimental data are then used to simulate the reservoirs production process applying the CMG. Results have shown that the dynamic capillary pressures of the fractured samples are 5-15% higher than the intact ones. The dynamic effect is weakened by the fractures indicated by the lower values of dynamic capillarity coefficient in the fractured core samples. Dynamic relative permeability curves are higher than the steady ones at low water saturation, and lower than the steady ones at high water saturation. The production rate of the reservoir is overestimated if dynamic effect is ignored in fractured tight sandstone reservoirs, and the production well will be predicted to breakthrough earlier, with a higher breakthrough water flow. This paper helps to understand the multiphase flow behavior and simulate the oil recovery process in fractured tight sandstone reservoirs.
Wu, Zhongwei (College of Petroleum Engineering, China University of Petroleum, East China & School of Mining and Petroleum, Department of Civil and Environmental Engineering, University of Alberta) | Cui, Chuanzhi (College of Petroleum Engineering, China University of Petroleum, East China) | Cheng, Xiangzhi (Petrochina Research Institute of Petroleum Exploration & Development, Department of Logging & Remote Sensing Technology) | Wang, Zhen (College of Petroleum Engineering, China University of Petroleum, East China) | Sui, Yingfei (College of Petroleum Engineering, China University of Petroleum, East China) | Zhao, Xiaoyan (China University of Petroleum, East China)
The tight reservoir and fracture are stress sensitivity medium, and the flow in tight reservoirs obeys the low-velocity non-Darcy flow. Currently, few studies of pressure analysis for volume fracturing well are conducted with simultaneously considering low-velocity non-Darcy flow and stress sensitivity.
In this paper, the dynamic threshold pressure gradient and permeability modulus are respectively utilized to characterize the low-velocity non-Darcy flow and permeability stress sensitivity. And then the model of volume fracturing well in tight reservoirs simultaneously considering low-velocity non-Darcy flow and stress sensitivity is built. After that the finite difference method is used to solve it and the proposed model is verified by comparing the result of this proposed model with that of the commercial software. Finally, the effect related parameters on the dimensionless pressure and pressure derivative are analyzed.
The six flow regimes are identified by the dimensionless pressure and pressure derivative curve. They are fracture linear flow regime, early transition flow regime, radial flow regime, cross flow regime, advanced transition flow regime and boundary controlling flow regime, respectively. The reservoir stress sensitivity and dynamic threshold pressure gradient have a great effect on the dimensionless pressure and pressure derivative curves. With the increase of reservoir stress sensitivity, the dimensionless pressure and pressure derivative move upward at the advanced transition flow and boundary controlling flow stages. The decrease of fluid viscosity results in an increase of the dynamic threshold pressure gradient. The increase of reservoir permeability corresponds to an increase of dynamic threshold pressure gradient and that results in the curves of dimensionless pressure and pressure derivative moving downward. The fracture stress sensitivity has a tiny effect on dimensionless pressure and pressure derivative and can be ignored when the flow rate is small.
This work reveals the effect of dynamic threshold pressure gradient and permeability stress sensitivity on pressure, and provides a more accurate reference for reservoir engineers in pressure analysis when developing tight reservoir by using volume fracturing well.
Sheng, Mao (State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing) | Khan, Waleed Ali (National and Local Joint Engineering Research Canter of Shale Gas Exploration and Development) | Cheng, Shizong (China University of Petroleum-Beijing) | Zhang, Panpan (China University of Petroleum-Beijing) | Tian, Shouceng (China University of Petroleum-Beijing) | Xu, Quan (State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum-Beijing)
Evaluation of organic-rich shale and its cracking mechanism through acidizing attracts much attention as a result of advancements in deep exploration of unconventional reservoirs. In this paper mineral dislodgment and mineral cracking phenomenon were explained by combined experimental methods including atomic force microscopy (AFM), inductively coupled plasma mass spectrometry (ICP-OES), XRD, XRF, Ion chromatography and SEM-EDS to characterize microstructure of individual minerals for pre and post acidizing test samples. Two types of core samples from Longmaxi marine and Yanchang continental shale formations were emphasized for acidizing behaviors by employing hydrochloric acid (15%+ 3%KCL) as the acid fluid medium to treat shale samples for 240 minutes. Moreover, the mechanical mapping was conducted via AFM to identify the variation of mechanical properties of the targeted minerals. Porosity and microfractures were generated due to compression caused by mineral grain displacement mostly on the areas dominated by carbonate minerals for Longmaxi marine formation carbonates and non-swelling clay minerals (Kaolinite, Chlorite), thus contributing in generation of secondary pores. Inter-particle and Intra-particle pores are greatly enchanted as a result of acidizing in carbonate regions of Longmaxi marine shale formation. Yanchang continental shale is mostly dominated by intra-particle pores that effect greatly in the generation of overall porosity enhancement in shale. However Clay mineral swelling was restricted as presence of non-reactive minerals near the clay causes hindrance due to dissolution effect after post acidizing treatment. Secondly during reaction some heavy ions such as iron or potassium may precipitate out and gets deposited on clay minerals. This phenomenon increases the mechanical strength as clay is easily deformed considering its low elasticity and weaker poisson ratio. Acid dissolution cracks are generated as a result of mineral dissolution of carbonate and iron-oxide regions. Acid induced cracks are also generated as a result of mineral grain displacement due to creation of void spaces that are generated due to mineral dissolution. Due to reaction some of the ions get deposited on the shale surface while some ions are dislodged and get immersed in the acid solution. The different ions formed on surface of shale and in the acid solution were closely monitored as these ions are the driving factors for the generation of micro-cracks and porosity enhancement on shale sample. This paper would help to understand the creation of microfractures and pores in a more efficient and detailed way.
