Reservoir Production Performance Research Articles

An Artificial Neural Network Model for a Comprehensive Assessment of the Production Performance of Multiple Fractured Unconventional Tight Gas Wells

The potential of unconventional hydrocarbon resources has been unlocked since the hydraulic fracturing technique in combination with long horizontal wells was applied to develop this type of reservoir economically. The design and optimization of the fracturing treatment and the stimulated reservoir volume and the forecasting of production performance are crucial for the development and management of such resources. However, the production performance of tight gas reservoirs is a complicated nonlinear problem, described by many parameters loaded with uncertainty. The complexity of the problem influences and inspires the sophistication of the solution to be used. This paper proposed an artificial network model that allows for fast, extended, and accurate analyses of the production performance of multiple fractured unconventional tight gas wells. In the comprehensive approach developed, the reservoir rock parameters, the drainage area, and the hydraulic fracture parameters are treated as a variable input to the model. The analysis is no longer constrained by fixed “shoes box” geometry, and the values of the parameters defining the reservoir and stimulated volume are not limited to a few discrete values. The numerical experiment used to construct a database for model development was designed using a genetically optimized Latin hypercube sampling technique. A special approach was used in the preparation of “blind data”, which are crucial for truly reliable model verification. In the result, a developed tool offers an extended rock-fluid description, flexible model, and stimulated reservoir volume dimensioning and parameterization, as well as a high degree of applicability in sensitivity analysis and/or optimization.

The Selection of Optimal Gas Production Rate using Dynamic Reservoir Simulation in Field X

Indonesian government has targeted a gas production rate of 12 BSCFD by 2030 to balance the energy demands and the carbon emission reduction. To achieve this goal, a comprehensive evaluation of a gas field will be carried out regarding Recovery Factor, Stable Production Period (Plateau Time), Total Production Period, and Profits using simulation programme. Dynamic Reservoir Simulation is an integrated field development simulation that combines physics, mathematics, reservoir engineering, and computer programming to analyze and predict the wells performance or how fluid flows through reservoir rocks to the surface over time under various operating conditions. There are stages in the simulation include Reservoir Model Creation, Initialization, History Matching, and Production Performance Forecasting. This research is a continuation of static reservoir modeling research done by LEMIGAS, which started by reinitializing the model and ended by forecasting the production performance of field X using several gas production flowrate scenarios to find out the optimal gas production flowrate for Field X in ten years period. The simulation result showed that the best gas production flowrate for a ten-year period is 3 mmscfd. It gives 78,505% recovery factors, with cumulative profit of $40,915,872 USD over a plateau period of 6.6 years.

A novel framework for predicting non-stationary production time series of shale gas based on BiLSTM-RF-MPA deep fusion model

Shale gas, as an environmentally friendly fossil energy resource, has gained significant commercial development and shows immense potential. However, accurately predicting shale gas production faces substantial challenges due to the complex law of decline, nonlinear and non-stationary features in production data, which greatly repair the robustness of current models in predicting shale gas production time series. To address these challenges and improve accuracy in production forecasting, this paper introduces a novel and innovative approach: a hybrid proxy model that combines the bi-directional long short-term memory (BiLSTM) neural network and random forest (RF) through deep learning. The BiLSTM neural network is adept at capturing long-term dependencies, making it suitable for understanding the intricate relationships between input and output variables in shale gas production. On the other hand, RF serves a dual purpose: reducing model variance and addressing the concept drift problem that arises in non-stationary time series predictions made by BiLSTM. By integrating these two models, the hybrid approach effectively captures the inherent dependencies present in long and nonstationary production time series, thereby reducing model uncertainty. Furthermore, the combination of BiLSTM and RF is optimized using the recently-proposed marine predators algorithm (MPA) to fine-tune hyperparameters and enhance the overall performance of the proxy model. The results demonstrate that the proposed BiLSTM-RF-MPA model achieves higher prediction accuracy and demonstrates stronger generalization capabilities by effectively handling the complex nonlinear and non-stationary characteristics of shale gas production time series. Compared to other models such as LSTM, BiLSTM, and RF, the proposed model exhibits superior fitting and prediction performance, with an average improvement in performance indicators exceeding 20%. This innovative framework provides valuable insights for forecasting the complex production performance of unconventional oil and gas reservoirs, which sheds light on the development of data-driven proxy models in the field of subsurface energy utilization.

