Reservoir Boundaries Research Articles

Geophysical analysis to delineate a Class-I AVO prospect in the offshore east coast of India: A case study

Characterization of deep-water reservoirs poses enormous challenges to interpreters because of its inherent complexity. Therefore, defining reservoirs' extent and predicting their properties in absence of drilled well or away from drilled wells has always been difficult. In deeper targets, the sensitivity of seismic amplitude to fluid change gets considerably reduced, therefore detection of fluid and their contact remains challenging. In such a case, the application of extended elastic impedance can be helpful in the delineation of prospective reservoirs and detection of fluid contact. This is demonstrated with a case study of a Miocene slope fan prospect in the deepwater Mahanadi basin on the east coast of India. The prospect is typical Class-I in terms of amplitude variation with offset where the presence of fluid is hard to identify in conventional full-stack data. An appropriate extended elastic impedance attribute for fluid has been generated and interpreted to define the reservoir boundary and detect fluid contact. The amplitude of the fluid attribute map is corrected for tuning effect as there are variations in reservoir thickness across the area. Additionally, in order to detect fluid contact, a common contour binning technique has been applied which helps to locate the depth contour where possible fluid contact could be present. The case study has added significant values in de-risking a Class-I prospect without any anomalous amplitude increase with offset.

Supervised machine learning application of lithofacies classification for a hydrodynamically complex gas - condensate reservoir in Nam Con Son basin

Conventional integration of rock physics and seismic inversion can quantitatively evaluate and contrast reservoir properties. However, the available output attributes are occasionally not a perfect indicator for specific information such as lithology or fluid saturation due to technology constraints. Each attribute commonly exhibits a combination of geological characteristics that could lead to subjective interpretations and provides only qualitative results. Meanwhile, machine learning (ML) is emerging as an independent interpreter to synthesise all parameters simultaneously, mitigate the uncertainty of biased cut-off, and objectively classify lithofacies on the accuracy scale.
 In this paper, multiple classification algorithms including support vector machine (SVM), random forest (RF), decision tree (DT), K-nearest neighbours (KNN), logistic regression, Gaussian, Bernoulli, multinomial Naïve Bayes, and linear discriminant analysis were executed on the seismic attributes for lithofacies prediction. Initially, all data points of five seismic attributes of acoustic impedance, Lambda-Rho, Mu-Rho, density (ρ), and compressional wave to shear wave velocity (VpVs) within 25-metre radius and 25-metre interval offset top and base of reservoir were orbitally extracted on 4 wells to create the datasets. Cross-validation and grid search were also implemented on the best four algorithms to optimise the hyper-parameters for each algorithm and avoid overfitting during training. Finally, confusion matrix and accuracy scores were exploited to determine the ultimate model for discrete lithofacies prediction. The machine learning models were applied to predict lithofacies for a complex reservoir in an area of 163 km2.
 From the perspective of classification, the random forest method achieved the highest accuracy score of 0.907 compared to support vector machine (0.896), K-nearest neighbours (0.895), and decision tree (0.892). At well locations, the correlation factor was excellent with 0.88 for random forest results versus sand thickness. In terms of sand and shale distribution, the machine learning outputs demonstrated geologically reasonable results, even in undrilled regions and reservoir boundary areas.

