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Summary Benchmarking the recovery factor and production performance of a given reservoir against applicable analogs is a key step in field development optimization and a prerequisite in understanding the necessary actions required to improve hydrocarbon recovery. Existing benchmarking methods are principally structured to solve specific problems in individual situations and, consequently, are difficult to apply widely and consistently. This study presents an alternative empirical analog benchmarking workflow that is based upon systematic analysis of more than 1,600 reservoirs from around the world. This workflow is designed for effective, practical, and repeatable application of analog analysis to all reservoir types, development scenarios, and production challenges. It comprises five key steps: (1) definition of problems and objectives; (2) parameterization of the target reservoir; (3) quantification of resource potential; (4) assessment of production performance; and (5) identification of best practices and lessons learned. Problems of differing nature and for different objectives require different sets of analogs. This workflow advocates starting with a broad set of parameters to find a wide range of analogs for quantification of resource potential, followed by a narrowly defined set of parameters to find relevant analogs for assessment of production performance. During subsequent analysis of the chosen analogs, the focus is on isolating specific critical issues and identifying a smaller number of applicable analogs that more closely match the target reservoir with the aim to document both best practices and lessons learned. This workflow aims to inform decisions by identifying the best-in-class performers and examining in detail what differentiates them. It has been successfully applied to improve hydrocarbon recovery for carbonate, clastic, and basement reservoirs globally. The case studies provided herein demonstrate that this workflow has real-world utility in the identification of upside recovery potential and specific actions that can be taken to optimize production and recovery.

Background Early identification of the occurrence of arrhythmia in patients with acute myocardial infarction plays an essential role in clinical decision-making. The present study attempted to use machine learning (ML) methods to build predictive models of arrhythmia after acute myocardial infarction (AMI). Methods A total of 2084 patients with acute myocardial infarction were enrolled in this study. (All data is available on Github: https://github.com/wangsuhuai/AMI-database1.git). The primary outcome is whether tachyarrhythmia occurred during admission containing atrial arrhythmia, ventricular arrhythmia, and supraventricular tachycardia. All data is randomly divided into a training set (80%) and an internal testing set (20%). Apply three machine learning algorithms: decision tree, random forest (RF), and artificial neural network (ANN) to learn the training set to build a model, then use the testing set to evaluate the prediction performance, and compare it with the model built by the Global Registry of Acute Coronary Events (GRACE) risk variable set. Results Three ML models predict the occurrence of tachyarrhythmias after AMI. After variable selection, the artificial neural network (ANN) model has reached the highest accuracy rate, which is better than the model constructed using the Grace variable set. After applying SHapley Additive exPlanations (SHAP) to make the model interpretable, the most important features are abnormal wall motion, lesion location, bundle branch block, age, and heart rate. Among them, RBBB (odds ratio [OR]: 4.21; 95% confidence interval [CI]: 2.42–7.02), ≥ 2 ventricular walls motion abnormal (OR: 3.26; 95% CI: 2.01–4.36) and right coronary artery occlusion (OR: 3.00; 95% CI: 1.98–4.56) are significant factors related to arrhythmia after AMI. Conclusions We used advanced machine learning methods to build prediction models for tachyarrhythmia after AMI for the first time (especially the ANN model that has the best performance). The current study can supplement the current AMI risk score, provide a reliable evaluation method for the clinic, and broaden the new horizons of ML and clinical research. Trial registration Clinical Trial Registry No.: ChiCTR2100041960.

Global analogues are widely used across the exploration and production (E&P) life cycle. Analogues, used in conjunction with primary data, expand the knowledge of both the individual and team and develop insights that are not possible from using either local data or individual experience in isolation. Difficulties in the application of analogues arise when the analogues are not selected consistently, are too specific, or are in conflict with empirical local data. Most of these difficulties arise from the lack of a proper definition of analogues, absence of a systematic method of analogue selection, and poorly defined objectives for the use of analogues. Analogues are herein defined as comparable fields and reservoirs relevant to a specific question or set of questions. To select appropriate analogues, practitioners should focus on specific individual question(s) instead of “look-alike” fields. A consistent global field and reservoir knowledge base with standardized and classified geological and engineering parameters form the basis for analogue selection and analysis. The ability to standardize knowledge on practitioners’ own E&P assets and conduct benchmark comparisons against applicable global analogues is critical to the identification of potential problems, mitigation strategies, and best practices. Appropriate application of global analogues to a local situation not only fosters creative thinking but also provides a way to quickly learn, increase confidence, and efficiently reduce risk for E&P decision-making.

