Thin Reservoir Research Articles

A Laboratory Experimental Study on Enhancing the Oil Recovery Mechanisms of Polymeric Surfactants.

In order to evaluate the physical and chemical properties of polymer surfactants and analyze their oil displacement mechanisms, three types of poly-surfactant used in the Daqing oil field were chosen to be researched, and the oil displacement effects were studied using poly-surfactants of different viscosity, dehydrating rate, and core permeability. The main purpose is to determine the reasonable range of different characteristic indexes of polymeric surfactant flooding. The oil displacement effect of 15 cores was analyzed, and the effects of viscosity, the dehydrating rate of emulsion, and permeability on EOR (Enhanced Oil Recovery) were analyzed. The oil displacement mechanisms of polymeric surfactants were researched using a photolithographic glass core. This paper explores the mechanism underlying production enhancement as an EOR target, while simultaneously conducting laboratory tests to assess the physical and chemical properties of polymeric surfactants. The poly-surfactant agents exhibit a notable increase in viscosity, with the optimal displacement effect observed at a core effective permeability exceeding 400 mD, resulting in a potential EOR of 15% or higher. Moreover, at a viscosity ranging between 40 and 70 mPa·s, the total EOR can reach 73%, with the peak efficiency occurring at a viscosity of 60 mPa·s. The water loss rate of the emulsion, ranging between 30% and 70%, achieves optimal performance at 50%. The poly-surfactants' higher viscosity extends the oil sweep area, enhancing recovery efficiency, and noticeably reducing residual oil compared to water flooding. During poly-surfactant flooding, a substantial amount of residual oil is extracted and transformed into droplets. The rapid emulsification of the polymeric surfactant solution with crude oil forms a stable emulsion, contributing to its significant oil recovery effect. This research provides valuable technical support for EOR in thin and low-quality reservoirs of onshore multi-layered sandstone reservoirs.

Opportunities and challenges for gas coproduction from coal measure gas reservoirs with coal‐shale‐tight sandstone layers: A review

AbstractThe extraction of coal measure gas has been shifted toward thin gas reservoirs due to the depletion of medium‐thick gas reservoirs. The coproduction of coalbed gas, shale gas, and tight sandstone gas (called a multisuperposed gas system) is a key low‐cost technology for the enhancement of natural gas production from thin gas reservoirs in coal measure. As an emerging engineering exploitation technology at its early stage of development, gas coproduction confronts various engineering challenges in hydraulic fracturing, bottom‐hole pressure regulation, well network arrangement, and extraction sequence. The current understanding of the opportunities and challenges in the gas coproduction from the multisuperposed gas system is not comprehensive enough. In this case, the previous achievements in the field of gas coproduction should be urgently reviewed to provide valuable guidance and recommendations for further development. This review first discusses the regional and spatial distribution characteristics and possible reservoir combinations of gas reservoirs in coal measure. Then, the basic properties of different reservoirs, engineering challenges, and interlayer interference are comparatively analyzed and discussed. The current simulation models for gas coproduction and potential future research directions are further explored. The results indicate that the coupling effects of reservoir heterogeneity, interwell interference, and geological structure for increasing coproduction prediction accuracy should be included in future simulation models for gas coproduction. Careful investigation is required to explore the mechanisms and their further quantifications on the effects of interlayer interference in gas coproduction. The fractal dimension as a scale can play an important role in the characterization of the gas and water transport in different reservoirs. The machine learning methods have tremendous potential to provide accurate and fast predictions for gas coproduction and interlayer interference.

