Reservoir Monitoring Research Articles

Gulls as a host for both gamma and deltacoronaviruses

The coronaviruses (CoV) are ubiquitous pathogens found in wide variety of hosts that constantly pose a threat to human and animal health as a result of their enormous capacity to generate genetic changes. Constant monitoring of virus reservoirs can constitute an early-warning tool and control the spread and evolution of the virus. Coronaviruses are common in wild birds, globally, and birds of the Charadriiformes in particular have been demonstrated to be carriers of delta- (dCoV) and gammacoronaviruses (gCoV). In this paper, we present the genetic characterisation of five CoV strains from black-headed (Chroicocephalus ridibundus) and common (Larus canus) gulls. Whole genome sequence analysis showed high similarity of detected dCoV in gulls to previously identified strains from falcon, houbara, pigeon and gulls from Asia (UAE, China). However, phylogenetic analysis revealed bifurcation within a common branch. Furthermore, the accumulation of numerous amino acid changes within the S-protein was demonstrated, indicating further evolution of dCoV within a single gull host. In turn, phylogenetic analysis for the most of the structural and non-structural genes of identified gCoV confirmed that the strain belongs to the duck coronavirus 2714 (DuCoV2714) species within Igacovirus subgenera, while for the spike protein it forms a separate branch not closely related to any gCoV species known to date. The current study provides new and significant insights into the evolution and diversification of circulating coronaviruses in members of Laridae family.

A novel velocity band energy workflow for fiber-optic DAS interpretation and multiphase flow characterization

Distributed fiber-optic sensing continues to gain widespread adoption in the energy industry because of the numerous benefits it offers for real-time surface and subsurface monitoring of pipelines, wellbores, reservoirs, and storage infrastructure. In this study, we introduce a novel workflow to analyze optical fiber-based distributed acoustic sensor (DAS) data, which takes into account the speed of sound for a certain phase to filter the acoustic energy or signal contributed by that phase. This information is then utilized for the characterization of multiphase flow. The application of the proposed velocity band energy (VBE) workflow is demonstrated using a dataset acquired in a 5163-ft-deep wellbore, for estimating gas void fraction and real-time gas–liquid interface tracking across the length of the well. The workflow utilizes a series of signal processing and conditioning steps that aim to reduce noise and enhance the signals of interest. The insights from the new methodology will further assist in validating DAS-based flow monitoring algorithms, leak detection and quantification, and reservoir characterization.

Validation of a novel rebound tonometer (Tono-Vera® Vet) in normal ex vivo rabbit eyes.

The purpose of this study was to validate the use of the Reichert Tono-Vera® Vet tonometer rabbit setting in normal ex vivo rabbit eyes and to compare the rabbit setting to the dog, cat, and horse settings of this tonometer. Six freshly enucleated normal rabbit eyes were cannulated and connected to a fluid reservoir and physiologic monitor. Triplicate measurements were obtained with the four available settings: dog, cat, horse, and rabbit at various intraocular pressures (IOP) ranging from 5 to 80 mmHg. Bland-Altman analysis was utilized to determine bias and 95% limits of agreement for each setting. Linear regression equations for the dog, horse, cat, and rabbit settings were y = 0.8101x + 2.5058, y = 0.7594x - 3.4673, y = 0.6635x + 0.3021, and y = 0.8935x + 1.3295, respectively. All settings demonstrated strong positive linear trends (dog r2 = 0.9644, horse r2 = 0.9456, cat r2 = 0.9309, and rabbit r2 = 0.9558). Bland-Altman plots revealed that the average bias and 95% limits of agreement (mmHg) were -4.73, -12.65, -12.86 and -2.73 and (-15.31, 5.86), (-29.03, 3.74), (-25.67, -0.05), and (-12.21, 6.76) for the dog, horse, cat, and rabbit settings, respectively. The Tono-Vera® Vet rabbit setting provided the most accurate and precise measurements compared with the other settings, but slightly underestimated actual IOP, especially as IOP was increased. This tonometer, using the rabbit setting, is likely to be appropriate for the estimation of IOP in rabbits with the appropriate correction formula applied.