The CORRELATION BETWEEN 3-D MAGNETOTELLURIC INVERSION MODEL WITH DRILLING DATA IN PATUHA GEOTHERMAL FIELD

The Patuha geothermal field is located in West Java Province, Indonesia and developed by state owned company PT Geo Dipa Energi (Persero). The Commercial Operation Date (COD) for Patuha was in September 2014 with plant capacity of 1x60 MW. Until now, Patuha Unit I geothermal field has been running for almost 7 years. The current production wells have experienced a natural decline, which is showed by a reduction in production capacity to the initial production. This causes the steam supply to the Power Plant Unit I to be not optimal, so a make-up well program is needed. Furthermore, to support the addition of electricity production capacity from geothermal energy in Indonesia, the development of the Patuha Geothermal Field is planned to be carried out for the next Power Plant Unit’s expansion (Unit 2 and Unit 3). Nevertheless, determining the location for both make-up and development drilling might still pose high risks. This is especially because the development area (where production and injection wells are located) is only concentrated in the eastern area of the contract area. Geophysical data especially Magnetotelluric (MT) has an indispensable role considering the limited data and the limited number of existing wells that cover the entire Patuha prospect area. To understanding the subsurface feature and see the correlation between MT model with well results in Patuha Geothermal Field, MT and TDEM survey were conducted in the eastern and western parts of Patuha area with total 100 stations. Considering the complexity of the subsurface condition in volcanic area, 3-D inversion of the MT data will be the most representative approach to investigate geothermal system in Patuha Geothermal Field. An obvious subsurface resistivity distribution revealed by the 3-D inversion showed a good agreement with well results especially in mapping the temperature distribution both vertically and horizontally. Generally, the resistivity distribution consists of a conductive zone (1–10 ohm-m) at the shallow part overlying a reservoir zone with a rather higher resistivity range (20–60 ohm-m). The conductive zone (<10 ohm-m) is correlated with Base of Conductor (BOC) of the wells that indicated by the presence of the argillic mineral. Meanwhile, the resistivity value around 15-20 ohm-m is correlated with Top of Reservoir of the production or injection well which is characterized by the presence of a convective temperature. In addition, from the results of resistivity mapping there is a very good correlation also in determining of reservoir boundary which is characterized by the presence of reverse temperature from the well. These results can be used as a guidance for better development strategy and drilling prognosis for the next drilling campaign especially in the area which limited number of wells.

Pore pressure prediction using seismic acoustic impedance in an overpressure carbonate reservoir

The drilling engineers favor a quantifiable understanding of the subsurface overpressure zones to avoid drilling hazards. The conventional pore pressure estimation techniques in carbonate reservoirs are prone to uncertainties that affect the calculated pore pressure model resolution and are still far from satisfactory. Basically, in carbonate reservoirs, the effect of chemical process and cementation on porosity is more important than the mechanical compaction, so the conventional pore pressure prediction methods based on the normal compaction trend mostly do not provide acceptable results. Using the conventional methods for carbonate reservoirs can yield large errors, even suggesting a reduction in abnormal pressure in overpressure zones where considerable attention must be paid. Conventional methods need to model density and velocity to calculate the effective and overburden pressures. Converting acoustic impedance to density and velocity is always associated with errors and generally provides low resolution, which adds substantial uncertainties to the pressure prediction. Although pore pressure measurements are usually associated with low resolution, additional error-prone steps can be dropped if used directly. This research outlines the pore pressure estimation of a famous Iranian carbonate reservoir using direct acoustic impedance without inverting it to density and velocity. Finally, this method gives acceptable results in carbonate formations compared to the results of the Repeat Formation Test (RFT) in this region. The results show a zone of overpressure between the two low-pressure intervals of the carbonate reservoir. This result can be of great help in determining reservoir boundaries as well as in planning for drilling trajectory for new wells. Furthermore, the pore pressure estimation results also show pressure reduction in the central part of the seismic section. The proposed approach is a viable alternative to the conventional method and is in line with the geological field report, where the ratio of hydrocarbon potential of total rock on the reservoir sides is higher than its middle part. In this study, we want to emphasize that the calibrated function obtained in our area can be used in similar basins with carbonate reservoirs.

Hydrocarbon dynamic field division and its relevance to oil and gas exploration for Paleogene reservoir in Lufeng Depression

Significant breakthroughs have been achieved in the exploration of Paleogene reservoirs in the Lufeng Depression. However, as drilling depth is becoming greater, the discovered oil and gas reservoirs show signs of transition from conventional to unconventional accumulations, and the identification of conventional and unconventional reservoir boundaries is of particular significance. Herein, the hydrocarbon dynamic field boundaries in the Lufeng Depression are comprehensively identified by the geological drilling result method, the sandstone pore throat radius critical value discrimination method and the dry layer drilling rate variation method; then, the hydrocarbon dynamic field is divided and the characteristics and differences of hydrocarbon accumulations in each hydrocarbon dynamic field are compared. The results show that the buoyancy-driven hydrocarbon accumulation depth in the Lufeng Depression is between 3,500-4,000 m, and the hydrocarbon accumulation depth limit is about 5,800 m. The focus of research on Paleogene oil and gas exploration in the Lufeng Depression should be placed on conventional oil and gas reservoirs in the free dynamic field and tight oil reservoirs in the reformed dynamic field. As for the Enping Formation and Upper Wenchang Formation, efforts should concentrate on conventional oil and gas reservoir exploration, and the tight reservoir of Lower Wenchang Formation should be explored in the high fracture density area in C-4 and C-8 well blocks and the west of C-8 well block of the Lufeng 13 sag. The research results of this paper are of great value in further increasing oil and gas production and the explorarion of reservoirs in the Lufeng Depression. Cited as: Ma, K., Pang, H., Zhang, L., Huang, S., Huo, X., Chen, J. Hydrocarbon dynamic field division and its relevance to oil and gas exploration for Paleogene reservoir in Lufeng Depression. Advances in Geo-Energy Research, 2022, 6(5): 415-425. https://doi.org/10.46690/ager.2022.05.06

