Reservoir Development Plan Research Articles

A Novel Streamline-Based Objective Function for Well Placement Optimization in Waterfloods

AbstractIn reservoir development plans, well placement optimization is usually performed to better sweep oil and reduce the amount of trapped oil inside reservoirs. Long-term optimization of well placement requires multiple times simulation of reservoirs which makes these problems cumbersome, especially when a large number of decision variables exist. Cumulative oil production (COP) or net present value (NPV) functions are commonly used as the objective function of optimal enhance oil recovery projects. Use of these functions requires a full-time reservoir simulation and their convergence could be difficult with the chance to be trapped in local optimum solutions. In this study, the novel proportionally distributed streamlines (PDSLs) target function is proposed that can be minimized to reach the optimal well placement. PDSL can be estimated even without full-time reservoir simulation. PDSL tries to direct the appropriate number of streamlines toward the regions with larger amount of oil in the shortest time and hence can improve oil recovery. Particle swarm optimization (PSO) method linked to an in-house streamline-based reservoir simulator is implemented to optimize well placement of water-flooding problems in a two-dimensional heterogeneous reservoir model.

Analysis of Factors Influencing the Capacity of Fractured Straight Wells in Tight Gas Reservoirs

In response to the problems of non-production and low production from tight gas reservoirs, a study on the degree of influence of different parameters on the production capacity after fracturing of straight wells was carried out. Taking fractured wells in the Linxing block as the target, under the premise of relatively small and incomplete data, geological and engineering factors with gas wells in production were given priority, and the parameters affecting the production capacity of each well were calculated and analyzed by using the information quantity analysis method and gray correlation analysis method to determine the information quantity of each parameter and the correlation degree between each parameter. The analysis concluded that: permeability, shot hole thickness, water content saturation and porosity are the main factors affecting straight wells, and the secondary factors are seam length, formation pressure, and return discharge rate, respectively. Based on the high similarity of the analysis results of the above two methods, it is considered that the objective analysis method, gray correlation method, can compensate for the errors of the information quantity analysis method due to subjective factors. In the design of the Linxing gas reservoir development plan, the engineering factor among the main factors is used as the entry point, which can significantly improve the gas well capacity

Application of ML & AI to model petrophysical and geomechanical properties of shale reservoirs – A systematic literature review

Extensive reviews and cross-comparison studies are essential to analyze the emerging developments in a specific field of research. In the past decade, hydrocarbon exploration and exploitation from the shale reservoirs have been the most discussed and researched area around the globe. A dramatic development in shale formations became the game-changer, especially in the US. On the other hand, Artificial Intelligence (AI) and Machine Learning (ML) are playing an important role in the rapid development in all the industries through automating most of the routine operations. The oil industry is also getting equal benefits of AI and ML for the reservoir development planning and its operational accuracy through a series of automated systems. For the field development, computerized static and dynamic simulation models are generated based on several Petrophysical and Geomechanical properties gathered through different resources that are quite time-taking and expensive. AI and ML have made this process much easier, faster, and economical by means of learning through uncounted experiences from already explored and developed reservoirs, their rock properties, and the cross-ponding fluid flow behavior under different circumstances and hence, predicts accordingly. This article provides a comprehensive literature review in the area of AI and ML applications to model Petrophysical and Geomechanical properties using different approaches and algorithms. Also, a systematic publication counts in each field of subject study per year in different literature databases are presented that infect reflects the trending interest in this subject. Finally, multiple AI and ML techniques are discussed in detail which have been tested in the last decade for the sake of achieving higher accuracy in Petrophysical and Geo-Mechanical simulation models.