Time-dependent model for two-phase flow in ultra-high water-cut reservoirs: Time-varying permeability and relative permeability

For the ultra-high water-cut reservoirs, after long-term water injection exploitation, the physical properties of the reservoir change and the heterogeneity of the reservoir becomes increasingly severe, which further aggravates the spatial difference of the flow field. In this study, the displacement experiments were employed to investigate the variations in core permeability, porosity, and relative permeability after a large amount of water injection. A relative permeability endpoint model was proposed by utilizing the alternating conditional expectation (ACE) transformation to describe the variation in relative permeability based on the experimental data. Based on the time dependent models for permeability and relative permeability, the traditional oil-water two-phase model was improved and discretized using the mimetic finite difference method (MFD). The two cases were launched to confirm the validation of the proposed model. The impact of time-varying physical features on reservoir production performance was studied in a real water flooding reservoir. The experimental results indicate that the overall relative permeability curve shifts to the right as water injection increases. This shift corresponds to a transition towards a more hydrophilic wettability and a decrease in residual oil saturation. The endpoint model demonstrates excellent accuracy and can be applied to time-varying simulations of reservoir physics. The impact of variations in permeability and relative permeability on the reservoir production performance yields two distinct outcomes. The time-varying permeability of the reservoir results in intensified water channeling and poor development effects. On the other hand, the time-varying relative permeability enhances the oil phase seepage capacity, facilitating oil displacement. The comprehensive time-varying behavior is the result of the combined influence of these two parameters, which closely resemble the actual conditions observed in oil field exploitation. The time-varying simulation technique of reservoir physical properties proposed in this paper can continuously and stably characterize the dynamic changes of reservoir physical properties during water drive development. This approach ensures the reliability of the simulation results regarding residual oil distribution.

Optimization of CO2 EOR and geological sequestration in high-water cut oil reservoirs

In terms of the collaborative optimization of CO2 flooding for Enhanced Oil Recovery (EOR) and CO2 sequestration, previous studies have co-optimized both cumulative oil production and CO2 sequestration by various algorithms. However, these solutions fail to optimize the CO2 injection schemes for high-water cut oil reservoirs. This paper presents an optimization methodology for CO2 flooding and sequestration in high-water cut oil reservoirs. The production optimization was carried out by adjusting the injection and production rate. To solve the proposed objective functions, the simultaneous perturbation stochastic approximation (SPSA) algorithm is applied in this paper, and the CMG-GEM module is utilized to simulate the reservoir production performance. A typical high-water cut reservoir in the Shengli oilfield was used to verify the feasibility of the presented methodology. In this paper, the production performance and net present value (NPV) for continuous gas injection under different water cuts were analyzed. The optimal timing of transforming from water flooding to gas displacement for the high-water cut reservoir was optimized. In addition, the optimal water–gas ratios for Water-Alternating-Gas (WAG) flooding were determined. The sensitivity of NPV to gas injection price and carbon subsidy was analyzed. The results show that when the gas price is 0.178 $/m3 and the carbon subsidy is 0.0169 $/m3, the optimal timing of transforming from water flooding to gas injection should be earlier than the time when the water cut is 0.82. Through the combination of NPV, cumulative oil production rate, and CO2 sequestration volume for WAG flooding, the optimal WAG ratio should be 1:2. The presented method in this paper considers various economic indicators and can optimize CO2 flooding and sequestration in high-water cut oil reservoirs efficiently, which can provide some guidance for the design of CO2 flooding schemes in high-water cut oil reservoirs.