Naturally fractured reservoirs are important contributors to global petroleum reserves and production. Existing classification schemes for fractured reservoirs do not adequately differentiate between certain types of fractured reservoirs, leading to difficulty in understanding fundamental controls on reservoir performance and recovery efficiency. Three hundred naturally fractured reservoirs were examined to define a new classification scheme that is independent of the type of fracturing and describes fundamentally different matrix types, rock properties, fluid storage and flow characteristics. This study categorises fractured reservoirs in three groups: (1) Type 1: characterized by a tight matrix where fractures and solution-enhanced fracture porosity provide both storage capacity and fluid-flow pathways; (2) Type 2: characterized by a macroporous matrix which provides the primary storage capacity where fractures and solution-enhanced fracture porosity provide essential fluid-flow pathways; and (3) Type 3: characterized by a microporous matrix which provides all storage capacity where fractures only provide essential fluid-flow pathways. Differentiation is made between controls imparted by inherent natural conditions, such as rock and fluid properties and natural drive mechanisms, and human controls, such as choice of development scheme and reservoir management practices. The classification scheme presented here is based on reservoir and production characteristics of naturally fractured reservoirs and represents a refinement of existing schemes. This refinement allows accurate comparisons to be made between analogous fractured reservoirs, and trends and outliers in reservoir performance to be identified. Case histories provided herein demonstrate the practical application of this new classification scheme and the benefits that arise when applying it to the understanding of naturally fractured reservoirs.

Background: The clinical use of angiotensin-converting enzyme inhibitors (ACEI) and angiotensin-receptor blockers (ARB) in patients with COVID-19 infection remains controversial. Therefore, we performed a meta-analysis on the effects of ACEI/ARB on disease symptoms and laboratory tests in hypertensive patients infected with COVID-19 virus and those who did not use ACEI/ARB. Methods: We systematically searched the relevant literatures from Pubmed, Embase, EuropePMC, CNKI, and other databases during the study period of 31 December 2019 (solstice, 15 March 2020), and analyzed the differences in symptoms and laboratory tests between patients with COVID-19 and hypertension who used ACEI/ARB drugs and those who did not. All statistical analyses were performed with REVMAN5.3. Results: We included a total of 1808 patients with hypertension diagnosed with COVID-19 in six studies. Analysis results show that ACEI/ARB drugs group D-dimer is lower (SMD = −0.22, 95%CI: −0.36 to −0.06), and the chances of getting fever is lower (OR = 0.74, 95%CI: 0.55 to 0.98). Meanwhile, laboratory data and symptoms were not statistical difference, but creatinine tends to rise (SMD = 0.22, 95% CI: 0.04 to 0.41). Conclusion: We found that the administration of ACEI/ARB drugs had positive effect on reducing D-dimer and the number of people with fever. Meanwhile it had no significant effect on other laboratory tests (creatinine excepted) or symptoms in patients with COVID-19, while special attention was still needed in patients with renal insufficiency.

Objectives Cardiac injury is associated with poor prognosis of 2019 novel coronavirus disease 2019 (COVID-19), but the risk factors for cardiac injury have not been fully studied. In this study, we carried out a systematic analysis of clinical characteristics in COVID-19 patients to determine potential risk factors for cardiac injury complicated COVID-19 virus infection. Methods We systematically searched relevant literature published in Pubmed, Embase, Europe PMC, CNKI and other databases. All statistical analyses were performed using STATA 16.0. Results We analysed 5726 confirmed cases from 17 studies. The results indicated that compared with non-cardiac-injured patients, patients with cardiac injury are older, with a greater proportion of male patients, with higher possibilities of existing comorbidities, with higher risks of clinical complications, need for mechanical ventilation, ICU transfer and mortality. Moreover, C-reactive protein, procalcitonin, D-dimer, NT-proBNP and blood creatinine in patients with cardiac injury are also higher while lymphocyte counts and platelet counts decreased. However, we fortuitously found that patients with cardiac injury did not present higher clinical specificity for chest distress (P = 0.304), chest pain (P = 0.334), palpitations (P = 0.793) and smoking (P = 0.234). Similarly, the risk of concomitant arrhythmia (P = 0.103) did not increase observably either. Conclusion Age, male gender and comorbidities are risk factors for cardiac injury complicated COVID-19 infection. Such patients are susceptible to complications and usually have abnormal results of laboratory tests, leading to poor outcomes. Contrary to common cardiac diseases, cardiac injury complicated COVID-19 infection did not significantly induce chest distress, chest pain, palpitations or arrhythmias. Our study indicates that early prevention should be applied to COVID-19 patients with cardiac injury to reduce adverse outcomes.