Potential Impacts of Climate Change on Reservoir Water Quality in An Giang Province, Vietnam

As water scarcity puts over 80% of the world’s population at risk, water quality has become a major environmental topic. In particular, climate change has jeopardised the quality of water within the Vietnamese Mekong Delta (VMD), a key agronomic and aquaculture hub. A modest canal system and small to medium-sized reservoirs in the semi-mountain region of An Giang province contribute to a less abundant water supply and a tendency for water quality reservoirs to deteriorate. The water quality index method and descriptive technique were used in this study. The results show that in the period 2017–2020, some water quality indicators exceeded the permissible limits of the Vietnamese standards for domestic surface water in column B1 (NO3-, Total Coliform, BOD5, COD, N-NH4+) but are consistent, but are allowed for use in irrigation purposes. Findings show that for many years, WQI values in Tinh Bien and Tri Ton districts have diminished because of wastewater pollution. WQI values near the shores of O Tuk Sa Reservoir (Tinh Bien), Lo^˜i đánh máy (Tri Ton), and O Ta Soc Reservoir (Tri Ton) diminished over time. According to the WQI index, the water quality at the reservoir monitoring stations has fluctuated throughout the years, so it is advised that people implement water purification techniques for long-term well-being.

A brief review of steam flooding and its applications in fractured oil shale reservoirs

Steam flooding is an important thermal recovery method for heavy oil reservoirs, and convective heating technology is used to fracture oil shale reservoirs with good results. This paper reviews the main prediction methods, optimization approaches for steam flooding performance, and its application in fractured oil shale reservoirs. The prediction methods include experimental, numerical simulation, and statistical models. These provide insights into steam override, heat transfer, and production dynamics. To optimize steam flooding, parameters like quality, temperature, injection rate, and allocation need to be coordinated based on reservoir conditions and monitoring data. Real-time injection control, economic analysis, and sweep efficiency improvements should also be considered in optimization workflows. Although progress has been made, more field studies are needed to establish systematic optimization practices utilizing advanced technologies. This review summarizes the key developments in steam flooding modeling and optimization, providing a reference for further research and field applications.

A framework for subsurface monitoring by integrating reservoir simulation with time-lapse seismic surveys

Reservoir simulations for subsurface processes play an important role in successful deployment of geoscience applications such as geothermal energy extraction and geo-storage of fluids. These simulations provide time-lapse dynamics of the coupled poromechanical processes within the reservoir and its over-, under-, and side-burden environments. For more reliable operations, it is crucial to connect these reservoir simulation results with the seismic surveys (i.e., observation data). However, despite being crucial, such integration is challenging due to the fact that the reservoir dynamics alters the seismic parameters. In this work, a coupled reservoir simulation and time-lapse seismic methodology is developed for multiphase flow operations in subsurface reservoirs. To this end, a poromechanical simulator is designed for multiphase flow and connected to a forward seismic modeller. This simulator is then used to assess a novel methodology of seismic monitoring by isolating the reservoir signal from the entire reflection response. This methodology is shown to be able to track the development of the fluid front over time, even in the presence of a highly reflective overburden with strong time-lapse variations. These results suggest that the proposed methodology can contribute to a better understanding of fluid flow in the subsurface. Ultimately, this will lead to improved monitoring of reservoirs for underground energy storage or production.

Numerical simulation analysis of ecological monitoring of small reservoir dam based on maximum entropy algorithm

Abstract Displacement monitoring method of reservoir dam is a key research topic at present. In order to better display the overall efficiency of horizontal displacement and vertical displacement monitoring, a numerical simulation analysis method of ecological monitoring of small reservoir dam based on the maximum entropy algorithm is proposed. The virtual value is calculated by the maximum entropy algorithm, and the probability distribution function of random variables is obtained. The comprehensive prediction model of ecological monitoring results is constructed by the probability distribution function, and the daily monitoring values of ecological history of small reservoir dams are obtained. The maximum entropy probability density function is used to calculate the initial moment of small reservoir displacement samples, calculate the abnormal probability of the dam, get the maximum entropy probability density, realize the unbiased distribution of simulation values, and complete the dam deformation monitoring of small reservoirs. The simulation experiment is verified by numerical simulation. The results show that this method can effectively monitor the horizontal and vertical displacement of the dam; monitor the water-level hydrograph of pressure pipes at each measuring point; and obtain the changes of ecological runoff, temperature difference, and sediment discharge around the dam of small reservoirs in real time, which provides data guarantee for improving the ecological added value of small reservoirs.