The magnitudes of multi-physics effects on geothermal reservoir characteristics during the production of enhanced geothermal system

The multi-physics coupling process during the heat extraction from enhanced geothermal system, encompassing thermo(T)-hydro(H)-mechanical(M)-chemical(C) interactions, plays a pivotal role in changing geothermal reservoir characteristics. However, a comprehensive quantitative assessment of these multi-physics behaviors has been lacking. In this study, a novel approach was proposed to calculate the magnitude of mechanical, chemical, strong mechanical-chemical coupling, and weak mechanical-chemical coupling effects on the variations of reservoir characteristics. In particular, mechanical-chemical coupling effects are quantified for the first time. They are obtained by the fracture aperture difference results across five distinct coupling models (thermo-hydro, thermo-hydro-chemical, thermo-hydro-mechanical, partially-coupled four-field, and fully-coupled four-field models). The findings indicate that mechanical effects lead to an increase in fracture aperture, while chemical effects contribute to its reduction under underbalanced injection conditions. Strong mechanical-chemical coupling effects, exhibiting a negative correlation with chemical effects, conversely result in a diminished fracture aperture. The influences of these effects are investigated from the temporal and spatial perspectives. Temporally, mechanical effects dominate early production while chemical effects become prominent in later stages. Spatially, there mainly exists two zones when stable production: a mechanical-controlled region surrounding injection wells, and a chemical-controlled area distant from the injection wells. Furthermore, sensitivity analysis of injection concentration indicates its alternation changes the reservoir traits and production performance by modifying the magnitudes of chemical and mechanical-chemical coupling effects. This quantification of multi-physics effects offers insights into optimizing injection strategies for better geothermal development. The approach could hold promising potential in other geo-energy scenarios like carbon and hydrogen storage in reservoirs.

A New Index to Evaluate the Seepage Capacity of Water-Wet Sandstone Reservoirs

The water-wet sandstone reservoirs in the Liushagang Formation of the Beibuwan Basin has tremendous exploration potential for oil reserves in the South China Sea. However, owing to the weak correlations between petrophysical parameters and oil productivity, the production performance and seepage capacity showed significant differences in various reservoirs. The production performance of the field was evaluated by characterizing the mobility of two-phase flow through the concept of classical global mobility. However, global mobility still does not consider differential displacement pressure (DDP) and movable oil saturation (MOS). Therefore, a new index based on the Li–Horne model was established to simultaneously evaluate the seepage capacity of water-wet sandstone reservoirs, accounting for DDP and MOS. The detailed work stemming from the model included selecting water-wet sandstones with different lithologies and comparing the displacement effects of different flooding systems, oil viscosities, injection water salinities, pressure conditions, and MOS in multiple sets of parallel core samples. Finally, the new index was validated. A strong correlation was found between the new index and oil productivity per-unit differential pressure through displacement analysis of rock/oil/water, rock/oil/gas, and rock/oil/polymer systems on several core samples. The developed index for evaluating seepage capacity is suitable for different sandstones, flooding systems, oil viscosities, injection water salinities, pressure conditions, and productivity test data, thus providing insight into the production performance and seepage capacity parameters of water-wet sandstone reservoirs.

Well Test Analysis for a Well in Gas Storage Reservoirs With the Formation Containing High Salinity Water

Abstract The production capacity of the gas wells is seriously affected by salt deposition during the injection and production process for underground gas storage with high salt content, so it is necessary to predict the production performance through well test technology. However, the existing well test analysis methods cannot be reliably used to interpret the well test data affected by salt deposition phase change and high-speed non-Darcy flow during the injection and production process. Therefore, this paper first determines the relationship between salt deposition and temperature and pressure through flash calculation of phase equilibrium of saltwater and hydrocarbon system, then establishes a porosity and permeability model considering the effect of salt deposition, and further establishes a high-speed injection-production well test analysis model considering the effect of salt deposition in combination with Forchheimer’s percolation law. Finally, the model is solved by numerical method, and the dynamic changes of reservoir pressure and salt deposition are simulated and calculated. The results show that the higher the salinity of formation water is, the greater the risk of salt deposition in the reservoir is, and the permeability of the reservoir will significantly decrease after salt deposition occurs; the non-Darcy flow effect will aggravate the risk of salt deposition in the reservoir. The research results provide a theoretical method for the evaluation of reservoir parameters and production performance prediction of salt gas storage reservoirs.