Experimental investigation on the recovery performance and steam chamber expansion of multi-lateral well SAGD process

Multi-lateral well SAGD process is a newly proposed recovery process in recent years, in which a multi-lateral well is applied to replace the horizontal well in classic SAGD process. In this paper, a three-dimensional physical model is applied to simulate the recovery performance of multi-lateral well SAGD process in heavy oil reservoirs. First, on the basis of Pujol-Boberg similarity criterion, the Forchheimer's law is introduced to deal with the similarity of model permeability in 3D experiment. Thus, from the actual properties of Long Lake heavy oil reservoir, the lab scale experimental parameters are obtained. Then, by using a multi-lateral wellbore model, four scaled 3D SAGD experiments are performed, including one conventional dual horizontal well SAGD experiment (base case) and three multi-lateral well based SAGD experiments. From the experimental observation, the advantages of multi-lateral well are discussed from liquid production and steam chamber expansion. Finally, by the collected images, the distribution of residual oil saturation after SAGD process is also discussed. Results indicate that the introduction of Forchheimer's law can effectively handle with the problem of kinetic similarity damage caused by high permeability during a 3D experiment. Compared with the conventional dual horizontal well SAGD process, the application of multi-lateral well can increase the oil recovery factor by above 15%. To some extent, the application of multi-lateral well can increase the duration time of plateau stage or wind down stage. Simultaneously, compared with the single application of multi-lateral well in SAGD well pair, a dual multi-lateral well SAGD process has a higher expansion rate of steam chamber and a shorter recovery time. For steam chamber, under the dragging mechanism of branch wellbore, the shape of steam chamber is a “inverted trapezoid” shape instead of the “inverted triangle” shape for conventional dual horizontal well configuration. Under the effect of branch wellbore, steam chamber can effectively reach to the reservoir boundary and increase the volume of steam chamber. The residual oil saturation mainly distributed around the reservoir boundary, which is far from the main wellbore and branch wellbore. This paper further clarifies the EOR mechanisms and steam chamber expansion rules of multi-lateral well SAGD process.

Вычисление перетоков флюида между скважинами в фильтрационной модели разработки нефтяного пласта с помощью линий тока

To analyze the waterflooding system of an oil reservoir and predict the effectiveness of geological and technical measures, information is required on the distribution of injection rate between the reacting production wells and the reservoir boundary. The most reliable methods for calculating these characteristics are methods based on hydrodynamic modeling of flow. Modern commercial software implement algorithms for these purposes based on the construction and analysis of streamlines. At the same time, there are no reliable estimates of the accuracy of these algorithms and recommendations for choosing the optimal parameters in the available literature. In this paper, we propose an algorithm for calculating the proportions of the distribution of the total well flow rate between the surrounding wells and the reservoir boundary using streamlines. Streamlines are constructed on the basis of a finite element solution to the flow problem averaged over the formation thickness and determine the boundaries of the streamtubes connecting the corresponding wells. The flow rate through the flow tubes is calculated by numerically integrating the Darcy velocity field of the indicated two-dimensional problem. The algorithm was tested on idealized examples of waterflooding elements of typical well placement schemes, when the exact distribution of the proportions of fluid injected into the formation is known, and on the example of comparison with the solution of the problem of simulating the injection of a tracer into the reservoir. Recommendations for the selection of starting points for tracing streamlines are presented, which allow achieving a minimum level of error in determining the mutual influence of wells in a wide range of the computational grid resolution of the flow model. A more general application of the described method without significant changes is to equip the high resolution flow model along fixed stream tubes with their rate characteristics.

