Optimizing a Complex, Uneven and Low-Resolution Reservoir While Using Dynamic Dataset for Structure Definition

In the midst of current oil prices, most companies have shifted their focus on cost-constrained policies for hydrocarbon exploitation, thereby making robust subsurface description a real challenge. Developing a reservoir in such scenario is a massive problem. This study presents various engineering algorithms on such a low-resolution and uneven sandstone reservoir, to optimize the development and expected ultimate recovery - while honoring multiple challenges and limitations. This study focuses on a newly discovered formation, in one of the oldest fields in Pakistan. The productive section of the reservoir comprises of sandstone units in beds up to 40 m thick, separated by mudstone intervals; and is interpreted to be deposited in lower progradational intervals of a delta. To date, three different depositions have been identified with two of them in hydraulic communication and one isolated with faults. Since the seismic data has limitations in its resolution; various engineering analyses were carried out, among which the variations in reservoir pressures, GWC and PVT properties played a major role in the identification of partially drained and isolated prospects. The first two successful wells in the isolated compartment were high producers. However, sudden water production (from fractures) loaded up these wells with only 45% recovery from the compartment - very low for a weak-water drive dry gas system. The static and dynamic data set also showed the existence of more Hydrocarbons. Thus, several engineering and geological information, including the re-interpreted Seismic and simulation models, were applied to analyze the possibilities of concurrent sweet spots. Finally, after utilizing multiple algorithms & risk calculations, more wells were drilled - leading to the revelations of two more depositions in the reservoir, which were in hydraulic communication with each other but isolated with the first compartment. This added around 60% more reserves to the current mix of resources. Two more wells are now planned in the reservoir to optimize the field potential in both compartments. This will lead to an additional 23% reserves value, giving an overall EUR of ~83% from these compartments. The main achievement of this study includes the exploitation strategy of a complicated depositional system to optimize a reservoir full of uncertainties. Since the seismic cannot be solely relied upon in such formations; this paper also illustrates the robust engineering models and detailed algorithms to ensure the development of such low-resolution reservoir without incurring major costs. This study offers an innovative approach that can be undertaken to place the wells at optimum locations, along with the utilization of each data set in a more systematic manner to access the, otherwise, undrained locations.

Reservoir heterogeneity understanding is critical to predict gas-water contact (GWC) movement in order to take early preventative measures to delay water breakthrough in wells and hence improve Well, Reservoir and Facilities Management (WRFM). This maximizes ultimate recovery of a gas brownfield. The carbonate gas field investigated in this paper (called Delta Field) is located in Central Luconia, with 20 years of production history. It is a platform type carbonate build-up, penetrated by eight production wells and a water disposal well. The contact movement of the reservoir was monitored using well surveillance logs. After 5 years of production, a horizontal well (Delta-110S1) was drilled in the southern part of the field. The well targeted attic gas at the top of the reservoir and was designed with a horizontal drainage bore to avoid early water breakthrough. However, it encountered water breakthrough in Feb 2004 after 1.5 years of production. By 2007, all Delta Field wells were producing water. This indicated that the gas-water contact (GWC) rose non-uniformly with water encroachment faster in the southern area of the field compared to the north, resulting in a tilted GWC. Hence, a ‘back-to-basics' reservoir characterization was required to understand the reservoir architecture and heterogeneities. Reservoir characterization was carried out to identify and map out the distribution of low porosity zones within the carbonate reservoir, based on seismic and well-log data as well as regional understanding. In the Central Luconia carbonate fields two types of tight layers with very different dynamic behaviours are encountered: (1) Tight layers that formed by floodings events with a large lateral extent and continuity, acting as baffles to gas and water flow, and (2) tight layers related to exposure-events with a more patchy distribution, which can act as minor, local baffles but can also function as conduits for water when they are related to karsts and/or fractures. To distinguish the nature of the tight layers and predict their dynamic behaviour, they were mapped out within and between platforms and calibrated with core and seismic data, to understand their depositional origins that control their properties impacting flow and their continuity. Subsurface reservoir models focusing on the key reservoir heterogeneities that matter for flow were built by incorporating core, well log, drilling and seismic data. Integrating this static understanding with completion data (perforation intervals, water shut offs) and dynamic data (GWC-rise history, production and water-cut rates) provided valuable insights into the evolution of the GWC movement and allowed more accurate prediction of production rates and identification of suitable infill well locations. Through this study, an infill well opportunity was identified to target remaining attic gas in the northern part of the field. In 2013, Delta-111S1 was abandoned and side-tracked to target remaining attic gas in the north of the field. Delta-111S2 achieved the first gas in December 2013 and has produced very successfully.