A novel high-resolution imaging method based on sparsity in the time domain and spectral fitting in the frequency domain

During the propagation of seismic waves underground, the high-frequency seismic response of thin reservoir is absorbed and attenuated, which poses a challenge in seismic thin reservoir prediction. The high-resolution processing techniques have the capability to significantly expand the frequency range of the seismic data, so it becomes a key technique for thin reservoir prediction. Most of these techniques necessitate the extraction of seismic wavelets. However, the spatial and temporal variations of seismic data result in multiple solutions for wavelet extraction. Simultaneously, the majority of techniques fail to consider the influence of spatial tectonic features on the high-resolution processing. In this paper, we propose a novel solution to address these two fundamental challenges by utilizing seismic spectral expansion, sparse reflection coefficients, and spatial continuity constraints. First, we propose an innovative spectral fitting method that aims to expand the frequency bandwidth while adhering to the desired wavelet constraints. This method allows us to fully utilize the effective frequency information. It not only obtains broadband seismic data but also captures precise wavelets. Then, sparse deconvolution is employed to further extend the frequency range by utilizing the accurately expected wavelet and obtaining a high-resolution reflection coefficient. Finally, the Hessian matrix regularization is employed to constrain the spatial continuity of the reflection coefficient. This method is validated in both the model and real seismic data. Compared to traditional sparse deconvolution and spectral modeling deconvolution with spatial constraints, this method not only expands the frequency bandwidth and enhances seismic resolution but also preserves operational frequency information and improves the spatial continuity of seismic data. It has been verified that this approach can be used to forecast thin reservoir and reconstruct spatial tectonic characteristics.

Improved prediction of thin reservoirs in complex structural regions using post-stack seismic waveform inversion: a case study in the Junggar Basin

The Mahu sag slope area, which holds significance as an oil and gas resource, still have some underexplored regions because of structural mismatches, presenting a potential challenge to be properly addressed. To resolve, this study conducts a comprehensive investigation concerning structural characteristics, fault combinations, favorable reservoir distribution, reservoir control factors, and oil-water distribution characteristics within the Triassic Baikouquan Formation, evaluating the impact of depositional environments and sedimentary dynamics on reservoir quality. For this purpose, constrained sparse spike inversion and seismic waveform indication inversion were employed to comparatively evaluate oil and gas reservoirs, further integrating petrophysical and geological data with geological modeling to enhance accuracy in complex structural geology and enable high-precision reservoir prediction. The findings elucidated the distribution range of the Baikouquan Formation and the location of oil reservoir sand bodies, as exemplified by well B and identified potential hydrocarbon traps, offering valuable insights into reservoir performance. It demonstrated comparatively reliable effects and considerable predictability power of seismic waveform indication inversion. These outcomes provide a strong foundation for future evaluations and multi-layer system deployment in the region by serving as a novel valuable framework for subsequent development activities not only in the Mahu sag but also in similar regions.

Reservoir identification of marine facies carbonate shoals in the Middle Permian in the Sichuan Basin

Controlled by the base level change cycle, the carbonates exposed from the periodically shallowed water body at the top of the high-frequency sequence develops multiple sets of thin reservoirs. Such reservoir identification has always been tricky in the prediction of carbonate reservoirs. Based on the Middle Permian strata from the Sichuan Basin, this paper established a forecasting approach of high-frequency-sequence-controlled carbonate thin reservoir. The steps are as follows: (1) Combine the measured results of samples from the typical outcrops with changes of carbon and oxygen isotopes, thus to construct a division program for the 3rd-order sequence of the Middle Permian strata. (2) Compare the carbon and oxygen isotope changes and the global sea level change trend, determine the controlling factors of the 3rd-order sequences. (3) Carry out spectrum analysis based on the natural gamma energy spectrum logging (ln (Th/K)) curves of Wells Long-17 and Anping-1 to establish a high-frequency sequence framework division program, and then apply the logging curve characteristics to correct the top interface positions of the high-frequency sequences, which is the potential location of carbonate reservoir. The research results suggest that the Middle Permian in the Sichuan Basin can be divided into three 3rd-order sequences, which are PSQ1, PSQ2 and PSQ3 from bottom to top. Among which, PSQ1 is mainly affected by global sea level (GSL) changes, and the changes originated from its tuning curve can be directly applied to the division of high-frequency sequences and reservoir prediction. PSQ2 and PSQ3 are jointly controlled by global sea level changes and regional tectonics. In cope with the influence of regional tectonics, the positions of the four-level sequence interface established according to the tuning curve need to be fully considered, and good results were achieved through systematical correction. This method can effectively reduce the risk of reservoir prediction caused by marine carbonate heterogeneity, and provide scientific foundation for the prediction of high-frequency cyclic reservoirs of platform facies and platform margin subfacies in other marine carbonate sedimentary basins.