Multi-solution well placement optimization using ensemble learning of surrogate models

Well location optimization aims to maximize the economic profit of oil and gas field development while respecting various constraints. The limitations of the currently available well placement optimization workflows are their 1) high computational requirements, which makes them inappropriate for full-field applications where a large number of wells have to be optimized using a computationally expensive simulation model; and 2) providing a single optimal solution, whereas on-site operational problems often add unforeseen constraints that result in adjustments to this optimal, inflexible scenario degrading its value. This study presents a multi-solution, surrogate models (SMs)-assisted optimization framework to deliver diverse, close-to-optimum well placement scenarios at a reasonable computational cost. Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm is used as the optimizer while diversity in optimal solutions is achieved by multiple, parallel runs of the optimizer with different starting points. Convolutional Neural Network (CNN) is used as the SM, to partly substitute the computationally expensive reservoir model runs during the optimization process. A new, adjusted Latin Hypercube Sampling (aLHS) procedure is developed to generate initial training datasets with diverse well placement scenarios while respecting reservoir boundaries and well spacing constraints. An ensemble of CNNs is pre-trained using the generated dataset to enhance the robustness of the surrogate modeling as well as to allow estimation of the SM's prediction quality for new data points. The ensemble of CNNs is adaptively updated during the optimization process using selected new data points, to improve the SM's prediction accuracy. To the best of our knowledge, this is the first application of ensemble learning strategy to a well placement optimization problem. The added value of the framework is demonstrated by comparing three optimization approaches on the Brugge and Egg field benchmark case studies. The approaches are 1) ‘no SM’: using the actual reservoir model only, 2) ‘Offline SM’: the optimization is performed using SM-only that is pre-trained using initial training datasets generated by the actual reservoir model, and 3) ‘Online SM’: pre-trained CNNs are adaptively updated during the optimization process using new datasets generated using the actual reservoir model. The surrogate-assisted optimization approach substantially reduced the computation time, while a greater objective value was achieved by employing the adaptive learning strategy due to the enhanced prediction accuracy of the SMs. Multiple diverse solutions were obtained with different well locations but close-to-optimum objective values, which allows a more efficient exploration of the search space at a significantly reduced computational cost. The presented workflow integrates critical challenges that are correlated, yet often addressed independently, providing the much-required operational flexibility and computational efficiency to field operators when selecting from the optimal well placement scenarios. • A surrogate-assisted, multi-solution framework is presented for well placement optimization. • An ensemble of CNNs is used as the surrogate model (SM) and is adaptively updated during the optimization process, to partly substitute the computationally expensive reservoir simulation runs. • An adjusted Latin Hypercube Sampling (aLHS) procedure is developed to generate initial training datasets with diverse well placement scenarios while several constraints. • The developed framework allows a more efficient exploration of the search space, providing the much-required operational flexibility to field operators when selecting from the optimal well placement scenarios.

The elasticity of the outer boundary and the solution of two-region composite reservoir seepage model

Considering the characteristic of the outer boundary of the two-region composite reservoir has elasticity, firstly, a new two-region composite reservoir seepage model which considers the wellbore storage and effective well radius is established to describe the seepage laws of the two-region composite reservoir more accurately. Then, by combining the Laplace transform and the similar construction method, the solution of dimensionless bottom hole pressure is obtained in the Laplace space. Meanwhile, the solution is also inverted into real space by means of the Stehfest numerical inversion method. Finally, the characteristic curves of dimensionless bottom hole pressure and its derivative are drawn, and the influence of elastic coefficient and reservoir parameters on the characteristic curves is also analyzed. The results reveal that the characteristic curves have affine similarities, and the characteristic curves under the elastic outer boundary condition are always between the closed outer boundary condition and constant pressure outer boundary condition. It can be seen that the conventional three idealized outer boundary conditions (closed, constant pressure and infinite) of two-region composite reservoirs are actually three special cases of elastic outer boundary condition. The introduction of elastic outer boundary condition not only expands the range of data interpretation reasonably, but also shows the actual state of the outer boundary of the two-region composite reservoir better. The similar construction method can avoid complicated and trivial operation processes, and greatly accelerate the model solving speed. The findings of this study can help for better understanding of the real situation of the outer boundary of the two-region composite reservoir, which improves the matching degree between the theoretical model and the actual reservoir, and provides convenience for the development of related well test analysis software.