The Weisweiler passive seismological network: optimised for state-of-the-art location and imaging methods

Abstract. Passive seismic analyses are a key technology for the exploration and monitoring of subsurface reservoirs. Searching for alternative resources in the framework of the energy transition is creating a surge for identifying as many potential sites as possible suitable for geothermal exploitation. The Lower Rhine Embayment, at the western border of North Rhine-Westphalia in Germany, is an extensional system with a very high potential for geothermal exploitation. The area experiences moderate but continuous natural seismicity. Here, we report on a passive seismic dataset recorded with 48 seismic stations centred at and around Eschweiler–Weisweiler (https://doi.org/10.14470/MO7576467356, Finger et al., 2022). Background seismic noise levels are high at this site due to high levels of anthropogenic noise and thick unconsolidated sedimentary layers. The final station layout is a compromise between targeted network design and suitably quiet locations. We show that the network design allows for the application of state-of-the-art methods including waveform-based source location methods and ambient-noise velocity imaging methods.

Optimized time-lapse acquisition design via spectral gap ratio minimization

Modern-day reservoir management and monitoring of geologic carbon storage increasingly call for costly time-lapse seismic data collection. We demonstrate how techniques from graph theory can be used to optimize acquisition geometries for low-cost sparse 4D seismic data. Based on midpoint-offset-domain connectivity arguments, our algorithm automatically produces sparse nonreplicated time-lapse acquisition geometries that favor wavefield recovery.

WATER QUALITY ASSESSMENT IN RELATION TO THE SURROUNDING SOIL MANAGEMENT OF TWO RESERVOIRS IN PINDORAMA/SP - A PRELIMINARY STUDY

Water quality monitoring of rural reservoirs is essential to detect the effects of diffuse pollution sources such as agricultural activities on the water quality. This paper describes a preliminary study that uses a multiparameter probe and total phosphorus analysis to characterize and compare two reservoirs in Pindorama/SP surrounded by active plantations, noting that one of them has its surface filled with floating macrophytes. The reservoirs’ areas were characterized, and analysis of physicochemical parameters were made in strategic sampling points. Elevated total phosphorus concentrations were detected in both reservoirs, being hypothesized that the source of this nutrient is the runoff of agricultural byproducts from the surroundings. The reservoir filled with macrophytes had greater phosphorus concentration and was characterized as in a eutrophic state, thus explaining the overpopulation of macrophytes as they can be a consequence of the eutrophication process. Lower levels of phosphorus in the other reservoir may be explained by its morphological characteristics and the presence of a more consolidated riparian forest. To reduce the environmental impacts of the contamination in both reservoirs, it was proposed that practices for adequate soil management in the surroundings, for increasing the reservoirs’ water circulation, and for sustainably retaining the contamination sources, could be implemented to control the effects of eutrophication.

Using Large-Size Three-Dimensional Marine Electromagnetic Data for the Efficient Combined Investigation of Natural Hydrogen and Hydrocarbon Gas Reservoirs: A Geologically Consistent and Process-Oriented Approach with Implications for Carbon Footprint Reduction