Multisource working condition recognition via nonlinear kernel learning and p-Laplacian manifold learning

Effectively utilizing information from multiple sources and fewer labeled operating condition samples from a sucker-rod pumping system for oil production can improve the recognition effects and engineering practicability. Nevertheless, this is a challenging energy environment scientific application research subject, and therefore, this study proposes an operating state recognition scheme that relies on multisource nonlinear kernel learning and p-Laplacian high-order manifold regularization logistic regress. Specifically, three measured features are selected and extracted, i.e., wellhead temperature signal, electrical power signal, and ground dynamometer cards, based on mechanism analysis, expert experience, and prior knowledge. Finally, we establish the operating condition recognition model to recognize by the multisource p-Laplacian regularization kernel logistic regress algorithm. The experimental data are derived from 60 wells of a common high-pressure and low-permeability thin oil reservoir block of an oil field in China. The corresponding trials highlight that our scheme outperforms traditional recognition methods by exploiting single-source and multiple-feature data. In the context of fewer labeled samples, the proposed method has a greater recognition effect, engineering practicability, and better model robustness than the existing schemes based on other high-order manifold learning, verifying our method's effectiveness.

Effect of Aquifer Strength and Gas-cap Size on Oil Recovery Efficiency in Thin-Oil Rim

Recovering oil from thin oil rim reservoirs depends on some factors such as the gas-cap size, thickness of initial oil column, aquifer strength, permeability anisotropy (kV/kH), and rock and fluid properties. The arbitrary selection of these factors by researchers during investigation limits the systematic assessment of the influence of these factors on hydrocarbon recovery from thin oil rim reservoirs. This work investigated the effect of aquifer strength, gas cap size, and permeability anisotropy on hydrocarbon recovery, using design of experiment (DOE) as a tool in the systematic selection of some of the factors that influence hydrocarbon recovery. A static model of the base case oil rim was built in Petrel. Using Eclipse simulator, two other reservoir models having different gas cap sizes from the base case were built. Forty-eight simulation cases were generated using the result from the design of experiment (DOE). The aquifer model used is a Fetkovich analytical aquifer model, and the aquifer volume factors used for this investigation are 0.7, 1.0, 1.5 and 2.5, while the gas cap sizes (m-factor) used are 0.5, 1.0 and 2.0. The permeability anisotropy used are 0.01, 0.05, 0.10 and 0.40. Each simulation case was made to run for a period of twenty years (20years) and the results for the Field Oil Efficiency (FOE), Field Water Production Total (FWPT) and Field Gas Production Total (FGPT) were obtained and analyzed. It was found from this study that, the oil percentage recovery will increase as the gas cap size is decreased, while the percentage gas and water recoveries will increase as the size of the gas cap is increased for a thin oil rim reservoir. Again, for a thin oil rim reservoir with gas cap size of 0.50 ≤ m ≤ 2.00, percentage recovery of gas, oil and water will increase with aquifer volume. Also, based on the result obtained, a thin oil rim reservoir with small to moderate gas cap size (0.5≤ m≤1.0) will yield higher oil recoveries irrespective of the kV /kH ratio.

ResNet and CWT Fusion: A New Paradigm for Optimized Heterogeneous Thin Reservoir Evaluation.