A Practical Method to Calculate and Model the Petrophysical Properties of Reservoir Rock Using Petrel Software: A case Study from Iraq

Nasiriyah oilfield is located in the southern part of Iraq. It represents one of the promising oilfields. Mishrif Formation is considered as the main oil-bearing carbonate reservoir in Nasiriyah oilfield, containing heavy oil (API 25o(. The study aimed to calculate and model the petrophysical properties and build a three dimensional geological model for Mishrif Formation, thus estimating the oil reserve accurately and detecting the optimum locations for hydrocarbon production.
 Fourteen vertical oil wells were adopted for constructing the structural and petrophysical models. The available well logs data, including density, neutron, sonic, gamma ray, self-potential, caliper and resistivity logs were used to calculate the petrophysical properties. The interpretations and environmental corrections of these logs were performed by applying Techlog 2015 software. According to the petrophysical properties analysis, Mishrif Formation was divided into five units (Mishrif Top, MA, shale bed, MB1 and MB2). A three-dimensional geological model, which represents an entrance for the simulation process to predict reservoir behavior under different hydrocarbon recovery scenarios, was carried out by employing Petrel 2016 software. Models for reservoir characteristics (porosity, permeability, net to gross NTG and water saturation) were created using the algorithm of Sequential Gaussian Simulation (SGS), while the variogram analysis was utilized as an aid to distribute petrophysical properties among the wells.
 The process showed that the main reservoir unit of Mishrif Formation is MB1 with a high average porosity of 20.88% and a low average water saturation of 16.9%. MB2 unit has good reservoir properties characterized by a high average water saturation of 96.25%, while MA was interpreted as a water-bearing unit. The impermeable shale bed unit is intercalated between MA and MB1 units with a thickness of 5-18 m, whereas Mishrif top was interpreted as a cap unit. The study outcomes demonstrated that the distribution accuracy of the petrophysical properties has a significant impact on the constructed geological model which provided a better understanding of the study area’s geological construction. Thus, the estimated reserve h was calculated to be about 7945 MSTB. This can support future reservoir development plans and performance predictions.

Modeling the Depositional Environment of the Sandstone Reservoir in the Middle Miocene Sidri Member, Badri Field, Gulf of Suez Basin, Egypt: Integration of Gamma-Ray Log Patterns and Petrographic Characteristics of Lithology

Understanding the depositional setting of siliciclastics reservoir is fundamental process to exploration and development of hydrocarbon reservoirs and to the multi-phase cycle of the oil and gas industry. Typically, core samples from existing or potential reservoirs can be used for interpretation of depositional environment. However, the lack of core samples in certain reservoirs represents a challenge for reservoir development plans and further exploration. To overcome the absence of core samples in the middle Miocene Sidri Member in the Badri field, Gulf of Suez, this study aimed to reconstruct its depositional settings by coupling well logging patterns and petrographic characterization of ditch cuttings. Consequently, 30 thin section samples representing the reservoir section of four wells were described in detail and standard petrographic characteristics were determined. Then, gamma-ray (GR) log patterns of the studied reservoir wells were used for interpretation of depositional environment. Petrographic analysis indicates that the sandstone reservoir is fine- to medium-grained arkose with dominant siliceous cement and composed mainly of quartz, feldspars, and lithic fragments. Pores reflecting primary and secondary porosity as well as inter-granular pores are dominant. The facies analysis indicates that the studied member has a heterogeneous nature and rapid facies change; its main lithofacies are blocky sandstones, intercalated sandstones and shales, and shales. Three electrofacies were interpreted in the studied section: (1) electrofacies-A (blocky sandstones), which is characterized by a cylindrical-shaped (right boxcar) GR trend; (2) electrofacies-B (intercalated sandstones and shales), which is characterized by an irregular log trend with serrated shape; and (3) electrofacies-C (shales), which is characterized by irregular GR trend and has no character. The interpreted results indicate a tidal channel depositional setting for electrofacies-A, mixed tidal flat depositional setting for electrofacies-B, and low relief offshore mudstone depositional setting for electrofacies-C. Finally, the results illustrate how the coupling of GR patterns with the analysis of petrographic characteristics can be used to understand the depositional setting of a hydrocarbon reservoir that lacks core samples. This work could be useful for assessment of reservoir distribution and quality, for reduction of uncertainty during field development, as well as for providing useful insight to similar hydrocarbon reservoirs elsewhere.