Three-dimensional interwell electromagnetic detection

Electromagnetic methods play an important role in the exploration and development of oil and gas resources and metal minerals. The ground electromagnetic method is largely limited by the detection depth and resolution in actual work. In order to improve the detection accuracy and working efficiency of interwell electromagnetic detection, this paper proposes a three-dimensional inter-well electromagnetic detection method. The method utilises one or more production wells in the production well pattern to construct a transmission galvanic couple source, which effectively reduces the shielding effect of the metal casing on the transmission signal in the well and improves the transmission signal power. The downhole and the ground receiving arrays were used for simultaneous observation, with high observation network density and detection accuracy. With pseudo-random multi-frequency signals as excitation, the working efficiency of the electromagnetic detection is significantly improved. The downhole receiving array makes the measuring electrode closer to the target geological body, increasing the response signal intensity of the anomalous body. Meanwhile, the impact of electromagnetic interference on the ground is effectively reduced, and the detection depth is increased. The ground receiving array is composed of multiple measurements points located on concentric circular measuring lines, which is beneficial for the identification of the azimuth and angle information of underground geological targets. A detection model for anomalous bodies with different parameters in the formation was established. Numerical results show that for anomalous bodies with different resistivities in the formation, the electric field response curves on the ground and the downhole receiving arrays are significantly different. Because the emission source is located on the symmetry axis of the model, the excited field is distributed axisymmetrically. The ground observation response can effectively identify anomalous bodies with different azimuths and electrical parameters in the formation. The downhole observation response is sensitive to the upper and lower interfaces of the abnormal body, and the depth information of the abnormal body can be accurately determined. The calculation results of the oilfield water injection dynamic monitoring model show that the electric field response curves on the ground receiving arrays of different measuring lines can effectively reflect the water injection process of the underground reservoir, including the direction of water penetration and the change in reservoir resistivity. The research results show that this method can better identify the resistivity characteristics, azimuth information, and depth information of anomalous downhole bodies, while effectively delineating the reservoir boundary and revealing reservoir changes. This provides a theoretical basis and technical ideas for the three-dimensional electromagnetic detection of complex interwell geological bodies.

Reduced well path parameterization for optimization problems through machine learning

In this work we apply a recently developed machine learning routine for automatic well planning to simplify well parameterization in reservoir simulation models. This reduced-order parameterization is shown to be beneficial for well placement optimization, both in terms of convergence and final well configuration. The proposed machine learning routine maps trajectories that honor predefined engineering requirements by exploiting spatial information about the reservoir and prior domain-knowledge about the problem. In this paper, the well planner creates wells that traverse high-permeable parts of the reservoir, thereby increasing well productivity. Previous work found that small changes to the start- and end-points of the well had limited impact on most of the resulting well trajectories, since development of trajectories is chiefly determined by local information around the digital drill bit. In particular, changes in the depth component of the start- and end-points had limited impact on the trajectory away from the end-points. Based on these observations, this work reduces well parameterization to only include horizontal coordinates. The main assumption is that the perforated part of the well always enters the reservoir at the upper reservoir boundary, while the stopping criteria in the machine learning routine is a perforation length only. This formulation reduces the number of decision variables from six to four coordinates for each well. The resulting reduced search space enables a more efficient exploration effort at the cost of less freedom over the start and end points of the well path. However, we show that the highly-refined well trajectory developed by the well planning routine is robust and compensates for fewer degrees of freedom at the overarching parameterization. This robustness is tested by investigating the effect of different start locations on the automatic well planning routines. Moreover, the effect of the reduced well parameterization for well placement optimization is explored. Two optimization scenarios using four different optimizations algorithms are presented. Results show the implementation of the reduced well parameterization for optimization purposes consistently produces high quality solutions. • We present an automatic well planner methodology for design of well trajectories. • The methodology enables simplified parameterization of complex well trajectories. • This facilitates a more efficient exploration effort using fewer degrees of freedom. • Optimization with the proposed methodology improved convergence and final results. • Presented methodology yielded smoother response surfaces which facilitates optimization.

