Average Reservoir Research Articles

Holocene Tephrostratigraphy in the East Sea/Japan Sea: Implications for Eruptive History of Ulleungdo Volcano and Potential for Hemispheric Synchronization of Sedimentary Archives

AbstractActive volcanoes in East Asia pose potential threats to the surrounding areas. The eruptive history of many of the Japanese volcanoes are well understood, but their dispersal pathways are often based on visible tephra. Additionally, other important volcanoes in the region still require a deeper understanding of their eruptive potential. Here, we explore the Holocene cryptotephra record preserved in a marine core 13PT‐P4 in the southwestern East Sea, in order to better reconstruct past eruptive events and their dispersal. Six widespread tephra layers are identified and correlated to their source volcanoes in S Korea (Ulleungdo), China/N Korea (Changbaishan) and Japan (Kikai), with their dispersal ranges updated. Our results rank the 13PT‐P4 sequence the most intensively tephra‐constrained Holocene record in the East Sea, which permits synchronization of this mid‐latitude archive with records in the Arctic and tropical regions. Terrestrially based tephra ages are used to constrain the marine reservoir effect and the age‐depth model of the record. The average reservoir age in the region is estimated to be 1150 ± 3014C yr at ca. 7.3–5.6 cal ka BP and 1565 ± 3014C yr at ca. 1.0 cal ka BP. These observed changes in reservoir age could indicate active upwelling at a regional scale. Additionally, we provide a detailed age estimate and glass geochemistry for a previously poorly understood eruption (U‐1) from the Ulleungdo volcano, thus refining its Holocene eruptive history. The U‐1 eruption is dated to 3354‐3080 cal yr BP (95.4%), and has glass composition that is distinct from other Ulleungdo tephras.

Injection of gel systems for CO<SUB align="right">2 leakage remediation in a fractured reservoir

We perform a reservoir simulation study to investigate injection of gel systems, including cross-linked polymer gels and silica gels, as a treatment method for fracture sealing and leakage remediation in CO2 storage reservoirs. An adsorption and permeability reduction approach was adopted to model the fracture sealing by the gel. The results show that for both gel systems a successful treatment can reduce CO2 leakage by 103 times over 25 years of post-treatment CO2 injection. The effects of operating conditions, reservoir heterogeneity, and associated uncertainty on the treatment results were investigated by changing the injection time, injection rate, cross-linked polymer or silica concentration, reaction frequency factor, average reservoir permeability, and spatial correlation length. The simulation results show that selecting the appropriate operating conditions for specific reservoir properties are important to the success of CO2 leakage remediation. [Received: March 23, 2020; Accepted: November 15, 2020]

Population characteristics and potential factors influencing recruitment variability of blue catfish, channel catfish and flathead catfish in Thunderbird Reservoir, Oklahoma

AbstractBlue catfish (Ictalurus furcatus), channel catfish (Ictalurus punctatus) and flathead catfish (Pylodictis olivaris) are popular sport fishes throughout North America, and are therefore intensively managed by some natural resource agencies. Although catfish fisheries rely on sufficient natural reproduction and recruitment to sustain these populations, few studies have evaluated the variables affecting catfish recruitment. Thus, the objectives of this study were to describe population characteristics (age, size structure, condition, growth, mortality and recruitment) of blue catfish, channel catfish and flathead catfish in Thunderbird Reservoir, Oklahoma, and evaluate the effects of hydrology, water quality and temperature on year‐class strength. During 2017 and 2018, 235 blue catfish, 194 channel catfish and 120 flathead catfish were collected and aged using otoliths. In general, these catfish species in Thunderbird Reservoir were slow growing, long‐lived, had low mortality rates and experienced variable recruitment. Blue catfish recruitment was lower in years with higher average January air temperatures. Channel catfish recruitment was higher in years with increased average annual and spring/summer exchange rate and increased spring/summer average reservoir water volume (ha‐m). Conversely, higher annual average total hardness (mg/L) resulted in decreased recruitment for channel catfish. Flathead catfish recruitment exhibited a minimal negative impact with increased annual reservoir volume (ha‐m). The present study is among the first to describe potential variables influencing year‐class formation of blue catfish, channel catfish and flathead catfish in reservoirs. Although the variables found to influence catfish recruitment are outside the control of fisheries managers, biologists should promote downstream angling opportunities for blue catfish that escape during reservoir water release events and stock channel catfish in systems with consistently high total water hardness in order to maximize fishing opportunities. Further, they can use the results of this study to manage angler expectations following periods of low recruitment.