Analytical water saturation model using capacitance-resistance simulation: Clean and shaly formations

The strategies of reservoir development plans are constructed based on the economic values of reservoirs original hydrocarbon in place, which is always affected by the uncertainty in estimating water saturation. Maximum precision in water saturation is needed for reserve calculations or for decisions on whether to complete wells drilled in offshore or in unconventional hydrocarbon resources. Therefore, the development of a suitable model based on fundamental physics is sorely needed to cope with the demands of the present and future evaluation of petroleum reserves and also to overcome the shortages of current empirical models. In this study, an analytical model for the estimation of water saturation using traditional resistivity logs has been developed using capacitance-resistance modeling (CRM). This philosophy simulates the physics of saturated rock behavior to electric current by a resistor connected to a capacitor, which gives the overall electric system behavior. This system has a first order differential mathematical law. The advantage of analytical model is that it has no adjustable parameters, such as those exist in Archie's and other shaly empirical or electrochemical models. Moreover, it works in both clean and shaly formations of any kind of shale deposition within the rock matrix, which are usually determined from core analysis and laboratory experiments that consume time and cost. The mathematical derivation allows using the model for any values of porosity, shale volume, shale resistivity and true formation resistivity. Therefore, the model provides very significant outcomes of water saturation compared to Archie's and shaly empirical models. Model's reliability has been verified using laboratory measurements covering very wide range of shale content “0–0.8”, shale resistivity “0.1–48 Ω m”, formation water resistivity “0.02–10 Ω m” and formation porosity “0.015–0.48“.

Simulating the strategies of oil field development for enhanced oil recovery

Many years have passed in oil field development but primary challenges faced by the X reservoir are the rapid decline of formation pressure and the significant solution gas released from the formation, which impairs production. Based on these challenges, a compositional simulation model of the X reservoir was constructed and run to establish the future development plans. The basic reservoir data collection and processing, quality assurance of the data, characteristic pressure-volume-temperature (PVT) matching by ECLIPSE PVTi, and simulation of various adjustment strategies to forecast development plans, as well as data sensitivity analysis and optimization has been included in this study. In addition, to establish a desirable development plan, the simulation model is set up in great consistency with the geological model resulted from the seismic and logging interpretations. Also, emphases are paid on establishing matches with the reported lab data from production wells by PVTi. Results revealed that the specific reservoir development plan intends to reinstate or maintain formation pressure of the X reservoir. All design and optimization studies are set to comprehend the reservoir with the numerical model.

Parallel numerical simulation for a super large-scale compositional reservoir

A compositional reservoir simulation model with ten-million grids is successfully computed using parallel processing techniques. The load balance optimization principle for parallel calculation is developed, which improves the calculation speed and accuracy, and provides a reliable basis for the design of reservoir development plan. Taking M reservoir as an example, the parallel numerical simulation study of compositional model with ten million grids is carried out. When the number of computational nodes increases, message passing processes and data exchange take much time, the proportion time of solving equation is reduced. When the CPU number increases, the creation of Jacobian matrix process has the higher acceleration ratio, and the acceleration ratio of I/O process become lower. Therefore, the I/O process is the key to improve the acceleration ratio. Finally, we study the use of GPU and CPU parallel acceleration technology to increase the calculation speed. The results show that the technology is 2.4 ∼ 5.4 times faster than CPU parallel technology. The more grids there are, the better GPU acceleration effect it has. The technology of parallel numerical simulation for compositional model with ten-million grids presented in this paper has provided the foundation for fine simulation of complex reservoirs. Cited as : Lian, P., Ji, B., Duan, T., Zhao, H., Shang, X. Parallel numerical simulation for a super large-scale compositional reservoir. Advances in Geo-Energy Research, 2019, 3(4): 381-386, doi: 10.26804/ager.2019.04.05

Spatial configuration of sand and mud in the lacustrine nearshore sand bar deposits and its geological implications