Geothermal Reservoir Identification based on Gravity Data Analysis in Rajabasa Area- Lampung

Gravity research in the Rajabasa geothermal prospect area was conducted to determine geothermalreservoirs and faults as reservoir boundaries. The research includes spectrum analysis and separation of the Bouguer anomaly to obtain a residual Bouguer anomaly, gradient analysis using the second vertical derivative (SVD) technique to identify fault structures or lithological contact, and 3D inversion modeling of the residual Bouguer anomaly to obtain a 3D density distribution subsurface model. Analysis was performed based on all results with supplementary data from geology, geochemistry, micro-earthquake (MEQ) epicenter distribution map, and magnetotelluric (MT) inversion profiles. The study found 3 (three) geothermal reservoirs in Mount Balirang, west of Mount Rajabasa, and south of Pangkul Hot Spring, with a depth of around 1,000-1,500 m from the ground level. Fault structures and lithologies separate the three reservoirs. The location of the reservoir in the Balirang mountain area corresponds to the model data from MEQ, temperature, and magnetotelluric resistivity data. The heat source of the geothermal system is under Mount Rajabasa, which is indicated by the presence of high-density values (might be frozen residual magma), high-temperature values, and the high number of micro-earthquakes epicenters below the peak of Mount Rajabasa.

Efficient and robust optimization for well patterns using a PSO algorithm with a CNN-based proxy model

One objective of the field development plan (FDP) is to optimize well patterns, that is, the number and type of well (producers or injectors) and their locations, in order to maximize net present value (NPV). Optimization cost, including reservoir simulation, is strongly needed in terms of a global solution because of countless FDP scenarios, especially robust optimization for considering geological uncertainty. To solve this problem efficiently and reliably, this study introduces a convolutional neural network (CNN)-based proxy model into particle swarm optimization (PSO). For the proxy model, three map types having the same dimension as the reservoir model were fed into the input layer, giving an NPV for a given well-pattern scenario. The first map was a well configuration map, which consists of 1, -1, and 0 for producer, injector, and no well, respectively. The second and third maps were time-of-flight (TOF) maps from producers and injectors, respectively. Because the type of input data is an image, the CNN could extract features from 3500 scenarios while training the proxy model. When the predicted NPVs from the trained CNN-based proxy model were verified for 750 test data, the coefficients of determination for the true NPVs from reservoir simulation were higher than 0.94. In addition, the proxy model was flexibly applied to various well patterns, even for different numbers of wells because it utilizes TOF maps as input data. Three points are handled in PSO-Proxy to achieve a realistic well pattern: optimization of the number of wells, well spacing constraint, and operational condition for injection wells. The optimized well pattern maximizes NPV with the optimal number of producers and injectors under the predefined maximum number of wells. In the case of well spacing, two distances, that is, the distance between the wells and the distance between a production well and reservoir boundary, are used as criteria for the solution in terms of the filter method before evaluating the NPV. For injectors, water injection is controlled by bottomhole pressure instead of a constant injection rate, which gives meaningless injection wells placed at the edge of the reservoir. When the proposed method was tested using a 2-dimensional (D) synthetic field and 3-D Egg model, its well patterns showed approximately 1.2% lower NPV than the solution from a conventional method, PSO-ECL. This was relatively small when considering that there was approximately 7.8% NPV changes in each optimization run of the PSO-ECL. In addition, PSO-Proxy required only 21% and 8.6% of the optimization cost of the PSO-ECL for the 2-D and 3-D cases, respectively. Therefore, the proposed method was found to enable reliable and efficient decision-making for FDP; further, as the reservoir complexity increases, the CNN-based proxy model should be able to reduce the optimization time dramatically.

Deep transient testing methodology: An integrated approach to redefine the real-time reservoir complexities and well deliverability

Pressure transient analysis (PTA) forms a critical part of the reservoir characterization and quantitative evaluation of reservoir properties. In most of the cases, the pressure transient data are acquired by conventional drill stem tests (DST) to estimate fundamental reservoir properties like permeability, skin, and boundary, used for various well deliverability studies. However, with the emergence of cost optimization scenarios due to reduced crude oil prices in the market, and strict regulatory standards issued by the concerned governments, many exploration wells fail to pass the feasibility standards for a conventional full-scale drill stem test. At the same time, conventional formation testers couldn't help because of the limitation of its extremely low radius of investigation. The recent development of an improved wireline formation tester (WFT) version known as Deep Transient Tester (DTT) enables the industry to capture the far-field reservoir properties with a deeper investigation, complex reservoir heterogeneities, and possible boundary information. However, the acquired data needs advanced solution techniques for accurate interpretation of the information, which lacks at present. In the present study, we have showcased the development of a novel workflow that can interpret the deep transient testing data with better accuracy. The workflow is called Integrated Deep Transient Testing (IDTT). The IDTT workflow is the first of its kind, as per our knowledge, that utilizes both the analytical and numerical methods for the pressure transient analysis with advancements in each of them. The workflow has been validated by comparing results from three modes of testing DST, DTT, and WFT in a common well. Reservoir engineers can refer to the IDTT workflow to interpret the DTT pressure data to characterize reservoir properties, boundary information, and deliverability studies in simple to complex geological settings using the presently developed method.