Performance Analysis of Gas Wells Based on the Conventional Decline Parameters and the Flow Integral Equation

The estimation of reserves and performance prediction are two vital tasks for the development of gas reservoirs where the evaluation of gas in place or well-controlled reserves, as the foundation of the performance analysis of gas wells, turns to be exceedingly significant. Advanced production data analysis or modern rate transient analysis (RTA) methods mainly depend on the iterative calculations of material balance quasitime (tca) and type curve fitting, the essence of which is to update the average reservoir pressure data time and again. The traditional Arps’ decline models are of empirical nature despite the convenience and applicability to the constant bottomhole pressure (BHP) condition. In order to avoid the implicit iteration, this paper develops an explicit method for estimating the average reservoir pressure on the basis of dynamic material balance equation (DMBE), termed “flow integral method,” which can be applied to various gas production systems under boundary-dominated flow (BDF). Based on the flow integral method and the decline parameter evaluation, we employ the hyperbolic decline model to model the gas well performance at a constant BHP. The analytical formulations of decline rate and decline exponent are deduced from the DMBE and the static material balance equation (SMBE) considering the elastic compressibilities of rock pore and bound water. The resulting decline parameter method for explicit estimation of gas reserves boasts a solid and rigorous theory foundation that production rate, decline rate, and average reservoir pressure profiles have reference to each other, and its implementation steps are explained in the paper. The SMBE can, combined with the estimated pressure profile by the flow integral method, also be used to determine gas reserves which is not limited to the constant-BHP condition and can calibrate the estimates of the decline parameter method. The proposed methods are proven effective and reliable with several numerical cases at different BHPs and a field example.

14C GEOCHRONOLOGY AND RADIOCARBON RESERVOIR EFFECT OF REVIEWED LAKES STUDY IN CHINA

ABSTRACTLacustrine sediments are important archives for paleoclimate research, but there are evident carbon reservoir effects. Radiocarbon (14C) ages of lake sediments must be corrected for these effects before applying them to paleoclimate research. The authors review the lacustrine research from the last 20 years from different climatic regions in China, and systematically investigate the 14C age and correction methods used in the studies of 81 lakes. It is found that the climate-vegetation cover and distribution of carbonate around lakes are dominant factor controlling radiocarbon reservoir effects. In eastern China, the average 14C reservoir age is about 500 14C years and is associated with relatively dense vegetation. However, in northwest China and Qinghai-Tibet Plateau, widespread carbonate bedrock may markedly increase the radiocarbon reservoir age which frequently is about 1500 and 2500 14C years. A piecewise linear regression model provides more reliable 14C reservoir age correction that accounts for sedimentary facies and sedimentation rate changes. It is worth mentioning that when analyzing 14C ages deviated greatly from time sequence, the age anomalies may indicate important effects relevant to the study of climate and environmental changes.