Different configurational orders of sand bodies and interlayers in lacustrine nearshore sand bar reservoirs frequently interact, causing complicated genesis and distribution of argillaceous sediments, as well as other issues. This paper investigates the spatial configuration of sand and mud in the sand bar reservoir, and analyzes its internal structure. Modern sand bar deposits in the Xiashan Lake, Shandong Province, China, were analyzed and compared with the sand bar reservoirs of the Member 2 of the Paleogene Shahejie Formation in the Banqiao Sag, China. The configurational mode of sand bar deposits was explored from the perspective of the spatial distribution and composition relationships between sand and mud. Based on the alternate deposition characteristics of sand and mud in the longitudinal direction, lacustrine nearshore sand bars can be divided into three sedimentary combination patterns: thin-sand and thin-mud interbed pattern, thick-mud thick-sand pattern, and thin-mud thick-sand pattern. Their mud components manifest as the deposition of fine-grained lithofacies of multiple genetic types. These include (semi-)deep lacustrine mud, sand and mud interbedded beach, argillaceous sediments in the water retention area behind the bar, and fall-silt seams that resulted from flood discharge. By summarizing the specific developmental locations and sequential relationships of each fine-grained argillaceous facies in modern sand bar deposits, a depositional process-based argillaceous sediment composition model is proposed. Based on this, this paper discusses the spatial configuration of sand bodies and argillaceous sediments in sand bar reservoirs, and introduces the typical stratigraphic structures of sand bars in two environments, i.e., vertical superposition and lateral migration. In lacustrine nearshore sand bar reservoirs, the deposition and preservation degrees of mud mainly depend on three factors: accommodation space change, frequency of base-level cycles, and exposure-erosion time. These in turn influence the continuity and relative contents of sand and mud in reservoirs. The distribution of argillaceous sediments forms different orders of interlayers, which affects the heterogeneity and fluid percolation of sand bar reservoirs. Clarifying the space-matching relationship of sand and mud in sand bar deposits provides geological models and information parameters for the refined characterization and modeling of the internal configuration of sand bar reservoirs. Furthermore, this work offers guidance for the optimal adjustment of reservoir development strategies or the optimization of reservoir development plans.

Analysis of Spatial Distribution Pattern of Reservoir Petrophysical Properties for Horizontal Well Performance Evaluation-A Case Study of Reservoir X

Introduction:Building a large number of static models to analyze reservoir performance is vital in reservoir development planning. For the purpose of maximizing oil recovery, reservoir behavior must be modelled properly to predict its performance. This requires the study of the variation of the reservoir petrophysical properties as a function of spatial location.Methods:In recent times, the method used to analyze reservoir behavior is the use of reservoir simulation. Hence, this study seeks to analyze the spatial distribution pattern of reservoir petrophysical properties such as porosity, permeability, thickness, saturation and ascertain its effect on cumulative oil production. Geostatistical techniques were used to distribute the petrophysical properties in building a 2D static model of the reservoir and construction of dynamic model to analyze reservoir performance. Vertical to horizontal permeability anisotropy ratio affects horizontal wells drilled in the 2D static reservoir. The performance of the horizontal wells appeared to be increasing steadily as kv/kh increases. At kv/kh value of 0.55, a higher cumulative oil production was observed compared to a kv/kh ratio of 0.4, 0.2, and 0.1. In addition, horizontal well length significantly affects cumulative oil production of the petroleum reservoir studied.Results:At kv/kh of 0.55, the results of the analysis showed a rapid decrement in cumulative oil production as the horizontal well length decreases. Considering horizontal well length of 3000 ft, 2000 ft, and 1500 ft, a minimum cumulative oil production was obtained from a horizontal well length of 1500 ft.Conclusion:The geostatistical and reservoir simulation methods employed in this study will serve as an insight in analyzing horizontal well performance.

A new method to determine reasonable well pattern density in low-permeability gas reservoirs

The productivity evaluation of gas reservoirs is used to determine the optimal number of well pattern, which is an important part of the preparation of gas reservoir development plan. Using integral transformation and asymptotic analyses to solve the pseudo steady-state flow model in closed rectangular gas reservoir of constant thickness, analytic solution of pressure distribution of eccentric well can be obtained. This paper presents mathematical model of multiple wells producing from a closed gas reservoir by applying the principle of pressure superposition. The pseudo steady-state dimensionless production index is introduced to solve the multiple well mathematical models under the constant pressure, and the number of production wells and cumulative production in different production interval are obtained. The results of the calculation shows that the curve of the cumulative production and economic benefits have a maximum value when the producing time, gas price, and drilling costs are given, so it can determine the optimal number of wells and provide the basis for making gas reservoir development plan.