This paper presents the development of a static model for a naturally-fractured High-Pressure-High-Temperature (HPHT) gas sand reservoir located in the Tarim basin, Western China. The study is part of a well placement optimization study. It is motivated by the big challenges of drilling a well at depths ranging from 6800m-8000m[AG1] in a HPHT environment. A detailed fine-scale model is required as input for the dynamic model. The static model is developed through an integration [AG2]process. It consists of both matrix and fractures. The matrix modeling started by integrating 3D seismic and log data to build the structural model. A new rock type scheme was developed by reconciling log and core data, including capillary pressures. Additionally, permeabilities are estimated at each uncored location using a two-step approach, namely trend estimation by regression analysis and variability simulation by 1D Gaussian simulation. The 3D modeling was executed in the order of least dependent to most dependent variable (i.e., from facies, to rock type, then followed by porosity, permeability and saturation respectively). From the geology, the sand bodies were interpreted to be continuous throughout the field. Discontinuous mudstone layers are sandwiched in-between the sand bodies. This information, together with outcrop data, is used to guide the spatial relationships in the model. Facies, rock type, porosity and permeability are simulated using geostatistical procedures. Meanwhile, saturation is generated based on the Leverett J-Function. To quantify the uncertainty in the various data, especially in the capillary pressure data, the porosity-permeability relationship, the gas-water contact and the surface tension of the gas-water system, a probabilistic model of the Gas Initially in Place (GIP) is created through uncertainty and sensitivity analysis. The origin of the fracture system was analyzed by developing a prototype of a conceptual model. The understanding from the prototype model is coupled with the 3D seismic, outcrops, drilling information, rock mechanics, image log, core, and dynamic data, to develop fracture characteristics and correlations. The discrete fracture system is modelled using a stochastic simulation approach, constraining it to the seismically-inverted fracture density map for each zone through well-seismic correlations and a nonlinear inversion [AG3]to build the Discrete Fracture Network (DFN). Finally, the fracture model is integrated with the matrix model by upscaling the DFN model into the grid system. Following the creation of the static model, a dual porosity model was prepared for dynamic modeling by maintaining consistency between the fine scale and upscaled models throughout the upscaling process. The methodology described above has produced a detailed fine scale model that shows consistency between properties and geology. This is a direct consequence of the new rock type system and the order in which the simulation was conducted. The facies model shows the continuity of the sand bodies, and the discontinuity of the mudstone, as indicated by the geological interpretation. The 3D Poro-Perm relationship shows the variability which is a reflection of the variability of the core data. The probabilistic distribution of the GIP is in agreement with the results of conventional reservoir engineering analyses, namely Material Balance and Rate Transient Analysis. Furthermore, the fracture distribution confirms the information both at the wells, as well as in-between the wells as given by the seismic interpretation. This study demonstrates that a reliable fine scale model can be developed to match the available data and interpretation by properly preparing the pre-requisite inputs and following the order of dependency in the reservoir attributes.

Interests in skyline query processing have significantly increased since it can be used in many applications, such as multi-criteria decision making, data mining, and user preference queries. In this paper, we propose continuous skyline queries over dynamic data set. Since the dynamic data set constantly changes as time passes, continuous skyline queries processing over dynamic data set becomes ever more complicated compared with static data set. We propose a multiple layer grids scheme for efficiently processing continuous skyline queries over skewed data set. The proposed scheme divides the work space into multiple layer grids and creates the skyline influence regions of each layer grid based on the existing data set. The continuous skyline queries are handled only when the dynamic data points update within the skyline influence regions of each layer grid. Since the multiple layer grids are divided dynamically, it is feasible even for the highly skewed data set. Experiments based on various synthetic data sets and real data sets show that our proposed scheme outperforms the existing schemes.