CO2 EOR Performance Evaluation in an Unconventional Reservoir through Mechanistic Constrained Proxy Modeling

There are multiple parameters including reservoir characteristics, hydraulic fracture design, injection solvent selection, and the enhanced oil recovery (EOR) operational design, etc., that are directly and indirectly involved in the unconventional reservoir development. And due to the lack of field data availability, the key performance indicators for such complex reservoirs are not well defined, therefore, reservoir engineers end up with a huge volume of numerical simulation scenarios to find an optimum field development plan. This approach makes the field development planning process complicated and time-consuming.In this study, a smart unconventional EOR performance evaluation tool is presented utilizing intelligent modeling strategies through proxy modeling approach with mechanistic constraints. The mechanistic constraints incorporate physics-based numerical simulation dataset. Key reservoir and hydraulic fracture topographies including average reservoir pressure and the matrix & hydraulic fracture permeability contrast are used as some of the key input parameters for the Deep Neural Network (DNN) modeling. Total four DNN models are generated for primary and EOR cases presenting the recovery performance prediction at two different timelines. The trained and validated DNN models are finally found well qualified to be applied for the development of the unconventional reservoirs with identical reservoir and hydraulic fracture characteristics for the EOR application forecasting.

Investigation of the influence of the heterogeneous permeability distribution on the oil phase displacement processes

The object of research is the filtration processes of displacement of the oil phase under the influence of an injection well in a heterogeneous porous medium. It is possible to evaluate and take into account the effect of reservoir heterogeneity on the distribution of reservoir pressure (and, consequently, on the intensity of the filtration process) using numerical modeling of filtration processes based on the piezoelectric equation. To solve the non-stationary anisotropic problem of piezoconductivity, it is proposed to apply the combined finite-element-difference method of M. Lubkov, which makes it possible to take into account the inhomogeneous distribution of permeability inside the anisotropic oil-bearing formation and at its boundaries, and to adequately calculate the distribution of reservoir pressure. The use of the combined finite-element-difference method allows to combine the advantages of the finite-element method and the finite difference method: to model geometrically complex areas, to find the value at any point of the object under study. At the same time, the use of an implicit difference scheme when finding the nodal values of the grid provides high reliability and convergence of the results. The simulation results show that the distribution of the pressure field between the production and injection wells significantly depends on their location, both in the isotropic landslide and in the anisotropic oil-bearing reservoir. It is shown that the distance between the wells of more than 1 km levels out the effectiveness of the impact of the injection well on the oil filtration process. The influence of the permeability of the oil phase in the shear direction dominates the influence of the permeability in the axial directions (affects the pressure decrease by 4–9.5 %). In the case of a landslide-isotropic reservoir, the wells should be located in the shear (diagonal) direction, which will provide the lowest level of drop in the average reservoir pressure (by 4 %). Based on the information obtained, for the effective use of anisotropic low-permeability formations, it is necessary to place production and injection wells in areas with relatively low anisotropy of the formation permeability, especially to avoid places with the presence of landslide permeability of the formation. The location of the wells is important so that, on the one hand, there is no blockage of oil from the side of reduced permeability, and on the other hand, rapid depletion of the formation from the side of increased permeability does not occur. And also the mutual exchange between the production and injection wells did not stop. When placing a system of production and injection wells in anisotropic formations of an oil field, it is necessary to carry out a systematic analysis of the surrounding anisotropy of the formations in order to place them in such a way that would ensure effective dynamics of filtration processes around these wells. Using the method used, it is possible to predict the impact of an injection well on the distribution of reservoir pressure in the reservoir.

Two deterministic methodologies for estimation of OGIP by production dynamics diagnostic of gas-condensate reservoir