The recycling or burial of carbon dioxide in depleted petroleum reservoirs and re-imagining exploration strategies that focus on hydrogen reservoirs (with any associated hydrocarbon gas as the upside potential) are a necessity in today’s environmental and geopolitical climate. Given that geologic hydrogen and hydrocarbon gases may occur in the same or different reservoirs, there will be gains in efficiency when searching for both resources together since they share some commonalities, but there is no geophysical workflow available yet for this purpose. Three-dimensional (3D) marine controlled-source electromagnetic (CSEM) and magnetotelluric (MT) methods provide valuable information on rock-and-fluid variations in the subsurface and can be used to investigate hydrogen and hydrocarbon reservoirs, source rocks, and the migration pathways of contrasting resistivity relative to the host rock. In this paper, a process-oriented CSEM-MT workflow is proposed for the efficient combined investigation of reservoir hydrocarbon and hydrogen within a play-based exploration and production framework that emphasizes carbon footprint reduction. It has the following challenging elements: finding the right basin (and block), selecting the right prospect, drilling the right well, and exploiting the opportunities for sustainability and CO2 recycling or burial in the appropriate reservoirs. Recent methodological developments that integrate 3D CSEM-MT imaging into the appropriate structural constraints to derive the geologically robust models necessary for resolving these challenges and their extension to reservoir monitoring are described. Instructive case studies are revisited, showing how 3D CSEM-MT models facilitate the interpretation of resistivity information in terms of the key elements of geological prospect evaluation (presence of source rocks, migration and charge, reservoir rock, and trap and seal) and understanding how deep geological processes control the distribution and charging of potential hydrocarbon, geothermal, and hydrogen reservoirs. In particular, evidence is provided that deep crustal resistivity imaging can map serpentinized ultramafic rocks (possible source rocks for hydrogen) in offshore northwest Borneo and can be combined with seismic reflection data to map vertical fluid migration pathways and their barrier (or seal), as exemplified by the subhorizontal detachment zones in Eocene shale in the Mexican Ridges fold belt of the southwest of the Gulf of Mexico, raising the possibility of using integrated geophysical methods to map hydrogen kitchens in different terrains. The methodological advancements and new combined investigative workflow provide a way for improved resource mapping and monitoring and, hence, a technology that could play a critical role in helping the world reach net-zero emissions by 2050.

Induced microseismicity and tremor signatures illuminate different slip behaviours in a natural shale fault reactivated by a fluid pressure stimulation (Mont Terri)

SUMMARY Fault slip induced by fluid perturbation in shale formations may only lead to a sparse seismicity. However, fault slip may strongly impact the integrity of shale formations that serve as caprocks for geological reservoirs holding buoyant fluids such as CO2, natural gas or hydrogen. A better understanding of the fluid reactivation processes of fault and the seismic triggering process is therefore critical for reservoir monitoring and fault stability. Here we analyse the seismic responses of a shale fault exposed to fluid pressurization during an in situ field-scale injection experiment at ∼340 m depth in the Mont Terri underground research laboratory (Switzerland). Two main types of seismic signals are observed as the fault was activated and started to slowly slip. After an aseismic phase, we observed tremor signatures and an increase in noise amplitude, which were directly associated with the slowly propagating fault slip in response to fluid injection. These signatures were later followed by micro-earthquakes that seem to occur further away from the fluid-pressurized area. We interpret these micro-earthquakes to be triggered by stress perturbations from the main slip growth. These two classes of seismic responses therefore highlight two different processes. Tremors seem to be a more direct observation for the fluid-induced slip propagation than micro-earthquakes. Even hidden in the noise, they precede earthquake failures, thus providing a useful tool for monitoring fluid leakage activated by slow deformation on low permeable shale faults, with applications for sealing integrity of caprocks.

Development of hybrid computational data-intelligence model for flowing bottom-hole pressure of oil wells: New strategy for oil reservoir management and monitoring