In early 2016 the Oklahoma Corporation Commission (OCC), the state regulator for oil and gas wells in Oklahoma, observed anomalous seismicity near oil and gas wells with active hydraulic fracturing operations. In response to well completion-associated seismicity, the OCC in the summer of 2016 implemented mandatory submission of Hydraulic Fracturing Notices ("Frac Notices"), and followed with a series of seismicity protocols related to well completions beginning in 2016, that were further refined through 2018. In near real-time, the OCC cross-references Frac Notices with seismic events in the Oklahoma Geological Society (OGS) seismic network to create a catalog of well completions and potentially associated seismicity, the "Frac Notice – Seismicity Match Catalog." In this paper, we review the Catalog for a time period between October 25, 2016 and August 6, 2019 and present the amount, location and rate of seismicity associated with hydraulic fracturing in the State of Oklahoma. To be included in the OCC's Frac Notice – Seismicity Match Catalog, an earthquake must have occurred within 5 kilometers of a well and between the start of that well's hydraulic fracturing operations and seven days following the onset of well flowback. During the study period we identified 826 unique well-seismicity matches, or 19.2% of the wells for which Frac Notices had been submitted. We further refined the Catalog to 624 wells by removing wells with associated seismicity where the maximum magnitude is <2. Assigning individual seismic events to a single nearby well further culled the dataset to 333 wells with hydraulic fracturing-related seismicity.
The major findings of this study are: 7.7% of the wells fracture stimulated during the study period in the state of Oklahoma have associated seismicity magnitude ≥2. The rate of well-seismicity occurrence and amount of seismic energy matched to a well completion is relatively constant over the study period. There are areas in Oklahoma with a significantly higher concentration of wells associated with seismic events. In the Central Area of the Well Completion Area of Interest outlined by the OCC, 19.5% of the wells have associated seismicity with magnitudes greater than or equal to 2.0. We identified 960 earthquakes with magnitude ≥ 2 in the Frac Notice – Seismicity Match Catalog. Of those, 57 events had a magnitude ≥ 3. The largest earthquake associated with a well completion occurred in July 2019 in Kingfisher County; the OGS earthquake catalog recorded the magnitude as a ML 3.9 and the USGS NEIC catalog listed the event as a Mw 3.6.
7.7% of the wells fracture stimulated during the study period in the state of Oklahoma have associated seismicity magnitude ≥2.
The rate of well-seismicity occurrence and amount of seismic energy matched to a well completion is relatively constant over the study period.
There are areas in Oklahoma with a significantly higher concentration of wells associated with seismic events. In the Central Area of the Well Completion Area of Interest outlined by the OCC, 19.5% of the wells have associated seismicity with magnitudes greater than or equal to 2.0.
We identified 960 earthquakes with magnitude ≥ 2 in the Frac Notice – Seismicity Match Catalog. Of those, 57 events had a magnitude ≥ 3. The largest earthquake associated with a well completion occurred in July 2019 in Kingfisher County; the OGS earthquake catalog recorded the magnitude as a ML 3.9 and the USGS NEIC catalog listed the event as a Mw 3.6.
Seismic waveform template matching using the OGS network data has helped increase the sensitivity of the OGS regional seismic array with additional earthquake detections. The OCC will continue to assess its usefulness in assessing the success of the operator's mitigation strategies during hydraulic fracturing operations associated with induced seismicity.
Limited research work and publications are available to examine the performance of Progressive Cavity Pumps (PCP) based on machine learning methods, especially in Coal Seam Gas (CSG) operations. Previous work done in this space either focuses on exception-based surveillance on time-series data , or the use of machine learning to optimize completion design  and production . This paper will discuss how data approximation and unsupervised machine learning methods can be applied to time-series data-sets, using data gathered from automation systems, to help analyze PCP performance and detect anomalous pump behavior.