This study presents two independent methodologies for estimation of original gas in place (OGIP) by production dynamics diagnostic of gas-condensate reservoir with no-flow outer boundary based on black-oil concept. Classic Blasingame decline-type curves are also extended to apply in gas-condensate reservoir to calculate kh . Both numerically simulated case and field data are used to demonstrate the applicability and validity of proposed methodologies. One method develops a novel analytical model to obtain average reservoir pressure, OGIP and Diatz shape factor at the same time by coupling flow equation of gas-condensate reservoir for boundary dominated flow (BDF) and general material balance equation (GMBE). The two-phase variable-rate flow equation at late time for BDF is clearly and concisely derived in this study in terms of defined two-phase pseodopressure and two-phase material balance pseudotime. In addition, another innovative, simple and effective method for estimation of OGIP is proposed in this study requiring input data of only cumulative production of well and reservoir fluid PVT characteristics of Constant Volume Depletion (CVD) experiment. The fundamental concept of this method suggests that transient cumulative production GOR is determined by only current gas recovery degree and fluid PVT characteristics of the reservoir. Due to the accurate, simple and relaxed data-requiring nature of this method, widespread use in field to estimate OGIP of gas-condensate reservoir is potentially encouraging. On the contrary, if OGIP is already known, an intermediate equation of the method can also be applied to check accuracy of CVD experiment results from laboratory. The first methodology extends OGIP estimation to gas-condensate reservoir from Blasingame and Lee (1988)’s method for dry-gas reservoir. Often used two-phase z factor, which is inconvenient to evaluate and easy to yield error, for gas-condensate reservoir in material balance equation is avoided in this methodology by applying more analytical and accurate Walsh et al. (1994)’s GMBE instead. The second methodology, to the authors’ knowledge, is the first proposed allowing OGIP estimation of gas condensate reservoir without requiring bottom hole flowing pressure (BHFP), pressure tests and complex calculation.

Calculation of Average Reservoir Pore Pressure Based on Surface Displacement Using Image-To-Image Convolutional Neural Network Model

The average pore pressure during oil formation is an important parameter for measuring the energy required for the oil formation and the capacity of injection–production wells. In past studies, the average pore pressure has been derived mainly from pressure build-up test results. However, such tests are expensive and time-consuming. The surface displacement of an oilfield is the result of change in the formation pore pressure, but no method is available for calculating the formation pore pressure based on the surface displacement. Therefore, in this study, the vertical displacement of the Earth’s surface was used to calculate changes in reservoir pore pressure. We employed marker-stakes to measure ground displacement. We used an improved image-to-image convolutional neural network (CNN) that does not include pooling layers or full-connection layers and uses a new loss function. We used the forward evolution method to produce training samples with labels. The CNN completed self-training using these samples. Then, machine learning was used to invert the surface vertical displacement to change the pore pressure in the oil reservoir. The method was tested in a block of the Sazhong X development zone in the Daqing Oilfield in China. The results showed that the variation in the formation pore pressure was 83.12%, in accordance with the results of 20 groups of pressure build-up tests within the range of the marker-stake measurements. Thus, the proposed method is less expensive, and faster than existing methods.

Comparative Study of Oil Recovery Factor Determination for Edge and Bottom Water Drive Mechanism Using Water Influx Models

The purpose of this research work is to comparatively study the oil recovery factor from two major aquifer geometry (Bottom and Edge water aquifer) using water aquifer model owing to the fact that most if not every reservoir is bounded by a water aquifer with relative size content (Most Large). These aquifers are pivotal in oil recovery factor (percent%), Cumulative oil produced (MMSTB) as well as overall reservoir performance the methodology utilized in this study involves; Identification of appropriate influx models were utilized for aquifer characterization. The characterizes of the Niger Delta reservoir aquifer considered include aquifer permeability, aquifer porosity etc. Estimation of aquifer properties is achieved by using regressed method in Material Balance Software (MBAL). This approach involves History Matching of average reservoir pressure with computed pressure of the reservoir utilizing production data and PVT data. The computed pressure from model is history matched by regressing most uncertain parameters in aquifer such as aquifer size, permeability, and porosity. Historic production data was imputed into the MBAL Tank Model, the production data was matched with the model simulation by regressing on rock and fluid parameters with high uncertainty. The match parameters were recorded as the base parameter and other sensitivity on aquifer parameters using the Fetkovich model for the bottom and edge water drive. The average percentage increase in oil cumulative volume was 0.40% in fovour of bottom water drive. Further sensitivity on cumulative oil recovered showed the increase in reservoir size with increasing aquifer volumes increases oil production exponentially in bottom water drive whereas edge water drive increased linearly. Aquifer volume, aquifer permeability showed linear relationship with bottom and edge water drive.