Among several metric parameters concerning the assessment of oil and gas well production, the flowing bottom-hole pressure (FBHP) is considered essential. Accurate prediction of FBHP is crucial for petroleum engineering and management. Several related parameters are associated with the FBHP magnitude influence; thus, proper inspection of those parameters is another vital concern. This research proposes a hybrid modeling framework based on the hybridization of machine learning (ML) models (i.e., Extreme Learning Machine (ELM), Support Vector Machine Regressor (SVR), Extreme Gradient Boosting (XGB), and Multivariate Adaptive Regression Spline (MARS)) and nature-inspired Differential Evolutional (DE) optimization for FBHP prediction. The adjustment of the internal parameters of the ML-based models and the input feature selection is formulated as an incremental learning problem that is solved by the evolutionary algorithm. Problem-specific samples were collected from the open-source literature for this investigation. Modeling results are adaptable, automatically determining the most relevant variables for the context of the ML model. The adaptive polynomial structure of hybridized MARS model attained the best average performance for the FBHP modeling with correlation (R = 0.94) and minimum root mean square (RMSE = 97.88). The proposed modeling framework produces an alternative efficient computer aid model for FBHP prediction, resulting in reliable automated technology to assist oil and gas well management.

Developing a Modified Online Water Quality Index: A Case Study for Brazilian Reservoirs

Online approaches for monitoring water quality can be an alternative aid to rapid decision-making in watershed management, especially reservoirs, given their vulnerability to the process of eutrophication. In this study, a modified water quality index (WQI) was developed using parameters that are easily measured with sensors, which would allow for the online monitoring of reservoirs. The modified WQI was based on WQICETESB and we used regression models to obtain values for the parameters: total phosphorus (TP), total nitrogen (TN), biochemical oxygen demand (BOD) and total solids (TS). Water quality data from reservoirs from 2003 to 2020 were used, which were provided by the Environmental Company of the State of São Paulo (CETESB), Brazil. The adjusted modified WQI employing weight redistribution (WQIRWAdj or WQISOL) presented the most promising results, with a Pearson correlation of 0.92 and a success rate of 72.6% and 97.0% for the CETESB and simplified classifications, respectively. WQISOL, which was proposed in the present study, exhibited a satisfactory performance, allowing the water quality of reservoirs to be monitored remotely and in real-time.

Data Assimilation of Production and Multiple 4D Seismic Acquisitions in a Deepwater Field Using Ensemble Smoother with Multiple Data Assimilation

Summary In recent years, time-lapse (4D) seismic (4DS) data have been widely used for reservoir monitoring to provide relevant information on dynamic changes occurring during production. In complex reservoirs, multiple seismic monitor surveys are usually available. Updating reservoir models with these data can be very beneficial to improve the field’s management. In the quantitative integration of 4DS data into the data assimilation (DA) process, it is crucial to define how to deal with more than one seismic monitor. In this work, we continue a series of investigations about seismic DA procedures and expand on them by analyzing ways to assimilate more than one seismic monitor. More specifically, we evaluate different ways of using production data and two monitor surveys (M3 and M5) to calibrate the dynamic models of a real Brazilian reservoir using the ensemble smoother with multiple data assimilation (ES-MDA) method. We performed the following experiments: (1) sequential assimilation of M3 and M5 with parts of well history divided according to the seismic acquisition dates; (2) assimilation of M3 with the entire well history and subsequent assimilation of M5; (3) assimilation of well and M3 data; and (4) assimilation of well and M5 data. For comparison purposes, we also assimilated only well data. From the results, we observed that well and 4DS data misfits were reduced when assimilating both monitors, compared to the cases where only a single monitor (any of them) was used with production data. This conclusion is also true in the comparison with results obtained when only assimilating well data. This indicates that both seismic monitors are important data to be quantitatively considered in DA. In this particular field, using a previous DA run to solely assimilate the newly available monitor (Case 2) delivered better models and long-term forecasts. Therefore, this would be our recommendation. This study highlights the importance of several 4DS acquisitions for reservoir monitoring and management and shows the challenges of their application in seismic DA for better life cycle field applications.