Assessing the accuracy of empirical decline curve techniques for forecasting production in unconventional reservoirs: a case study of Haynesville, Marcellus, and Marcellus Upper Shale

Decline curve analysis (DCA) is a widely used method to estimate the production performance and ultimate recovery of conventional and unconventional reservoirs. Due to the unconventional nature of shale wells, traditional decline curve methods are not ideal for analyzing their production decline behavior. In response, different empirical methods have been developed and used which rely on different mathematical and statistical approaches and can result in varying forecasts.This study compares fourteen decline curve methods, along with the traditional Arps method, in terms of their ability to match production history, sensitivity to data size, effect of flow type, production forecast, and ultimate recovery estimation.The methods were tested on three wells from Haynesville Shale (Lorikeet Field), Marcellus Shale (Ostrich Field), and Marcellus-Upper Shale (Penguin Field) respectively. The study concludes that each method may be useful in different cases, and engineers should choose the method that best models their wells based on their specific characteristics and circumstances. Recommendations were also provided for an effective evaluation of uncertainty and application of DCA. The primary objective of this study is to improve the accuracy and reliability of DCA predictions for different reservoir types with different declining modes.

Experimental study on the mechanism of five point pattern refracturing for vertical & horizontal wells in low permeability and tight oil reservoirs

Low permeability oil reservoir has the characteristics of low porosity and low permeability. The initial fracturing can effectively improve the recovery of the reservoir, but the physical mechanism of refracturing to improve the recovery is still lack of systematic research. In this paper, the refracturing effect of low permeability reservoirs under the condition of five point well pattern is clarified; the refracturing mechanism of vertical-horizontal well combination is revealed; the reservoir production performance characteristics under different soak time conditions are analyzed. It is found that: (a) after 1st fracturing, the area between the two fractures still has a high residual oil, which is the material basis for refracturing. (b) After refracturing, there are secondary fractures connecting the main fractures. The crude oil in the low permeability reservoir can flow not only to the main fracture and horizontal wellbore, but also to the secondary fractures. This leads to the effective reduction of oil saturation between the main fractures. (c) The influence of soak time on cumulative oil production is obvious. With the increase of soak time, the cumulative oil production increases significantly.

Investigating tight oil reservoir production performance: Influence of geomechanical parameters and their distribution

Geomechanical properties have a prominent influence on reservoir stresses, which consequently reduce permeability and porosity with pressure depletion. These properties significantly affect the accuracy of reservoir modeling and recovery calculation, but have not been fully studied; therefore, more work is needed. Full field data and laboratory measurements are included in the study. The work involves deriving an equation by combining experimental data for permeability and porosity reduction during a change in stress with the poroelastic stress equation to investigate the impact of Poisson's ratio and Young's modulus on the reduction of permeability and porosity with pressure depletion. Most simulation studies assume constant geomechanical properties across the entire reservoir or for each individual reservoir layer. In this study, three approaches were considered for the Poisson's ratio and Young's modulus in the reservoir model: 1) constant average values assigned to the entire reservoir, 2) constant average values assigned to each layer, and 3) constant values assigned to each grid block. The validity of the model results was checked by history matching with production and pressure data. For the studied tight reservoir, the Poisson's ratio and Young's modulus significantly affected the permeability and porosity reduction with pressure depletion. The impact of Young's modulus was more pronounced than Poisson's ratio. The simulation results for oil rate, cumulative oil production, and water cut for the reservoir and a selected well showed that applying the three suggested geomechanical approaches resulted in a substantial discrepancy in the model outcome. In general, the coupled model with the mapped geomechanical properties resulted in lower oil and water production. This is attributed to the large values of mapped Young's modulus in parts of the reservoir which resulted in large permeability reduction and subsequently lower oil and water production is expected. In contrast lower Young's modulus per layer was obtained due to averaging process. Poisson's ratio effect on fluid production is much less significant due to its small effect on permeability reduction with depletion. Similarly, the adoption of different geomechanical property values for each layer yielded a relatively lower production outcome than when using a constant value for the entire reservoir. The study indicates the importance of considering the detailed description of the reservoir geomechanical properties to obtain reliable simulation results.