Comparative Study of Oil Recovery Factor Determination for Edge and Bottom Water Drive Mechanism Using Water Influx Models

The purpose of this research work is to comparatively study the oil recovery factor from two major aquifer geometry (Bottom and Edge water aquifer) using water aquifer model owing to the fact that most if not every reservoir is bounded by a water aquifer with relative size content (Most Large). These aquifers are pivotal in oil recovery factor (percent%), Cumulative oil produced (MMSTB) as well as overall reservoir performance the methodology utilized in this study involves; Identification of appropriate influx models were utilized for aquifer characterization. The characterizes of the Niger Delta reservoir aquifer considered include aquifer permeability, aquifer porosity etc. Estimation of aquifer properties is achieved by using regressed method in Material Balance Software (MBAL). This approach involves History Matching of average reservoir pressure with computed pressure of the reservoir utilizing production data and PVT data. The computed pressure from model is history matched by regressing most uncertain parameters in aquifer such as aquifer size, permeability, and porosity. Historic production data was imputed into the MBAL Tank Model, the production data was matched with the model simulation by regressing on rock and fluid parameters with high uncertainty. The match parameters were recorded as the base parameter and other sensitivity on aquifer parameters using the Fetkovich model for the bottom and edge water drive. The average percentage increase in oil cumulative volume was 0.40% in fovour of bottom water drive. Further sensitivity on cumulative oil recovered showed the increase in reservoir size with increasing aquifer volumes increases oil production exponentially in bottom water drive whereas edge water drive increased linearly. Aquifer volume, aquifer permeability showed linear relationship with bottom and edge water drive.

Delineation of reservoir channels by different seismic attributes and geobody extractions for robust volumetric estimation, Saffron Field, offshore Nile Delta, Egypt

The Nile Delta Basin is a major gas province. Commercial gas discoveries there have been proven mainly in Pleistocene to Oligocene sediments, and most discoveries are within sandstone reservoirs. Three-dimensional seismic data acquired over the basin have helped greatly in imaging and visualization of stratigraphy and structure, leading to robust understanding of the subsurface. Channel fairways serve as potential reservoir units; hence, mapping channel surfaces and identifying and defining infill lithology is important. Predicting sand distribution and reservoir presence is one of the key tasks as well as one of the key uncertainties in exploration. Integrating state-of-the-art technologies, such as including 3D seismic reflection surveys, seismic attributes, and geobody extractions, can reduce this uncertainty through recognition and accurate mapping of channel features. In this study, seismic attribute analysis, frequency analysis through spectral decomposition (SD), geobodies, and seismic sections have been used to delineate shallow Plio-Pleistocene El Wastani Formation channel fairways within the Saffron Field, offshore Nile Delta, Egypt. This has led to providing more reliable inputs for calculation of volumetrics. Interpretation of the stacked-channels complex through different seismic attributes helped to discriminate between sand-filled and shale-filled channels and in understanding their geometries. Results include more confident delineation of four distinct low-sinuosity channelized features. Petrophysical evaluation conducted on five wells penetrating Saffron reservoirs included electric logs and modular dynamic test data interpretation. The calculated average reservoir properties were used in different volumetric calculation cases. Different approaches were applied to delineate channel geometries that were later used in performing different volumetric cases. These approaches included defining channels from root-mean-square amplitude extractions, SD color-blended frequencies, and geobodies, all calculated from prestack seismic data. The different volumetric cases performed were compared against the latest field volume estimates proven after several years of production in which an area-versus-depth input showed the closest calculated hydrocarbon volumes to the actual proven field volumes.