An integrated geochemical spatial and temporal survey of thermal springs to characterize the geothermal resource of a volcano (Piton des Neiges, Réunion Island)

Geothermal exploration can be challenging in the absence of obvious surface indicators of a high enthalpy geothermal resource such as geysers, fumaroles or thermal springs with temperatures near 100 °C. This is the case at the Piton des Neiges volcano (Réunion Island), which displays evidence of hydrothermal activity mostly as thermal springs with temperatures not exceeding 50 °C, affected by mixing and reequilibration, and emerging in a complex geological framework, resulting from the polygenic history of this dormant volcano. Yet, these thermal springs keep a partial record of the reservoir geochemistry. Here, we propose an exploration method to set this thermal signature apart from the contribution of other processes and trace back the equilibrium conditions, enabling us to locate thermal fluid circulations, and evaluate their temperature and availability. We report its application at Piton des Neiges volcano. We led an extensive geochemical survey which nearly doubled the number of thermal springs reported on the volcano and dramatically extended the existing geochemical database in space and time. In tandem, we also monitored δ18O and δD values in rainwaters and thermal springs over two years to compare their temporal variations.Our surveys show that the repartition of thermal springs is controlled by only one of the volcanic rift zones (the N30°E axis), which is thus identified as the heat source of hydrothermal circulations. This N30°E rift zone is also a preferential pathway for the degassing of mantellic CO2. In addition, the composition of thermal waters is influenced by syenite intrusions along the rim of the caldera, acting as drains for the uprise of hydrothermal waters. O, H and Sr isotopic signatures of springs show that the geothermal resource of Piton des Neiges is in fact made of two independent and unconnected hydrothermal systems on the northern and southern circular depressions of the volcano (the cirques of Salazie and Cilaos, respectively). Their recharge is meteoric, multi-year, and mostly achieved by cyclonic events. Thermal waters experience reequilibration during their ascent and various degrees of CO2 input or degassing. Last equilibrium temperatures of water/rock interaction, estimated by multicomponent geothermometry, reach up to 125 ± 6 °C in the cirque of Salazie, and up to 141 ± 15 °C in the cirque of Cilaos, with possibility for hotter waters before reequilibration. Taken together, our results suggest that the most promising target for future exploration is located in the cirque of Cilaos, along the caldera rim, and in proximity of syenite intrusions.With a thorough prospecting of thermal springs, a comprehensive geochemical study and a geochemical monitoring of the different water reservoirs, we improved our understanding of the geothermal resource and identified future exploration targets at Piton des Neiges volcano.A separation scheme for strontium and light rare earth elements and its application to the isotopic analysis of strontium and neodymium in silicate rocks are presented. This method benefits from the selectivity and high capacity of two newly introduced extraction Chromatographic materials, referred to as Sr.Spec and TRU.Spec, respectively. These afford a straightforward separation of Sr and Sm + Nd with high yield, good purity and satisfactory blank levels, on very small (0.25 ml) columns using small volumes of solutions of a single mineral acid, HNO3. The validity of the method is illustrated by the measurement of 87Sr/ 86Sr and 143Nd/144Nd ratios in twelve international standard reference materials.

Monitoring fluid saturation in reservoirs using time‐lapse full‐waveform inversion

AbstractMonitoring the rock physics properties of the subsurface is of great importance for reservoir management. For either oil and gas applications or CO2 storage, seismic data are a valuable source of information for tracking changes in elastic properties which can be related to fluids saturation and pressure changes within the reservoir. Changes in elastic properties can be estimated with time‐lapse full‐waveform inversion. Monitoring rock physics properties, such as saturation, with time‐lapse full‐waveform inversion is usually a two‐step process: first, elastic properties are estimated with full‐waveform inversion, then the rock physics properties are estimated with rock physics inversion. However, multiparameter time‐lapse full‐waveform inversion is prone to crosstalk between parameter classes across different vintages. This leads to leakage from one parameter class to another, which, in turn, can introduce large errors in the estimated rock physics parameters. To avoid inaccuracies caused by crosstalk and the two‐step inversion strategy, we reformulate time‐lapse full‐waveform inversion to estimate directly the changes in the rock physics properties. Using Gassmann's model, we adopt a new parameterization containing porosity, clay content and water saturation. In the context of reservoir monitoring, changes are assumed to be induced by fluid substitution only. The porosity and clay content can thus be kept constant during time‐lapse inversion. We compare this parameterization with the usual density–velocity parameterization for different benchmark models. Results indicate that the proposed parameterization eliminates crosstalk between parameters of different vintages, leading to a more accurate estimation of saturation changes. We also show that using the parameterization based on porosity, clay content and water saturation, the elastic changes can be monitored more accurately.