Undershultz, Jim (University of Queensland) | Mukherjee, Saswata (University of Queensland) | Wolhuter, Alexandra (University of Queensland) | Xu, Huan (China University of Petroleum, East China and The University of Queensland) | Banks, Eddie (Flinders University) | Noorduijn, Saskia (Flinders University) | McCallum, Jim (University of Western Australia)
There is an increasing need to understand the influence of faults in both gas production performance and the resulting potential impact on adjacent groundwater resources.Faults can exhibit a wide variety of hydraulic properties. Where resource development induces changes in pore pressure, the effective stress and thus the permeability can be transient. In this study, w explored strategies for characterizing fault zone properties for the initial purpose of evaluating gas production performance. The same fault characterization can then be incorporated into regional groundwater flow models to more accurately represent stress, strain and the resulting transmissivities when assessing the impact of gas development on adjacent aquifers.
Conventional fault zone analysis (juxtaposition, fault gouge or shale smear, fault reactivation) is combined with hydrodynamic analysis (distribution of hydraulic head and hydrochemistry) and surface water hydrology and hydrochemistry to evaluate across fault or up fault locations of enhanced hydraulic conductivity at specific locations of complex fault systems.
The locations of identified vertical hydraulic communication from the hydraulic analysis are compared with the fault zone architecture derived from the 3D seismic volume overlain with the
Accurate coal identification is critical in coal seam gas (CSG) (also known as coalbed methane or CBM) developments because it determines well completion design and directly affects gas production. Density logging using radioactive source tools is the primary tool for coal identification, adding well trips to condition the hole and additional well costs for logging runs. In this paper, machine learning methods are applied to identify coals from drilling and logging-while-drilling (LWD) data to reduce overall well costs. Machine learning algorithms include logistic regression (LR), support vector machine (SVM), artificial neural network (ANN), random forests (RF), and extreme gradient boosting (XGBoost). The precision, recall, and F1 score are used as evaluation metrics. Because coal identification is an imbalanced data problem, the performance on the minority class (i.e., coals) is limited. To enhance the performance on coal prediction, two data manipulation techniques [naive random oversampling technique (NROS) and synthetic minority oversampling technique (SMOTE)] are separately coupled with machine learning algorithms.
Case studies are performed with data from six wells in the Surat Basin, Australia. For the first set of experiments (single well experiments), both the training data and test data are in the same well. The machine learning methods can identify coal pay zones for sections with poor or missing logs. It is found that ROP is the most important feature. The second set of experiments (multiple well experiments) use the training data from multiple nearby wells, which can predict coal pay zones in a new well. The most important feature is gamma ray. After placing slotted casings, all wells have over 90% coal identification rates and three wells have over 99% coal identification rates. This indicates that machine learning methods (either XGBoost or ANN/RF with NROS/SMOTE) can be an effective way to identify coal pay zones and reduce coring or logging costs in CSG developments.
Al-Alwani, Mustafa A. (Missouri University of Science and Technology) | Dunn-Norman, Shari (Missouri University of Science and Technology) | Britt, Larry K. (NSI Fracturing) | Alkinani, Husam H. (Missouri University of Science and Technology) | Al-Hameedi, Abo Taleb T. (Missouri University of Science and Technology) | Al-Attar, Atheer M. (Enterprise Products) | Trevino, Al-Hameedi (Missouri University of Science and Technology) | Al-Bazzaz, Waleed H. (Kuwait Institute for Scientific Research)
Drilling, completion, and stimulation designs have changed over time as a result of the oil and gas industry's ongoing efforts to increase well productivity. Over the last five years hydraulic fracturing treatments, represented by the volume of pumped water and the amount of proppant utilized, have increased significantly, along with the lengths of horizontal wells. This work represents a large-scale descriptive analysis study to illustrate the trends and the range of completion, stimulation and production parameters in the Marcellus Shale play of the Appalachian Basin between 2012 and the last quarter of 2017 (2012-2018).
A database was created by combing stimulation fluids and proppant data from the FracFocus 3.0 chemical registry, with completion and production data from the DrillingInfo database. More than 2000 Marcellus Shale wells were utilized in this study. The data were processed and cleaned from outliers. Box plots and distribution bar charts are presented for most of the parameters in this study, to show the range in values for each parameter and its frequency of use. The stimulation parameters were normalized to perforated lateral length in order to compare productivity between the wells.
Trends identified in this study show how operators in the Marcellus have increased the use of hybrid fracturing fluids, in addition to increasing water and proppant volumes over time. The work also illustrates the point at which increasing fracture treatment volumes no longer increases production rate.
This paper demonstrates the utility of integrating publicly available databases to examine well completion trends in the Marcellus. The work also provides a summary of well response as a function of treatment volume over the five year study period.