Interpretation of interwell connectivity tests in a waterflood system

This study is an extension of a novel technique to determine interwell connectivity in a reservoir based on fluctuations of bottom hole pressure of both injectors and producers in a waterflood system. The technique uses a constrained multivariate linear regression analysis to obtain information about permeability trends, channels, and barriers. Some of the advantages of this new technique are simplified one-step calculation of interwell connectivity coefficients, small number of data points and flexible testing plan. However, the previous study did not provide either in-depth understanding or any relationship between the interwell connectivity coefficients and other reservoir parameters. This paper presents a mathematical model for bottom hole pressure responses of injectors and producers in a waterflood system. The model is based on available solutions for fully penetrating vertical wells in a closed rectangular reservoir. It is then used to calculate interwell relative permeability, average reservoir pressure change and total reservoir pore volume using data from the interwell connectivity test described in the previous study. Reservoir compartmentalisation can be inferred from the results. Cases where producers as signal wells, injectors as response wells and shut-in wells as response wells are also presented. Summary of results for these cases are provided. Reservoir behaviours and effects of skin factors are also discussed in this study. Some of the conclusions drawn from this study are: (1) The mathematical model works well with interwell connectivity coefficients to quantify reservoir parameters; (2) The procedure provides in-depth understanding of the multi-well system with water injection in the presence of heterogeneity; (3) Injectors and producers have the same effect in terms of calculating interwell connectivity and thus, their roles can be interchanged. This study provides flexibility and understanding to the method of inferring interwell connectivity from bottom-hole pressure fluctuations. Interwell connectivity tests allow us to quantify accurately various reservoir properties in order to optimise reservoir performance. Different synthetic reservoir models were analysed including homogeneous, anisotropic reservoirs, reservoirs with high permeability channel, partially sealing fault and sealing fault. The results are presented in details in the paper. A step-by-step procedure, charts, tables, and derivations are included in the paper.

Optimization of inflow performance relationship curves for an oil reservoir by genetic algorithm coupled with artificial neural-intelligence networks

In this paper, the effect of parameters on the IPR (Inflow Performance Relationship) curves of a well is analyzed using a multilayer perceptron artificial neural network. Genetic algorithms were used to train the network to adjust the weights and bias of the network so that the RMSE (Root Mean Squared Error) of the data assigned to the network test was minimized. The algorithm also optimized the network structure (including the number of hidden layers and the neurons of each layer). Based on Eclipse software, one of the oil reservoirs was first analyzed and then by changing the average reservoir pressures (assuming the oil well is predicted to reach such pressures above the average reservoir) and pressures. For this purpose, 48 experiments were conducted concerning the research variables implemented by each of them, providing inputs and outputs for network training and testing. Finally, 85% of the data were allocated to the training section and 15% to the software-generated software using the artificial neural network test section. The basis for deciding the error rate of the test data was considered. About 100% accuracy in the regression indicates that the neural network is reliable in other performances. The defined error is less than 2%, which indicated the efficiency of the genetic algorithm to predict IPR curves. This is rooted in applying genetic algorithms as a training function because it has increased the accuracy of data training. The magnitude of ANN (Artificial Neural Network) error for each scenario is also shown in the following curve. For example, the error of the sixth experiment is reported to be around 8%.