The development of seismic technology has made seismic data to be widely used in the interpretation of stratigraphic sequence frames, reservoir identification, fluid detection, and other research fields involved in reservoir description. The 3D technology reservoirs have always been the focus, as well as difficulty, of research. With the rapid development of information technology and the continuous improvement of seismic exploration level, people have put forward higher requirements for the accuracy of seismic data interpretation results. Aiming at the large number of structural and unstructured data in seismic, logging, geology, and other disciplines involved in seismic interpretation, how to effectively organize and coordinate analysis to discover the hidden reservoir structure and oil and gas distribution information has always been a geological and important topic for information processing technicians. This thesis is aimed at the current high-water-phase development of Shengtuo Oilfield reservoir and the problems existing in geological research. Based on seismic structural interpretation and attribute analysis, this paper analyzes the reservoir structural characteristics, sedimentary characteristics, and reservoir physical parameter characteristics based on geology, logging interpretation, core analysis, drilling, and seismic interpretation. Using the kriging method with external drift can cooperate with seismic variables to establish a reservoir geological model to study the Shengtuo Oilfield reservoir. We combine artificial intelligence technology with geological modeling technology of seismic interpretation results to explore the best method for predicting earthquakes. The research results in this paper show that the relative error of the model established by the kriging method in the article is relatively small for thinning wells, mainly concentrated around 1%. Examination of the thinning wells of 45 wells shows that the model established is basically good and the example has high accuracy. The research results in this paper have a guiding study of distribution and tapping potentials in the study area, formulating reasonable development and adjustment plans and improving oil recovery.

Generation and transmission of complex animation sequences can benefit substantially from the availability of tools for handling large amounts of data associated with dynamic three-dimensional (3-D) models. Previous works in 3-D dynamic compression consider only the simplest situation where the connectivity changes do not occur with time. In this paper, we present an approach for compressing 3-D dynamic models in which both the vertex data and the connectivity data can change with time. Using our framework, 3-D animation sequences generated using commercial graphics tools or dynamic range data captured using range scanners can be compressed significantly. We use 3-D registration to identify the changes in the vertex data and the connectivity of the 3-D geometry between successive frames. Next, the interframe motion is encoded using affine motion parameters and the differential pulse coded modulation (DPCM) predictor. Our work is the first to exploit the temporal coherence in the connectivity data between frames and presents a detailed encoding scheme for 3-D dynamic data. We also discuss the issue of inserting I-frames in the compressed data for better performance. We show that our algorithm has a far superior performance when compared with existing techniques for both vertex compression and connectivity compression of 3-D dynamic datasets.

A single well, satellite gas accumulation offshore North Trinidad exhibits a strong water drive mechanism and is in pressure communication with two neighbouring fields through a common aquifer. Monitoring and predicting the movement of the gas water contact (GWC) is critical to reservoir management and resources estimation. This paper is the culmination of a study that was conducted over a five-year period, analyzing high quality downhole pressure buildup data to track the GWC movement in the field. Analysis of late time boundary dominated flow regime in multiple time lapsed pressure derivatives indicated a movement in the gas-water phase boundary, believed to be the contact. Pressure transient analysis (PTA) enabled the translation of shifting pressure derivatives to alternate GWC contour realizations. These matched derivatives provided a quantitative estimation of the contours which were then converted to an equivalent contact radius. For both edge water or bottom water drive mechanisms, the equivalent contact radius was then correlated to the field's cumulative gas produced. Prediction of water breakthrough was done by estimating a range of contours arriving near the well and calculating the corresponding recoverable gas volume from the generated correlation. Multiple analytically derived functions were used to correlate the equivalent contact radius with the gas produced. A strong correlation was observed on regressing produced volumes with the interpreted contact radii. Due to inherent uncertainties with sweep efficiency, as a proxy, three idealized cases were defined for arrival of water close to the well to capture a low, mid and high scenario. Using these cases, water breakthrough was predicted to occur for produced volumes in the range of 58 Bscf to 70 Bscf, with a mid-case of 64 Bscf. In May 2015, actual water breakthrough occurred after 62 Bscf of production thus, strongly validating the robustness of the time lapse pressure derivative analysis study. For gas reservoirs supported by moderate to strong aquifer drive, we suggest this as a robust workflow independent of 3D numerical reservoir simulation to predict recoverable volumes and water breakthrough timing. The observation of contact movement for gas reservoirs connected through a common aquifer could have significant implications on the conventional understanding around such reservoirs and their optimum management strategy.