A pressure drop model of post-fracturing shut-in considering the effect of fracturing-fluid imbibition and oil replacement

Since the production regime of shut-in after fracturing is generally adopted for wells in shale oil reservoir, a shut-in pressure drop model coupling wellbore-fracture network-reservoir oil-water two-phase flow has been proposed. The model takes into account the effects of wellbore afterflow, fracture network channeling, and matrix imbibition and oil exchange after stop of pumping. The simulated log-log curve of pressure-drop derivative by the model presents W-shape, reflecting the oil-water displacement law between wellbore, fracture network and matrix, and is divided into eight main control flow stages according to the soaking time. In the initial stage of pressure drop, the afterflow dominates; in the early stage, the pressure drop is controlled by the cross-flow and leakoff of the fracture system, and the fractures close gradually; in the middle stage of pressure drop, matrix imbibition and oil exchange take dominance, and the fracturing fluid loss basically balances with oil replaced from matrix; the late stage of pressure drop is the reservoir boundary control stage, and the leakoff rate of fracturing-fluid and oil exchange rate decrease synchronously till zero. Finally, the fracture network parameters such as half-length of main fracture, main fracture conductivity and secondary fracture density were inversed by fitting the pressure drop data of five wells in Jimsar shale oil reservoir, and the water imbibition volume of matrix and the oil replacement volume in fracture were calculated by this model. The study results provide a theoretical basis for comprehensively evaluating the fracturing effect of shale oil horizontal wells and understanding the oil-water exchange law of shale reservoir after fracturing.

Heat Flux Based Optimization of Combined Heat and Power Thermoelectric Heat Exchanger

We analyzed the potential of thermoelectrics for electricity generation in a combined heat and power (CHP) waste heat recovery system. The state-of-the-art organic Rankine cycle CHP system provides hot water and space heating while electricity is also generated with an efficiency of up to 12% at the MW scale. Thermoelectrics, in contrast, will serve smaller and distributed systems. Considering the limited heat flux from the waste heat source, we investigated a counterflow heat exchanger with an integrated thermoelectric module for maximum power, high efficiency, or low cost. Irreversible thermal resistances connected to the thermoelectric legs determine the energy conversion performance. The exit temperatures of fluids through the heat exchanger are important for the system efficiency to match the applications. Based on the analytic model for the thermoelectric integrated subsystem, the design for maximum power output with a given heat flux requires thermoelectric legs 40–70% longer than the case of fixed temperature reservoir boundary conditions. With existing thermoelectric materials, 300–400 W/m2 electrical energy can be generated at a material cost of $3–4 per watt. The prospects of improvements in thermoelectric materials were also studied. While the combined system efficiency is nearly 100%, the balance between the hot and cold flow rates needs to be adjusted for the heat recovery applications.

Wai Selabung geothermal reservoir analysis based on gravity method

Research has been conducted using the gravity method in the Wai Selabung area, South Ogan Kemiring Ulu Regency, South Sumatra Province, correlated with geological data, magnetotellurics, and geochemical data. This research aims to get structural patterns, subsurface models and identify the heat source and reservoir areas of the Wai Selabung geothermal system. This study uses the gravity method to model the subsurface, which is correlated with magnetotelluric and geochemical data to identify reservoir prospect areas. The results obtained from this research include residual anomalies in the research area showing the presence of a northwest-southeast trending fault structure by the main fault structure of this area trending northwest-southeast and slightly southwest-northeast. Analysis of the Second Vertical Derivative value of zero indicates the boundaries of the geothermal reservoir in the middle of the research area. The results of the 3D inversion modeling of the research area show that low density (2 to 2.15 g/cm3) indicates the location of the reservoir, medium-density values (2.2 to 2.4 g/cm3) are tertiary sandstone sedimentary. The high-density distribution value (2.5 to 2.9 g/cm3) indicates a potential heat source. And based on the analysis of the gravity method correlated with geological data, magnetotelluric, and geochemical data, the prospect area for the Wai Selabung geothermal reservoir, is around Teluk Agung, Perekan, and Talang Tebat.