In the past, most of the internal solitary waves (ISWs) found by seismic oceanography (SO) method were mode-1 ISWs. We discover many mode-2 ISWs in the Pacific coast of Central America by using SO method for the first time. These mode-2 ISWs are convex mode-2 ISWs with the maximum amplitudes of about 10 m, and most of them are ISWs with smaller amplitudes. The pycnocline for the mode-2 ISWs on the shelf (ISW3) is displaced 6.4% of the total seawater depth from the mid-depth of the total seawater. The deviation is large, and it shows a strong asymmetry feature of the peaks and troughs on the seismic profile. This is consistent with the results of previous numerical simulation. Observing the changes in the fine structure of mode-2 ISWs packet through pre-stack migration, it was found that the overall waveform of the three mode-2 ISWs (ISW1, ISW2, and ISW3) on the shelf during the acquisition time period of about 40 seconds is stable. The apparent phase velocity of these mode-2 ISWs calculated by the pre-stack migration section using the Common Offset Gathers is about 0.5 m/s, and their apparent propagation directions are from SW to NE along the seismic line (44 ° N, 0° pointing north). The vertical amplitude distribution and estimated apparent velocities of these mode-2 ISWs are basically consistent with the theoretical values ​​calculated from the KdV equation. By analyzing the apparent velocities of the three mode-2 ISWs (ISW1, ISW3, and ISW5) with relatively small apparent velocity errors, it is found that the apparent velocity of mode-2 ISWs generally increases with the increasing depth of seawater. In addition, the apparent phase velocity of the mode-2 ISWs with a larger maximum amplitude is generally larger. Based on the analysis of hydrological data in the study area, it was found that a strong anticyclone developed on the northwest side of the seismic survey line and a weaker anticyclone developed on the southeast side. These anticyclones will increase the depth of the thermocline in the surrounding seawater. According to previous studies, the deepening of the thermocline (pycnocline) maybe conducive to the generation of mode-2 ISWs.

In this paper, we used the seismic oceanography method to study the structural characteristics of internal solitary waves (ISWs) near the Strait of Gibraltar in the Mediterranean Sea, South China Sea and offshore Central America.The ISWs near the Strait of Gibraltar are the first mode depressional type, mostly medium amplitude and large amplitude internal solitary waves. The maximum vertical amplitude is up to 74.5m, and the amplitude increases with depth，the propagation velocity increases with amplitude. It can be determined that the "true" maximum amplitude position is near the pycnocline. After correction, the maximum half-height-width can reach 1721.8m, but there is somewhat different from the theoretical result，which may be related to the development stability of ISWs. As the solitary wave packet continuously moves eastward, the overall wave width becomes larger, and the vertical velocity becomes smaller. In this paper, seismic oceanography is applied to the analysis of ISWs in the Mediterranean Sea, which further proves the feasibility of using seismic oceanography to study the movement of sea water.We reprocess some multi-channel seismic (MCS) data which is acquired recently in the Dongsha region of the northeastern South China Sea and we obtain new seismic oceanography data. The research suggest that there are the mode-2 internal solitary wave(ISWs) not just the mode-1 ISWs and a special reflection pattern (hair-like reflection configuration )usually above sand dunes in the seismic images. In new seismic oceanography data, there are some mode-1 ISWs with amplitudes less than 50m and wavelength of 1~5 km and the biggest mode-1 ISWs have the amplitude about 45m. The internal solitary waves packets are not prototypical rank-ordered ISW packets, their soliton amplitudes are smaller than 40. The mode-2 ISWs is well-shaped and its’ amplitude is approximate 30m, the vertical structure height is about 200m.The reflection configuration of water column above sand dunes usually include weak reflection layer-maybe called turbulent bottom boundary layer, and there is hair reflection configuration that must not appear. Whether there will be hair reflection configuration or not may depend on the angle between the seismic line and the sand dunes.In the region offshore Central America, there are lots of mode-2 ISWs revealed from seismic oceanography data. We combine seismic data with hydrographic data to study the features of ISWs in these different regions. The preliminary results show the phase velocity in SCS is the largest, that in the Strait of Gibraltar is the second and that offshore Central America is the last. The phase velocity depends on the amplitude of ISW. Usually the mode-1 depressional ISW has the largest phase velocity, while the mode-1 elevation ISW is the second, and the mode-2 ISW is the last. The location of the maximum amplitude from the characteristic function is consistent with the pycnocline as shown from floating frequency curve. The polarity of ISW is consistent with nonlinear parameter of alpha. Seismic data in global continental margins will provide more and more key evidence to increase our understanding of ISW evolution in the ocean.