The endeavor to explore and characterize oil and gas reservoirs presents significant challenges due to the inherent heterogeneities that are further compounded by the existence of thin sand layers encapsulated in shale strata. This complexity is intensified by limited and low-resolution seismic data, missing critical well-log information, and inaccessible angle stack data. Conventional reservoir classification approaches have struggled to address these issues, primarily due to their limitations in handling missing data effectively and, hence, precise estimations. This study focuses on the characterization of thin, heterogeneous potential sands of the B-interval within the Lower Goru Formation, a proven gas reservoir in the Badin area. The reservoir sands with varying thicknesses are assessed in detail for their optimized description and field productions by handling challenges, including low seismic resolutions, heterogeneities, and missing data sets. An innovative solution is developed based on the integration of continuous wavelet transform (CWT) and machine learning (ML) techniques for the approximation of missing data sets, i.e., S-wave (DTS), along with enhanced elastic and petrophysical properties. The improved properties are augmented by the high resolution attained by CWT and captured variability more profoundly through the implication of residual neural networks (ResNet). The limitations of conventional approaches are harnessed by ML solutions that operate with limited input data and deliver significantly improved results in characterizing enigmatic thin sand reservoirs. The high-frequency petroelastic properties reliably determined the thin heterogeneous potential sand bodies and illuminated a channelized play fairway that can be tested for additional wells with low-risk involvement.

Detection of a CO2 plume by time-lapse analysis of Rayleigh-wave amplitudes extracted from downhole DAS recordings of ocean microseisms

Amplitudes of Rayleigh waves are known to decrease exponentially away from the surface. If elastic properties of the solid are stratified on a scale much smaller than the wavelength, the Rayleigh-wave amplitude at a given depth should also be affected by the formation properties at that depth: the softer the medium, the larger the amplitude. An increasingly widespread deployment of fiber-optic cables in wells makes it possible to record this depth variation of Rayleigh-wave strain amplitudes and their variations over time (due to changes of formation properties) using distributed acoustic sensing (DAS). To investigate this opportunity, we have explored temporal variations of downhole DAS amplitudes of ocean-generated Rayleigh waves during injection of CO2 into a water-saturated thin porous layer. Analysis of these data clearly shows changes of these amplitudes related to the CO2 injection. To understand these amplitude variations, we perform a theoretical analysis and numerical simulations, which explain our field observations. In particular, analysis of downhole DAS data and theoretical modeling show that Rayleigh-wave amplitudes measured with vertical fiber-optic cables can be used to detect thin layers in the subsurface. Furthermore, time-lapse analysis of these amplitudes indicates temporal changes of stiffness of these layers, such as changes in saturation or pressure of the fluid in a porous layer in the vicinity of the borehole. In particular, Rayleigh-wave amplitudes are sensitive to the presence in the vicinity of the wellbore of a CO2 plume created as a result of a small injection into a thin porous reservoir layer. Our analysis also shows that the effect of a thin layer on Rayleigh-wave amplitudes strongly depends on frequency so that at different frequencies the amplitude is affected by different combinations of elastic properties. This opens an opportunity to use amplitude variations with depth at different frequencies to separately estimate changes in bulk and shear moduli.

Application of Pre-Stack Geostatistical Inversion in Horizontal well Tracking of Thin Reservoir in well Area

Application of Pre-Stack Geostatistical Inversion in Horizontal well Tracking of Thin Reservoir in well Area

Optimization Study of Injection and Production Parameters for Shallow- and Thin-Layer Heavy Oil Reservoirs with Nitrogen Foam-Assisted Steam Flooding

Shallow- and thin-layer heavy oil reservoirs are characterized by their shallow burial, thin thickness, high viscosity, and scattered distribution. After years of steam injection development, several issues have emerged, including a highly comprehensive water cut in the reservoir and serious steam channeling. Therefore, there is an urgent need to change the development approach to enhance crude oil recovery. It has been discovered that developing heavy oil reservoirs through nitrogen foam-assisted steam flooding can effectively address the challenges encountered in pure steam development. This paper takes H Oilfield Block A as a case study, analyzes the geological characteristics and development status of the reservoir in this block, and predicts the recovery of steam injection development in this block using the injection-production characteristic curve method. Furthermore, by establishing a reservoir geological model and fitting it to the historical behavior of the target reservoir, the nitrogen foam-assisted steam flooding injection and production parameters were optimized. The optimal parameters are as follows: optimal steam injection intensity of 2.0 t/(d·ha·m), optimal production/injection ratio of 1.2:1, optimal nitrogen foam slug injection volume of 0.15 PV, optimal nitrogen/steam ratio of 2:1, and intermittent injection between 3 and 4 foam slugs. It is anticipated that this optimized scheme will result in a predicted increase in final recovery of 13.55%. The findings of this study hold significant importance in guiding the application of nitrogen foam-assisted steam flooding in shallow and thin heavy oil reservoirs.