Scale up of pore-scale transport properties from micro to macro scale; network modelling approach

Prediction of reservoir production using different technical scenarios and designs is essential for optimization of reservoir development plan. Due to the enormous scale of a reservoir, the simulators use simplified discretized equations to predict the production and other properties of the reservoir. Therefore, they cannot observe complicated physical phenomena that occur at the pore scale. Such phenomena have significant effect on the relative permeability of the fluids which is an important factor for predicting multiphase flow behaviour at reservoir scale. To remedy this problem, one can simulate the fluid flow in the pore scale and predict relative permeability curves for various rock types. To scale up the relative permeability curves from the pore-scale, it is necessary to scale up the porosity, permeability, and capillary pressure curves. This study is the first step towards this goal. The objective of this research is to calculate the single phase and immiscible two-phase flow properties including porosity, permeability, and capillary pressure of drainage and imbibition processes using random-network modelling technique and then scaling up the results to macro scale. This is done by generating four virtual porous media with various properties by simulating sedimentation process and dividing them into 8 sub-segments. Flow properties of all the sub-segments are computed using a network modelling technique. Flow properties are then scaled up to reconstruct the original macro scale media. Finally, the results are compared to ones obtained directly from the original samples. Results show relative errors ranging from 2% to 10% for homogenous and heterogenous media respectively. As the level of heterogeneric increases, deviation of the scaled-up properties from original values rises.

Reservoir architecture and fracture characterization of low-permeability sandstone reservoir: a case study of Biandong oilfield, Jinhu depression, northern Jiangsu Basin, China

Fracture is one of the most important factors through the whole process of low-permeability reservoir development. Biandong oilfield is a typical low-permeability fractured sandstone reservoir, and has stepped into high water cut stage; thus, the waterflooding effect is poor. Therefore, many contradictions such as high moisture content, decreasing production speed, and low recovery efficiency are becoming increasingly prominent, which have seriously hindered the sustainable development, and need to be solved urgently. However, few such studies on reservoir characterization in low-permeability fractured sandstone reservoir have been conducted in China. In this study, through comprehensive analysis on reservoir characterization and sedimentary environment, significant results are achieved. Three types of fracture occurrence are identified; they are high-angle fracture, low-angle fracture, and horizontal fracture, respectively. Two types of reservoir pore (primary porosity and secondary porosity) are recognized based on thin-section observation and analysis. The diagenetic stage of Biandong oilfield are divided into three stages, early A, early B, and late A, respectively. Finally, a regional discrete fracture network model is established with Fisher’s algorithm based on three-dimensional geological model. All the research results presented above can make a significant instructing function for making reservoir development plan and improving recovery efficiency.

The dynamic effect in capillary pressure during the displacement process in ultra-low permeability sandstone reservoirs

The relationship between the capillary pressure and saturation is a primary factor to describe and simulate the multiphase flow. This relationship is also fundamental to understand the characteristics of oil and gas reservoirs and make the reservoir development plan. Traditionally, the capillary pressure is measured under the equilibrium process; however, this equilibrium is hard to establish when the multiphase flow is expected in low to tight permeability porous media, and the capillary pressure is dynamic. This laboratory study conducts specially designed dynamic displacement experiments to examine the dynamic effect in capillary pressure in ultra-low permeability sandstone oil reservoirs. The dynamic capillary pressure, the dynamic relative permeabilities, the dynamic coefficient and the change rate of water saturation are obtained. Results show that the dynamic coefficient is relatively larger in ultra-low permeability reservoirs compared with that in high to low permeability reservoirs. Difference between the dynamic and the steady capillary pressures becomes more significant for less permeable porous media, with a higher dynamic coefficient and a stronger dynamic effect. Wettability advancement has been triggered during the dynamic displacement process, which is responsible for the water-wet rock before the displacement to be oil-wet during the displacement process. The difference between the dynamic and the steady relative permeabilities becomes obvious, and the dynamic effect in capillary pressure cannot be neglected when the permeability reaches ultra-low. The dynamic coefficient can reveal the shape of the displacement front. Cited as : Li, Y., Li, H., Cai, J., Ma, Q., Zhang, J. The dynamic effect in capillary pressure during the displacement process in ultra-low permeability sandstone reservoirs. Capillarity, 2018, 1(2): 11-18, doi: 10.26804/capi.2018.02.01