Supplemental material, sj-pdf-1-jra-10.1177_1470320320981321 for Effects of ACEI and ARB on COVID-19 patients: A meta-analysis by Yang Xue, Shaoqing Sun, Jianing Cai, Linwen Zeng, Shihui Wang, Suhuai Wang, Jingjie Li, Lin Sun and Jianmin Huo in Journal of the Renin-Angiotensin-Aldosterone System

In this paper, the shoaling mode-2 internal solitary waves (ISWs) in the Pacific coast of Central America are studied for the first time using seismic oceanography method. It is found that there is an asymmetry in the vertical amplitude variation of the mode-2 ISWs front and rear during the shoaling process. The amplitude may weaken the effect of the pycnocline deviation on the stability of the mode-2 ISWs. For large amplitudes, the pycnocline needs to deviate greatly, so that the mode-2 ISWs become unstable; for small amplitude, the pycnocline deviates very little, and the mode-2 ISWs become unstable. The pre-stack migration sections of the common offset gathers are used to calculate the apparent phase velocities of the mode-2 ISWs. It is found that in deep water, the seafloor depths and amplitudes simultaneously control the magnitude of the apparent phase velocities of the mode-2 ISWs; in shallow water, the amplitudes mainly control the magnitude of the apparent phase velocities of the mode-2 ISWs. For the mode-2 ISWs with small amplitudes ( 2 a / h 2 ≤ 2 ) in shallow water, the apparent phase velocities increase with the amplitudes, and increase rapidly; for the mode-2 ISWs with large amplitudes ( 2 a / h 2 > 2 ) in shallow water, the apparent phase velocities increase with the amplitudes, but increase slowly. By calculating the relative seismic spectrum energy, it is found that the seismic spectrum energy in the submesoscale wavenumber range corresponds well to the mode-2 ISWs waveform. The mode-2 ISWs in the shoaling process have submesoscale characteristics.

This paper presents the basic reservoir characteristics and the key improved oil recovery/enhanced oil recovery (IOR/EOR) methods for sandstone reservoir fields that have achieved recovery factors toward 70%. The study is based on a global analog knowledge base and associated analytical tools. The knowledge base contains both static (STOIIP, primary and ultimate recovery factors, reservoir/fluid properties, well spacing, drive mechanism, and IOR/EOR methods etc.) and dynamic data (oil rate, water-cut, and GOR, etc.) for more than 730 sandstone oil reservoirs. These reservoirs were subdivided into two groups: heavy and conventional oil reservoirs. This study focuses on the reservoirs with recovery factors great than 50% for heavy oil, and recovery factors from 60% to 79% for conventional oil with a view to understand the key factors for such a high recovery efficiency. These key factors include reservoir and fluid properties, wettability, development strategies and the IOR/EOR methods. The high ultimate recovery factors for heavy oil reservoirs are attributed to excellent reservoir properties, horizontal well application, high efficiency of cyclic steam stimulating (CSS) and steam flood, and very tight well spacing (P50 value of 4 acres, as close as 0.25 acres) development strategy. The 51 high recovery conventional clastic reservoirs are characterized by favorable reservoir and fluid properties, water-wet or mixed-wet wettability, high net to gross ratio, and strong natural aquifer drive mechanism. Infill drilling and water flood led to an incremental recovery of 20% to 50%. EOR technologies, such as CO2 miscible and polymer flood, led to an incremental recovery of 8% to 15%. Homogeneous sandstone reservoirs with a good lateral correlation can reach 79% final recovery through water flood and adoption of close well spacing. The lessons learned and best practices from the global analog reservoir knowledge base can be used to identify opportunities for reserve growth of mature fields. With favorable reservoir conditions, it is feasible to move final recovery factor toward 70% through integrating good reservoir management practices with the appropriate IOR/EOR technology.

Limited data is available for a new discovery at the preparatory stage for the plan of development (POD). Uncertainties exist such as the depositional environment of the reservoir and individual sandbody type, reservoir heterogeneities and fluid properties. This paper presents an innovative and unique method for the qualitative and quantitative evaluation of the influences of these uncertainties on production performance and final recovery factor.The developed methodology enables reservoir engineers and development geologists to conduct uncertainty assessment on production performance and final recovery factors by using a global analogs database and proprietary analytical software tools, including performance forecasting, characterization and attribute cross plotting, etc. The process consists of four steps: (a) selection of the analog reservoirs, (b) performance forecast, (c) uncertainties evaluation, and (d) analysis of key drivers impacting performance and recovery factor. In our case study, Field A is in its POD study stage. Based on available information, reservoir sand in Field A potentially consists of sandbodies of either fluvial channel (FC), distributary channel (DC) or combined fluvial and distributary channels (CFDC). Uncertainty evaluation results indicate that the sandbody of FC, DC and CFDC will produce ultimate recovery factors of 35.9%, 37.9% and 39.7% respectively for the medium-case scenario and 52.4%, 54.3% and 59.2%, respectively for the high-case. The various sandbody types also have a great influence on performances of life-cycle production profile, peak production rate and water-cut variations. Analog analysis of the same sandbody type reveals the impact of three group specific attributes on the ultimate recovery.Compared with the normal approach of conventional geological modeling and reservoir simulation, the analog solution using the proprietary software tool is an efficient process and provides reasonable results.