A New Model for Predicting Flow in Fractured-Vuggy Carbonate Reservoirs under Pseudosteady State Condition

For constant rate production of a single well in a closed boundary fractured-vuggy carbonate reservoir, when the pressure wave propagates to the reservoir boundaries, boundary-dominated flow occurs, and the transient flow period ends, the reservoir will be in a state of pseudoequilibrium (i.e., pseudosteady state flow occurs, and the pressure at any point in the reservoir declines at the same constant rate over time). The characterization of fluid flow in the fractured-vuggy carbonate reservoir under pseudosteady state condition is of significance in describing the productivity index (PI) of the well. However, due to complex mechanisms (e.g., stress dependency of reservoir properties and crossflow between different systems of the reservoirs) during flow in fractured-vuggy carbonate reservoirs, researches on productivity prediction in fractured-vuggy carbonate reservoirs under pseudosteady state are very limited. The present work is aimed at developing a new analytical model for predicting flow in fractured-vuggy carbonate reservoirs under pseudosteady state condition. In the derived model, the crossflow between different systems (i.e., matrix, fracture, and vug) of the reservoirs was taken into account. In addition, based on Hooke’s law, a quantitative model was proposed to study stress-dependent permeability of the fracture system, which connects the reserve spaces. Moreover, the roughness morphology characteristics of fracture surface were taken into account with fractal theory. Finally, with our derived model, influences caused by various related factors on productivity were analyzed. The results show that well productivity during pseudosteady flow will be significantly affected by the morphology of fracture surface (e.g., fracture microstructure parameters) and effective stress. Specifically, due to effective stress, the fracture system in the fractured-vuggy reservoirs will be deformed, and the corresponding properties (e.g., permeability, porosity, and conductivity) will change, leading to the change of well productivity. In addition, there exists a negative relationship between the elastic storage capacity ratio of vugs and well productivity during pseudosteady flow. Moreover, a larger value of matrix-fracture interporosity flow coefficient or vug-fracture interporosity flow coefficient corresponds to a larger value of well productivity during the pseudosteady period. The new derived model is beneficial to improve the productivity prediction accuracy and reduce uncertainty. What is more, the findings of this study can help for providing theoretical reference for the design of efficient development of fractured-vuggy carbonate reservoirs.

Seepage-evaporation controlled depletion of initially water-filled reservoirs on Earth and Mars: Analytic versus HYDRUS modeling

Analytical solutions are obtained for water extinction from an axisymmetric crater, filled at t < 0 and depleted by evaporation and transient infiltration into a Gardner or capillarity-free homogeneous soil during the time interval 0 ≤ t ≤ Te. The extinction time Te is found for crater beds, the shapes of which are shallow cones, spherical, spheroidal, and paraboloidal caps. An instantaneous seepage flow rate, Q(t), is approximated by truncated two-term formulae of Wooding for a zero-depth disk in Gardner's soil or Hunt for paraboloidal craters (soils with no capillarity). The instantaneous evaporation losses are the product of a constant A-pan evaporation rate and the shrinking area of a flat horizontal disk of the free water, which dwindles in the crater. In HYDRUS simulations of a van Genuchten soil, the Reservoir Boundary Condition is used for a falling water level in the ponded depressions. Cones and paraboloids are selected as craters, initially fully or partially filled with free water at t = 0, and infiltrating until extinction. The results are presented as drawdown curves and – for shallow craters - attest a good match between analytical approximations and HYDRUS numerical simulations. Experiments with the extinction of water from small axisymmetric ponds in dune sand are also carried out. They allow blitz-evaluation of hydraulic parameters of the subjacent sand. Hydrological implications for commingling surface-subsurface (pore) water entities in terrestrial and Martian environments are discussed.

Application of quantitative prediction technology based on reservoir inversion in sedimentary facies research

The traditional sedimentary facies research method based on rock ratio or comparison method has the disadvantages of strong uncertainty and low precision, which is difficult to meet the accurate description of lithologic reservoir boundary. Seismic reservoir inversion prediction technology makes full use of the sand body reflection information contained in seismic facies, which provides a guarantee for the final realization of quantitative study of sedimentary facies between wells and non-well areas. Taking Wang 955 well block on the north slope of Caoqiao as an example, the paper comprehensively uses curve reconstruction technology and seismic inversion technology to quantitatively predict the sandstone between wells and non-well area, and finally realize accurate description of sedimentary facies boundary.