Identification and plane distribution of thin reservoirs in the Middle Permian Qixia Formation in Shuangyushi, Northwest Sichuan

Identification and plane distribution of thin reservoirs in the Middle Permian Qixia Formation in Shuangyushi, Northwest Sichuan

Facies-controlled prediction of dolomite reservoirs in the Middle Permian Qixia Formation in Shuangyushi, northwestern Sichuan Basin

The Middle Permian Qixia Formation in the Shuangyushi area, northwestern Sichuan Basin, develops shoal-facies dolomite reservoirs. To pinpoint promising reservoirs in the Qixia Formation, deep thin shoal-facies dolomite reservoirs were predicted using the techniques of pre-stack Kirchhoff-Q compensation for absorption, inverse Q filtering, low-to high-frequency compensation, forward modeling, and facies-controlled seismic meme inversion. The results are obtained in six aspects. First, the dolomite reservoirs mainly exist in the middle and lower parts of the second member of Qixia Formation (Qi2 Member), which coincide with the zones shoal cores are developed. Second, the forward modeling shows that the trough energy at the top and bottom of shoal core increases with increasing shoal-core thickness, and weak peak reflections are associated in the middle of shoal core. Third, five types of seismic waveform are identified through waveform analysis of seismic facies. Type-I and Type-II waveforms correspond to promising facies (shoal core microfacies). Fourth, vertically, two packages of thin dolomite reservoirs turn up in the sedimentary cycle of intraplatform shoal in the Qi2 Member, and the lower package is superior to the upper package in dolomite thickness, scale and lateral connectivity. Fifth, in plane, significantly controlled by sedimentary facies, dolomite reservoirs laterally distribute with consistent thickness in shoal cores at topographical highs and extend toward the break. Sixth, the promising prospects are the zones with thick dolomite reservoirs and superimposition of horst–graben structural traps.

Prediction of Marine Thin Shale Gas Reservoir with Seismic Phase-Controlled Nonlinear Stochastic Inversion

Due to the complicated interference sources and low signal-to-noise ratio of seismic records, conventional seismic inversion methods are difficult to accurately identify shale gas reservoirs with a thickness of less than 10 m. This presents great challenges to shale gas exploration and development in China. Seismic phase-controlled nonlinear stochastic inversion (SPCNSI) is related to the heterogeneity of underground media. With the constraints of the stratigraphic sequence or seismic facies models, the minimum value between the seismic model and seismic record can be solved through iterative processes. Based on the solved acoustic velocity in formation, the constraints for SPCNSI can be formed with the matching relationship between target layers and different sequences in three-dimensional space. The prediction resolution of an unconventional reservoir can be effectively improved by combining logging, geological and seismic information. The method is suitable for predicting thin shale gas reservoirs in complex geological structures. In this study, SPCNSI was developed to predict the thin-layer marine shale gas reservoir in the southeast of Chongqing; the horizontal and vertical distribution characteristics were proven in the Longmaxi Formation and the Wufeng Formation; thin layers with a thickness of less than 7 m were also discovered. According to the results, three sets of potential development areas were determined by the inversion method, and the accuracy and reliability of the method were verified by logging and productivity testing.

Identification of interbedded gas hydrate and free gas using amplitude versus offset forward modelling