Optimization of steam injection in SAGD using reinforcement learning

Conventional steam injection strategies or policies in SAGD are typically not a result of a formal optimization process but rather empirically found. However, finding the steam injection policy that maximizes cumulative performance over the entire production horizon represents a major challenge due to the complex dynamics of the physical phenomena. To address this challenge one alternative is to use a reinforcement learning (RL) approach; here an agent is trained to find the optimal policy only by continuous interactions with the reservoir simulation model (environment). In this work, the RL-SARSA on-line on-policy learning algorithm is used to find the optimal steam injection policy and offer insight in the physics of the SAGD process. Net Present Value (NPV) is used as a performance measure of objective function, the action-value function is approximated using a stochastic gradient regression strategy, and the state vector is featurized using radial basis kernels. The action space is discrete, three (3) possible actions: increase/decrease/no change on the steam injection rate w.r.t the previous value, and the state space is continuous and is made up of cumulative values for water and oil production and steam injection. Additionally, the environment is represented by a one well pair reservoir simulation model built using data from a reservoir located in northern Alberta and a production horizon of 250 days is considered. For the considered case study, the agent showed a significant improvement on the cumulative NPV value after 200 episodes or simulations and the optimal policies are characterized by three distinct regions, (1) constant rate to increase the average reservoir pressure and allow the steam chamber reach the overburden, (2) sharp increase to increase average reservoir temperature and abrupt decrease and (3) constant minimum value to maintain the average reservoir temperature. • Reinforcement learning with function approximation has been successfully applied to the optimization of steam injection in a SAGD process. • The optimal steam injection policy is characterized by three distinct regions: constant rate, sharp increase and abrupt decrease, constant minimum rate. • For optimum SAGD operations, pressure plays a key role until the steam chamber reaches the overburden, afterwards temperature dominates.

Data-driven based investigation of pressure dynamics in underground hydrocarbon reservoirs

The process of storing natural gas in geological formations involves applying pressure to force the gas into and out of the porous and permeable reservoir. In response to gas extraction/withdrawal and storage/injection, the reservoir compresses and expands as a major consequences of fluid pore pressure variations. The major challenge associated with this type of energy systems is learning the pore pressure variations within the grid as fluid is being injected and/or withdrawn. As such, it is essential to identify a realistic model that accounts for the pore pressure variations at any point in time. In this paper, we present a data-driven technique called Dynamic Mode Decomposition (DMD) to investigate the pressure dynamics of an underground hydrocarbon reservoir model in relation to natural gas injection/storage. For demonstration purpose, we first implement a hydrocarbon reservoir model using a benchmark data of the first Society of Petroleum Engineers (SPE1) Comparative Solution Project. Applying DMD to a pressure field data of the simulated reservoir model, we show that DMD is capable of approximating the average reservoir pressure change and pore pressure variations within the reservoir grid over time with up to 99% accuracy. Given that depleted reservoirs are already developed hydrocarbon reservoirs, we conclude that DMD could serve as a reliable tool for fast evaluation of pressure dynamics of underground natural gas storage given its low complexity and insignificant loss of prediction accuracy.

Thermal Energy Estimation by In-situ Combustion in An Abandoned Oil Well

A downside of producing oil is that it can never be fully recovered. After the end of a well's life span, the residual oil remaining in the reservoir on average can be over 30%. This residual oil can be extracted using enhanced oil recovery techniques, one of which combusts the oil in the formation where the average reservoir temperature can increase to 400⁰C for light oil and over 600⁰C for heavy oils. This method can become a significant catalyst in solving Pakistan's energy need and increasing power production. This paper aims to estimate the thermal energy production by combusting this residual oil using in-situ combustion by air injection technique. The study deals with the well Kahi-01 located in the upper Indus basin having three formations. The main target is the Hangu formation and its three reservoir blocks. This formation is characterized by its high residual oil percentage of 76-85% at depths of about 1691-1741 meters. The results show that the highest thermal energy output among the three reservoirs was 34.6e6 Megajoules. The highest power output from the binary plant was 38.5e4 Kilowatt hour.

Multiple fluid-mineral equilibria approach to constrain the evolution of thermal waters in the Hisaralan geothermal field, Simav Graben, western Turkey