Improving the Production Performance of Low-Permeability Natural Gas Hydrate Reservoirs by Radial Water Jet Slotting and Grouting in a Horizontal Well

Most natural gas hydrate (NGH) reservoirs have poor permeability characteristics, which is unfavorable to fluid flow and gas production. To enhance gas production, a new method of radial water jet slotting and grouting (RWJSG) was proposed to reconstruct the formation around horizontal wellbores of a horizontal well. To evaluate the effectiveness of the proposed method, a three-dimensional (3D) gas production model was constructed with reference to the NGH reservoir at the SH2 site in the South China Sea (SCS). The results show that RWJSG can effectively enhance the gas recovery of the horizontal well. Compared with an unreconstructed case, the hydrate dissociation efficiency, cumulative gas production, and average ratio of gas to water production in the RWJSG case are increased by 121.0, 116.3 and 46.1%, respectively, during the 720-day production period. RWJSG can enlarge reservoir exposed area, promote pressure drop transfer, and improve gas/water flow near the wellbore. In addition, the effect of increasing production mainly depends on the slot radius and number. Within a certain range, the decrease in slot spacing and increase in slot filler permeability have positive effects. For the reservoir at SH2 site, the scheme with a radius of 5 m, a spacing of 5 m, a number of 5 and a permeability of 500 mD could achieve remarkable stimulation effect. This work provides ideas and guidance for stimulation of horizontal wells in NGH reservoirs by RWJSG.

Numerical analysis on gas production performance by using a multilateral well system at the first offshore hydrate production test site in the Shenhu area

Multilateral well technique is a promising approach to enhance gas recovery, especially in heterogeneous hydrate reservoirs with underlying free gas. However, little is known about the optimal deployment for multilateral wells on hydrate production. Herein, a 3D numerical model for predicting the combined production performance of hydrate reservoirs by using multilateral wells is proposed. The results indicate that the horizontal branch deployed at the interface between three-phase layer and free gas layer shows the best production potential when one branch is available. Then, effects of geometric parameters including branch deployment location, spacing, length, phase angle, and branch number on production behaviors are analyzed through orthogonal designs. The analysis shows dual-branch and quad-branch scenarios are most influenced by deployment location and branch length, and the corresponding optimal combinations are suggested respectively. By contrast, dual-lateral wells have the most favorable yield-increasing effects due to the synergistic depressurization, of which total gas production and productivity index are 123% and 81% higher than those of vertical wells. Additionally, well interference may exist between branches, which is unfavorable for gas recovery between the lateral branches and exacerbates with an increase in branch number. This research gives an in-depth insight into the industrialized co-production of hydrate and free gas.

Coupling effect of critical properties shift and capillary pressure on confined fluids: A simulation study in tight reservoirs

Critical properties shift and large capillary pressure are important contributors for the phase behavior altering of nanopore fluid. However, the effects of critical properties shift and large capillary pressure on the phase behavior are ignored in traditional compositional simulators, leading to inaccurate evaluation results of tight reservoirs. In this study, phase behavior and production of confined fluid in nanopores are studied. First, we developed a method for coupling the effect of critical properties shift and capillary pressure into the vapor-liquid equilibrium calculation base on Peng-Robinson equation of state. Second, a novel fully compositional numerical simulation algorithm considering effect of critical properties shift and capillary pressure on phase behavior is accomplished. Third, we have discussed the alterations of critical properties shift effect, capillary pressure effect and coupling effect on the composition of oil and gas production in detail. The critical properties shift and capillary pressure effects on oil and gas production in tight reservoirs are analyzed quantitatively through four cases, and the influences of the two effects in oil/gas production are compared. Based on the fully compositional numerical simulation, the simulator can rigorously simulate the impacts of component changes during production. The simulation results show that both the critical properties shift effect and the capillary pressure effect reduce the bubble point pressure of Changqing shale oil, and the influence are more prevalent in pores of smaller radius. In pores is larger than 50 nm, the phase behavior altering of the fluid can be ignored. In addition, we devised four cases to comprehensively investigate the effects of critical properties shift and large capillary pressure on production performance of tight reservoirs. The comparisons between the four cases show that the capillary pressure effect impacts the reservoir production performances greater than the critical properties shift effect, such as higher oil production, higher GOR, and lower content of lighter component and higher content of heavier component in the residual oil/gas. The results of coupling effects indicate that the critical properties shift effect would suppress the effect of the capillary pressure effect. In particular, the difference between the simulation results of the coupling effects and the base case is smaller than that between the simulation results of the capillary pressure effect and the base case.