Real-time fluid flow movement identification in porous media for reservoir monitoring application using polycarbonate optical fibre Bragg grating sensor

Fibre optic sensing technology has recently been hailed as a viable alternative for a real-time reservoir monitoring method. The aim of this study is to develop a robust and high-sensitivity polycarbonate optical fibre (PCPOF) sensor that can detect oil movement in porous media. To enhance the sensing capability of the Bragg sensor, partial removal of the cladding and deposition of APTES treated TiO2 on the sensing region was conducted. The cladding layer was removed using the chemical etching and the etching time was varied from 5 to 11 min. The best etching time was 9 min with a cladding thickness of ∼1.47 µm and increasing the etching time may result in damage to the fibre core. The nanoparticles were coated evenly to the sensing areas through a double dip-coating technique to ensure uniform distribution of TiO2. Sensor sensitivity was tested at 60 °C, 90 °C, and 120 °C. The sensitivity of the sensor was found to be more than 100 nm/RIU on average in different temperatures and the sensor was also capable to work at a temperature of 120 °C. Thus, the fabricated fibre optic sensor offers huge potential for real-time monitoring of reservoirs in oil and gas fields, which should be a very useful tool for engineers.

New Concept Ocean-Bottom Multiphysics (OBMP) Nodes for Reservoir Monitoring

Marine-controlled source electromagnetics (CSEM) have been extensively applied to various exploration scenarios worldwide. However, its perceived value and cost relative to seismic and the scarcity of realistic case studies have limited the industry’s interest in time-lapse reservoir-monitoring (4D) applications. A feasible way to make demand for CSEM for 4D-monitoring programs would be to increase the value of information and reduce survey costs by performing joint operations where seismic and CSEM data are acquired during the same survey and at equivalent spatial densities. To this end, we propose a new multiphysics ocean-bottom nodes (OBN) concept and show the industry that CSEM can be a cost efficient and effective integrators to 4D seismic projects. To this end, we conducted a feasibility study demonstrating that horizontal magnetic field components have the required sensitivities and can be used instead of horizontal electric field components in mapping the 3D resistivity distribution and 4D fluid change responses in a given reservoir. This makes engineering a new OBN class simpler and cheaper, as various miniaturized magnetic field sensors are available off-the-shelf or readily working along with packaging and coupling solutions.

Time‐lapse PS‐wave time‐shifts and quantitative pressure‐saturation discrimination applications

AbstractWe show that time‐lapse (4D) time‐shifts from PS‐wave data are valuable as they are very sensitive to pressure changes, whereas 4D time‐shifts from PP‐wave data are sensitive to both pressure and saturation changes. This gives another opportunity from using 4D amplitudes alone to understand and discriminate areas of pressure changes from areas of saturation changes in field data. 4D PS time‐shifts sense transmission related changes taking into consideration propagation through the altered medium, whereas amplitude changes are reflection or backscattered signals from the boundary. Therefore, these two attributes will be complimentary in 4D interpretation. Rock‐physics‐based time‐shift cross‐plots are generated to analyse how pressure and saturation changes in a reservoir impact PP‐ and PS‐wave time‐shifts. The developments of 4D time‐shifts are shown fixing the reservoir properties and varying reservoir layer thickness. Synthetic seismic data from a wedge is modelled to understand differences between 4D amplitude and time‐shift changes and the value of PS time‐shifts. Cases with pressure changes only and saturation changes only are also analysed with the wedge model. The method is next applied to two 4D field data sets. One is in the North Sea and the other offshore Brazil. In these field data sets, with different levels of noise in the 4D data, we see interpretable results from PS‐wave time‐shifts that can help in 4D signal understanding and improve reservoir characterization and monitoring practices. We believe that with modern acquisition and processing, this technology is realizable and provides quantitative and accurate 4D interpretations. It is shown that the use of PS‐wave data can lead to a larger chance of success in placing development wells.