AbstractThe complex contacts between gas hydrate and free gas have been confirmed by gas hydrate pilot production in the Pearl River Mouth Basin, South China Sea. The laminated clay silt reservoirs have high amplitude reflections which may be filled with different saturations of gas hydrates, free gas and the coexistence between gas hydrate and free gas. To distinguish the variations of amplitude reflections caused by different reservoirs properties below the bottom simulating reflection, we combine the forward modelling, pre‐stack gathers with different incident angles and well log analysis to conduct the seismic responses. A number of geological models are established with variable saturations and different interfaces between gas hydrate and free gas. First, we analyse the seismic and well log responses at Sites W11, W01 and W17 near the production test area. Then, we perform the forward modelling to quantify the differences among seismic reflections with different saturations, thickness, incident angles and strata dips in free gas‐ or gas hydrate‐bearing geological models. We extract the seismic amplitudes along the bottom simulating reflection and other layers to compare with the amplitudes generated from forward modelling. The results indicate that the inclined intervals below the bottom simulating reflection have high amplitude, continuous reflection and polarity reversal which may be caused by thin gas reservoir and the interlayered gas hydrate and free gas with different saturations. The top interfaces of the gas hydrate‐ and free gas‐bearing layers show typical Class III amplitude versus offset and exhibit high amplitude reflections at seismic data with near, mid and far‐incident angles, which are easy to distinguish. Seismic response of far‐incident angle can be used to identify the coexistence of gas hydrate and free gas.

Geotechnological regulation of the development of oil fields with hard-to-recover reserves

Background: A significant proportion of the remaining oil reserves of the fields under development is confined to reservoir zones with low-permeability and undersaturated reservoir, thin reservoirs. Maintenance of oil production levels in such deposits is possible through methodological study and development of recommendations for optimizing and improving the development system, targeted application of technologies and methods for enhanced oil recovery. In turn, the methodological study for deposits with hard-to-recover reserves includes a systematic statistical and geological and technological analysis of the results of field development, an analysis of existing generally accepted methodologies, and theoretical studies. Thus, the creation of an integrated approach to regulating the development of oil fields, taking into account a detailed understanding of the geological structure, is an important task in the current state of the fields under development.
 Aim: The aim of the work is to develop an integrated approach to regulating the development of oil fields with hard-to-recover reserves based on methodological solutions of technological and statistical analysis, differentiation of research objects, retrospective analysis of the use of technologies and methods aimed at increasing oil recovery. The aim of the work is to form an integrated approach to regulating the development of oil fields with hard-to-recover reserves based on methodological solutions for geological-technological and geological-statistical analysis, differentiation of research objects, retrospective analysis of the use of technologies and methods aimed at increasing oil recovery.
 Materials and methods: Achieving this goal is possible using the following methods: statistical analysis, geological and field analysis, methodological solutions for studying the relationship "rock fluid", differentiation of research objects according to geological, geophysical and geological and field data. On the example of some stages, research algorithms are proposed.
 Results: A methodological solution is proposed for regulating the development of oil fields with hard-to-recover oil reserves.
 Conclusion: The proposed geotechnological approach to the development control will improve the technological efficiency of hydrocarbon reserves development due to a detailed understanding of the reservoir structure, differentiation into zones (areas) of the reservoir, study and analysis of their state of development, reasonable selection of priority and promising technologies and technical solutions to increase their production.

A Novel Inner Wall Coating-Insulated Oil Pipeline for Scale and Wax Prevention

During the production of deep oil and gas, scaling, waxing, hydrate ice plugging and other problems easily occur. To solve these problems, reducing the temperature loss of oil pipelines is a feasible method. In order to protect the outer wall coating from being damaged and losing its thermal insulation performance, this paper proposes a developed technology for a novel inner wall coating-insulated oil pipeline. A new temperature-resistant and heat-insulating material aerogel was optimized and developed, and it has an extremely low thermal conductivity of less than 0.055 W/m·K. The influence of different coating processes on the thermal insulation coefficient was analyzed, and a novel inner wall coating-insulated oil pipeline was developed. A testing and evaluation platform for its thermal insulation effect was built, and a finite element model was established to analyze the temperature field distribution. When the thickness of the inner coating was 0.5 mm, the thermal insulation effect of the new oil pipeline improved by about 29%. This technology could be widely used in the production of deep oil and gas, high salinity oil and water reservoirs, thin oil reservoirs, etc., to alleviate scaling and waxing phenomena.