A critical review of self-diverting acid treatments applied to carbonate oil and gas reservoirs

Carbonate reservoirs generally achieved relatively low primary resource recovery rates. It is therefore often necessary to clean those reservoirs up and/or stimulate them post drilling and later in their production life. A common and basic carbonate reservoir cleanup technique to remove contaminating material from the wellbore is acidizing. The efficiency of acid treatments is determined by many factors, including: the type and quantity of the acid used; the number of repeated treatments performed, heterogeneity of the reservoir, water cut of the reservoir fluids, and presence of idle zones and interlayers. Post-treatment production performance of such reservoirs frequently does not meet design expectation. There is therefore much scope to improve acidizing technologies and treatment designs to make them more reliable and effective. This review considers acid treatment technologies applied to carbonate reservoirs at the laboratory scale and in field-scale applications. The range of acid treatment techniques commonly applied are compared. Differences between specific acid treatments, such as foamed acids, acid emulsions, gelled and thickened acid systems, targeted acid treatments, and acid hydraulic fracturing are described in terms of the positive and negative influences they have on carbonate oil production rates and recovery. Opportunities to improve acid treatment techniques are identified, particularly those involving the deployment of nanoparticles (NP). Due consideration is also given to the potential environmental impacts associated with carbonate reservoir acid treatment. Recommendations are made regarding the future research required to overcome the remaining challenges pertaining to acid treatment applications.

A coupled thermo-hydro-mechanical-chemical model for production performance of oil shale reservoirs during in-situ conversion process

A coupled thermo-hydro-mechanical-chemical model for production performance of oil shale reservoirs during in-situ conversion process

Research progress in natural gas hydrate reservoir stimulation

Natural gas hydrate (hereinafter referred to as hydrate) is a kind of future energy with great potential. At present, the apparent factor hindering commercial hydrate development is the unqualified gas production rate, so it is necessary to research stimulation means from the perspective of hydrate exploitation method, and reservoir stimulation technology is particularly important. After systematically reviewing hydrate reservoir stimulation theories and technologies, this paper divides the field of reservoir stimulation into three directions, i.e., hydraulic fracturing, near-well stimulation and chemical stimulation, summarizes the main research results, problems and challenges in these three directions, and carries out discussion and prospect. And the following research results are obtained. First, rapid progress has been made in the research of hydraulic fracturing and it results have verified the fracability of hydrate deposits. It is revealed that the fracturing mechanism of hydrate deposits is similar to the tensile failure of rocks. It is indicated that fractures can still make contribution to permeability improvement after they closed under confining pressure, which is beneficial to secondary opening. In addition, the effects of in-situ stress and fracturing fluid on fracturing behaviors of hydrate deposits are analyzed, the numerical model of fracturing process is established, the mechanisms of hydraulic fractures to improve the depressurization and heat injection effects of hydrate reservoirs are analyzed, and the improvement effects of hydraulic fractures, as high-permeability channels on gas production rate and other key production indexes are clarified. Second, the research of near-well stimulation reveals the washout mechanisms and laws of high-pressure water jet on hydrate deposits. It is verified by numerical simulation that water jet slotting, circumferential grouting column and stratified split grouting can effectively improve the production performance, but the research is in the stage of establishing gas production model to evaluate the stimulation effect and the feasibility and effectiveness needs verifying. Third, as for chemical stimulation, the potential of CO2 caprock reconstruction and methanol huff and puff to improve the production performance of hydrate reservoirs is explored, and the feasibility of CO2 caprock reconstruction and storage is analyzed. In conclusion, to deal with current problems and challenges, it is necessary to strengthen the construction of the reservoir stimulation theory and technology system with hydraulic fracturing as the leading role, near-well reservoir stimulation as the auxiliary and chemical stimulation as the supplement, so as to accelerate the industrialization process of hydrate resources.