In this study seasonal changes in the geochemical and stable isotope compositions of Hisaralan thermal waters in Simav Graben, western Turkey, were investigated with regards to a variety of mineral-water interactions and mixing processes. The Hisaralan and Emendere geothermal waters, with temperatures of up to 99 °C, were mostly of Na-HCO3 and Ca-HCO3 types. The δ18O and δ2H values of the Hisaralan waters ranged from -9.32‰ to -8.73‰ and -65.02‰ to -61.10‰, with maximum seasonal differences of 0.3‰ and 1.8‰. The Emendere waters were represented by a more positive range of δ2H values (-54.95‰ to -54.61‰), while their δ18O compositions (-9.04 to -8.41‰) were very similar to those of the Hisaralan waters. The stable isotope compositions of the Hisaralan thermal waters were consistent with those of the global meteoric water line, whereas the Emendere waters closely resembled those of the Marmara meteoric water line. The δ13C of the dissolved inorganic carbon varied from -4.33‰ to -2.77‰ for the thermal waters and from -13.84‰ to -12.51‰ for the cold waters. These values indicated a marine carbonate origin for the former and an organic source for the latter. Sulfur isotope systematics of dissolved sulfate in the Hisaralan geothermal waters indicated that the sulfate was most likely derived from the dissolution of marine carbonates and terrestrial evaporites. Chemical geothermometers applied to the Hisaralan thermal waters yielded average reservoir temperatures of 123 to 152 °C, which were rather consistent with those estimated using the silica-enthalpy (146 to 154 °C) and chloride-enthalpy (142 to 178 °C) mixing models. The recharge elevations of the thermal waters that were computed from the δ2H compositions were between 1060 and 1330 m.

Dynamic Material Balance Method for Estimating Gas in Place of Abnormally High-Pressure Gas Reservoirs

Abstract Determination of gas in place (GIP) is among the hotspot issues in the field of oil/gas reservoir engineering. The conventional material balance method and other relevant approaches have found widespread application in estimating GIP of a gas reservoir or well-controlled gas reserves, but they are normally not cost-effective. To calculate GIP of abnormally pressured gas reservoirs economically and accurately, this paper deduces an iteration method for GIP estimation from production data, taking into consideration the pore shrinkage of reservoir rock and the volume expansion of irreducible water, and presents a strategy for selecting an initial iteration value of GIP. The approach, termed DMBM-APGR (dynamic material balance method for abnormally pressured gas reservoirs) here, is based on two equations: dynamic material balance equation and static material balance equation for overpressured gas reservoirs. The former delineates the relationship between the quasipressure at bottomhole pressure and the one at average reservoir pressure, and the latter reflects the relationship between average reservoir pressure and cumulative gas production, both of which are rigidly demonstrated in the paper using the basic theory of gas flow through porous media and material balance principle. The method proves effective with several numerical cases under various production schedules and a field case under a variable rate/variable pressure schedule, and the calculation error of GIP does not go beyond 5% provided that the production data are credible. DMBM-APGR goes for gas reservoirs with abnormally high pressure as well as those with normal pressure in virtue of its strict theoretical foundation, which not only considers the compressibilities of rock and bound water, but also reckons with the changes in production rate and variations of gas properties as functions of pressure. The method may serve as a valuable and reliable tool in determining gas reserves.

Preliminary Studies on the Proppant Embedment in Baltic Basin Shale Rock

Proppant embedment is a serious issue that reduces fracture width and conductivity. The paper presents the results of experiments on embedment phenomena on a shale rock from the region of the Baltic Basin, which is regarded as an unconventional gas deposit. A novel laboratory imaging procedure was implemented to the proppant embedment visualization. The tests were performed for conditions corresponding to the average reservoir conditions occurring in the studied deposit formation. The parameters characterizing damage of the surface of the fracture faces by the grains of proppant material, after the application of axial compressive stress to two shale core samples with proppant placed in between, are presented. The tests were carried out for rock samples pre-saturated with fracturing fluid. The obtained results of relatively low total effective penetration depth of proppant grains into the walls of the fracture (0.293 mm), and high effective width of fracture with proppant material after hydraulic fracturing (87.9%), indicate the proper selection of proppant and fracturing fluid for the properties of the rock and the reservoir conditions. The results of the experiments present a range of embedment parameters, that have not been widely described before. The test procedure presented in the article is a good method for assessing the vulnerability of a deposit rock to embedment phenomenon.