Evaluating the impact of 4D seismic data artefacts in data assimilation

Time-lapse or 4D seismic data are important constraints in reservoir studies because they enable monitoring of saturation and pressure changes that result from hydrocarbon production. 4D seismic data have been quantitatively added, along with production data, in history matching or data assimilation procedures to reduce uncertainty and improve production forecasts. Before performing quantitative studies, it is important to ensure that the 4D seismic data are reliable, with minimal artefacts such as side-lobe effects that can disturb the identification of anomalies. In this work, we propose different ways of treating 4D seismic data in data assimilation for a real reservoir. Explicitly, we evaluated the impact on data assimilation results when considering different amounts of 4D information and three treatments to the identified artefacts. The treatments were: ignoring them, excluding them from data assimilation or defining no seismic changes at their locations. The results show that well and seismic matches are improved when 4D seismic data are assimilated, also improving the production predictions. Despite being a thin reservoir, assimilating two single-layer maps allowed us to predict relevant observed dynamic behaviour, such as the evolved gas trapped in the lower interval. Furthermore, when a treatment was applied to the artefacts, they produced better models than using a single two-layer map (with lower production errors and visually closer impedances to the observed data). Our recommendation is the assimilation of well and 4D seismic data, with the exclusion of unreliable information, for better life-cycle decisions.

Improved delineation of the Gassum Formation reservoir zones using seismic impedance inversions: implications for exploiting the Stenlille aquifer gas storage facility as a CO 2 storage demonstration site, onshore Denmark

A quantitative seismic interpretation of the Gassum Formation at the onshore aquifer gas storage near the Danish town of Stenlille is presented with its implications for exploiting the gas storage facility as a potential CO 2 demonstration site. Our objective was to better outline the reservoir heterogeneity of the Gassum Formation based on a 3D seismic volume and 20 wells available from the Stenlille gas storage facility. We derived new absolute and relative P-impedance inversion products, which are useful for delineating lithological distributions of thin sandstone reservoirs and shaly beds within the Gassum Formation. Our results broadly agree with previously published seismic interpretations, and build upon these by the identification of deviations in parts of the Gassum interval that should be considered in any subsequent development of a static reservoir model. Hence, this work is an important contribution to the planning of drilling new CO 2 injection wells as part of the development and management of the Stenlille CO 2 storage demonstration site. Nevertheless, we also recommend a modern seismic reprocessing of the 3D seismic data combined with newly acquired 2D data from the Stenlille structure as input into further quantitative seismic interpretation studies to refine reservoir characterization and reduce associated uncertainties. Supplementary material: video is available at https://doi.org/10.6084/m9.figshare.c.6662413

Evaluation and optimization of a horizontal well-triplet for CO2 plume geothermal harvest: Comparison between open and close reservoirs

Depleted oil/gas reservoirs can be used for CO2 sequestration and utilization; CO2 plume geothermal (CPG) production from a CO2 geological storage reservoir has emerged as a viable approach owing to its favorable thermodynamic properties. However, most oil/gas reservoirs are separated by faults into geological blocks, and the impact of these fault boundaries on CPG performance remains unclear. This study evaluated and compared the technical performances of a horizontal well-triplet placement and CPG operation in a thin geothermal reservoir between open and close boundaries. A meta-model simulation–optimization framework was also applied for the economic assessment of both systems. For each boundary system, 200 samples of the horizontal well-triplet design, including injection well overpressure, horizontal perforation length of injection and production wells, and distance between injection and production well, were derived from a 4D-parameter space constrained by particular ranges. These 200 samples of input parameters yielded 200 numerical models for the simulation of CPG operations. A suite of technical metrics, including lifespan, injected, produced, and stored CO2, recovered heat energy, and produced heat flux, were computed from the model simulations for technical performance evaluations. Meta models for economic objectives were developed based on the 200 input–output datasets and used in optimization. A multi-objective particle swarm optimization (MOPSO) approach was utilized to obtain the appropriate optimal designs of the well-triplet for the two boundary systems. The results indicated that performance of both systems was controlled by the well space, which was positively correlated to CO2 storage and total heat recovery but negatively to power plant capacity. High horizontal well lengths and overpressure facilitated CO2 storage, heat recovery, and plant capacity. The open system could generate much more overall profit than the close system owing to CO2 storage income.