Efficient Optimization of Energy Recovery From Geothermal Reservoirs With Recurrent Neural Network Predictive Models

AbstractImproving the long‐term energy production performance of geothermal reservoirs can be accomplished by optimizing field development and management plans. Reliable prediction models, however, are needed to evaluate and optimize the performance of the underlying reservoirs under various operation and development strategies. In traditional frameworks, physics‐based simulation models are used to predict the energy production performance of geothermal reservoirs. However, detailed simulation models are not trivial to construct, require a reliable description of the reservoir conditions and properties, and entail high computational complexity. Data‐driven predictive models can offer an efficient alternative for use in optimization workflows. This paper presents an optimization framework for net power generation in geothermal reservoirs using a variant of the recurrent neural network (RNN) as a data‐driven predictive model. The RNN architecture is developed and trained to replace the simulation model for computationally efficient prediction of the objective function and its gradients with respect to the well control variables. The net power generation performance of the field is optimized by automatically adjusting the mass flow rate of production and injection wells over 12 years, using a gradient‐based local search algorithm. Two field‐scale examples are presented to investigate the performance of the developed data‐driven prediction and optimization framework. The prediction and optimization results from the RNN model are evaluated through comparison with the results obtained by using a numerical simulation model of a real geothermal reservoir.

Relationship between normalized permeability and resistivity index in hydrate-bearing sediments: fractal model and numerical simulation

SUMMARYPermeability is a critical factor in evaluating the fluid flow capacity and production performance of natural gas hydrate reservoirs. The similarity of electrical conduction and hydraulic flow makes it possible to predict reservoir permeability using electrical data. Clarifying the relationship between the permeability and resistivity of sediments with different hydrate growth habits contributes to the efficient exploration and development of natural gas hydrate resources. In this work, normalized permeability and the resistivity index models for grain-coating (GC) and pore-filling (PF) hydrates are developed based on the fractal geometry theory, forming a new relationship between normalized permeability and resistivity index. The empirical exponent is determined by fractal dimension. Meanwhile, we selected five sets of 3-D computed tomography (CT) images of quartz sand with different particle sizes, GC and PF hydrate digital rocks are constructed using random simulation methods. The numerical simulation of permeability and resistivity index is carried out, based on the pore microstructure images, the box counting method was used to calculate the fractal dimension and analyse the relationship between pore space and transport paths. Furthermore, the pore radius, throat radius and pore connection number are extracted through the pore network method to study the evolution of pore space. The results show that the tortuosity fractal dimension is a critical parameter in the relationship between normalized permeability and resistivity index. The proposed analytical expressions are validated by laboratory and well log data, and the exponent ranges cover existing hydrate permeability–resistivity index data. The models provide the possibility to predict the normalized permeability of hydrate reservoirs based on electrical data alone.

Structural core observations in a siliciclastic reservoir-scale framework

Abstract Detailed knowledge of subseismic structures and their influence on reservoir production performance is important for optimal reservoir management. Predicting subseismic structures from seismic-scale structural interpretations is inherently difficult without the use of core data. Cores allow direct measurements of porosity and permeability of deformed rocks and enable researchers to make detailed investigation of deformation mechanisms and cementation processes. Frequency, distribution and sometimes orientation of planar structures can be constrained. Such observations are then used together with location relative to seismically mapped fault and fold structures, and with respect to lithology and stratigraphy. However, a significant gap exists between the scale of core observation and the size of structures mappable from seismic data. Bridging this gap requires a sound general understanding of the different structures that occur in reservoirs, which, in addition to faults, includes drag folds, veins, fractures and the many types of deformation bands that can exist in porous rocks. Proper understanding of such subseismic structures is primarily based on outcrop-based observations and analyses, aided by physical experiments and numerical modelling. We stress that integrating such cutting-edge knowledge with core, seismic and other case-specific subsurface data in an appropriate tectonic context is paramount for realistic reservoir characterization and successful reservoir management.