A new fast approach for well production prediction in gas-condensate reservoirs

Prediction of gas-condensate well production is significant for sensible decision making for the reservoir development plan, infrastructure investment, and produced gas and condensate sales contract. Typically, time-consuming numerical simulation with fine grids or local grid refinement around the well is implemented in order to capture the effects of condensate blockage and predict gas-condensate well deliverability. In addition, in the commencement of the reservoir lifetime, the numerical simulation predicts erroneous results due to high uncertainty in reservoir data. A simple analytical model can estimate gas-condensate well production reasonable with a limited number of input data. On the other hand, uncertainty studies require repetitious usage of the analytical calculation. Therefore, a faster and more practical method for calculation of gas-condensates well flow rate has a precious value. In this paper, a fast analytical method is introduced for prediction of gas and condensate production profiles based on the two-phase pseudo-pressure integral and material balance equation. Proposed analytical model in contrast to previous ones, predicts the exact plateau time. As the result, it does not need iteration in each reservoir pressure step to compute the relevant flowing bottom-hole pressure during the constant gas production period. The model is expanded to take into account the high-velocity phenomena in near the wellbore region. It is also extended for the first time for different well geometries including vertical, deviated, horizontal, and hydraulic-fractured wells. Additionally, the analytical model is validated using fine grid numerical simulation for a wide range of rock and fluid properties. The developed analytical model can be used as a fast engineering tool for evaluating the uncertainty in well and reservoir data to choose the best strategy for reservoir development.

Integral analysis of geological and field data for selection of oilfield development strategy

The reservoir development plan is a complex process and should be analysed from different points of view. The process was analysed in terms of geology, petrophysics, modelling, production technology and economics. Therefore, different methods should be used for the project.

Geomechanical modelling of fault reactivation in the Cooper Basin, Australia

ABSTRACTThe Australian Cooper Basin is a structurally complex intra-cratonic basin with large unconventional hydrocarbon potential. Fracture stimulation treatments are used extensively in this basin to improve the economic feasibility; however, such treatments may induce fault activity and risk the integrity of hydrocarbon accumulations. Fault reactivation may not only encourage tertiary fluid migration but also decrease porosity through cataclasis and potentially compartmentalise the reservoir. Relatively new depth-converted three-dimensional seismic surveys covering the Dullingari and Swan Lake 3D seismic surveys were structurally interpreted and geomechanically modelled to constrain the slip tendency, dilation tendency and fracture stability of faults under the present-day stress. A field-scale pore pressure study found a maximum pressure gradient of 11.31 kPa/m within the Dullingari 3D seismic survey, and 11.14 kPa/m within the Swan Lake 3D seismic survey. The present-day stress tensor was taken from previously published work, and combined with local pore pressure gradients and depth-converted field-scale fault geometries, to conclude that SE–NW-striking strike-slip faults are optimally oriented to reactivate and dilate. High-angle faults striking approximately E–W appear most likely to dilate, and act as fluid conduits irrespective of being modelled under a strike-slip or compressional stress regime. Near-vertical SE–NW and NE–SW-striking faults were modelled to be preferentially oriented to slip and reactivate under a strike-slip stress regime. Considering that SE–NW-striking strike-slip faults have only recently been interpreted in the literature, it is possible that many reservoir simulations and development plans have overlooked or underestimated the effect that fault reactivation may have on reservoir properties. Future work investigating the likelihood that fracture stimulation treatments may be interacting, and reactivating, pre-existing faults and fractures would benefit field development programs utilising high-pressure hydraulic fracture stimulation treatments.

Efficient Particle Swarm Optimization of Well Placement to Enhance Oil Recovery Using a Novel Streamline-Based Objective Function

One of the main reservoir development plans is to find optimal locations for drilling new wells in order to optimize cumulative oil recovery. Reservoir simulation is a necessary tool to study different configurations of well locations to investigate the future of the reservoir and determine the optimal places for well drilling. Conventional well-known numerical methods require modern hardware for the simulation and optimization of large reservoirs. Simulation of such heterogeneous reservoirs with complex geological structures with the streamline-based simulation method is more efficient than the common simulation techniques. Also, this method by calculation of a new parameter called “time-of-flight” (TOF) offers a very useful tool to engineers. In the present study, TOF and distribution of streamlines are used to define a novel function which can be used as the objective function in an optimization problem to determine the optimal locations of injectors and producers in waterflooding projects. This new function which is called “well location assessment based on TOF” (WATOF) has this advantage that can be computed without full time simulation, in contrast with the cumulative oil production (COP) function. WATOF is employed for optimal well placement using the particle swarm optimization (PSO) approach, and its results are compared with those of the same problem with COP function, which leads to satisfactory outcomes. Then, WATOF function is used in a hybrid approach to initialize PSO algorithm to maximize COP in order to find optimal locations of water injectors and oil producers. This method is tested and validated in different 2D problems, and finally, the 3D heterogeneous SPE-10 reservoir model is considered to search locations of wells. By using the new objective function and employing the hybrid method with the streamline simulator, optimal well placement projects can be improved remarkably.

Optimizing production from water drive gas reservoirs based on desirability concept

There are various factors which determine the optimization and economic production from water drive gas reservoirs. These factors play an important role in designing an effective reservoir development plan. The present study, in the first step, investigates the relation between recovery factor, volumetric sweep efficiency and cumulative water production with six different engineering and geologic factors using design of experiments (DOE) and response surface methodology (RSM). Next, all derived response functions are optimized simultaneously based on the concept of desirability. In this manner, part of water drive gas reservoirs is simulated using Box–Behnken design. Important factors that have been studied include reservoir horizontal permeability (Kh), permeability anisotropy (Kv/Kh), aquifer size (Vaq), gas production rate (Qg), perforated thickness (Hp) and tubing head pressure (THP). The results indicate that by combining various levels of factors and considering relative importance of each response function, optimized conditions could be raised in order to maximizing recovery factor, volumetric sweep efficiency and minimizing cumulative water production. Also high rates of gas production result poor volumetric sweep efficiency and early water breakthrough, hence ultimate recovery factor decreases by 3.2–8.4%.

Dynamic monitoring of coalbed methane reservoirs using Super-Low Frequency electromagnetic prospecting

Dynamic monitoring of coalbed methane (CBM) reservoirs plays an important role in reservoir evaluation, production estimation, exploitation and development planning in order to efficiently operate producing wells. This paper proposes a passive Super-Low Frequency (SLF) electromagnetic prospecting and monitoring method, which helps us derive electromagnetic radiation (EMR) anomalies from reservoirs to directly identify and dynamically analyze CBM reservoirs. The modeling study shows that the SLF magnetic responses are sensitive to high resistivity layers. These responses turn out to be approximately stationary and can be seen as simply a component of the background field. This stationary background field can be clearly distinguished and then dynamic anomaly extraction would be completed. In order to suppress cultural noise and high frequency (HF) random noise, the methods of empirical mode decomposition (EMD) and wavelet transform are used in data processing. The reconstructed curves are employed to identify EMR anomalies at corresponding depths of reservoirs, and subsequently help directly interpret and dynamically monitor reservoirs. The SLF prospecting method is validated using the field data observed from CBM wells in the years from 2007 to 2013 in Qinshui Basin, China. The results present that the high EMR “wave packets” contribute conceivably to the CBM reservoir identification. Compared with audio-magnetotelluric (AMT) inversion results, the SLF identification resolution is greatly improved. The dynamic characteristics of producing reservoirs are revealed using EMR anomalies, and agree with production histories and other surveys.