Mature and complex reservoirs are usually covered by many kinds of static and dynamic data—i.e. petrophysical, PVT, well testing, geologic, completion, and reservoir production information. This paper illustrates an effective methodology to develop a consistent simulation model, via integration of the available static and dynamic data sets, that allows better understanding of the subsurface reservoir flow characteristics. A complex gas condensate reservoir, referred to as reservoir X and first put into production 14 years ago, serves as the example in this paper. There is abundance of available data from different sources. However, the data can not be directly applied to build a reservoir prediction model because of the various measurement scales—e.g., core = about 0.1 ft long, log = tens of feet away from wellbore, and reservoir simulation = hundreds of feet for the grid size. In some cases, the same parameter is derived from different sources—i.e., permeability from core samples, logging data, and pressure transient test. Due to the extreme intrinsic complexity of reservoir X, actual subsurface flow characteristics were not well understood before this study. By using the proposed methodology, a reliable, coherent and improved reservoir simulation model was built. In the past decade, the multidisciplinary approach (usually including geology, geophysics, petrophysics, reservoir engineering, and production engineering) has gained popularity in industry's attempt to achieve more effective reservoir management. This paper focuses on a multidisciplinary approach that integrated PVT data, well tests, geologic, petrophysical, and dynamic reservoir production information to build a reservoir simulation model, which can be used to predict reservoir performance. Reservoir X, discovered in early 1980s in Tarim Basin (P.R. China), is a gas condensate reservoir without oil rim. Geologic formations of this reservoir are relatively flat with only a few degrees of inclination. The depositional environment is fluvial-delta with bedded sandstones. The southern boundary …

The deep gas trend in west Texas includes an area of 9,000 sq mi underlain by favorable reservoir rock in the Delaware and Val Verde basins. Approximately an eighth of the favorable area has been explored. In addition, only Wolfcampian and older formations are considered. This trend should develop into the largest gas-producing area in the world. Expensive drilling costs, carbon dioxide gas distribution, the uncertainty of future gas prices, lack of deep subsurface data, and difficulty with seismic interpretations have caused an erratic development. The first giant gas field was discovered in 1952. Subsequent discoveries have established the deepest gas production in the world, some fields having as much as 3,500 ft of gas column above the gas-water contact. On the basis of reserve prediction methods developed by Hendricks, huge volumes of gas in place remain to be discovered. End_of_Article - Last_Page 751------------

Over the past two decades, significant geological exploration work, including seismic exploration, has been carried out within the junction zone of the Vilyui syneclise and the Aldan anteclise. In addition, oil and gas companies are also interested in this territory, acquiring licenses for the search and exploration for hydrocarbon deposits. The object of the study is the terrigenous deposits of the Permian system. The main oil and gas potential of this territory is associated with these Permian deposits. Within the Vilyui syneclise, there are gas fields in the Permian deposits, which provide gas to the central regions of Yakutia. Thus, it is necessary to update the oil and gas potential of the area. The study was based on seismic exploration data, deep well data, including well logging curves, core descriptions, and Permian sediment test results. Previously published literature on the geological structure of Permian rocks was also analyzed. Our seismic interpretation and analysis of well data resulted in structural surfaces. The structural surfaces characterize Permian, Triassic and Jurassic sediments. The thickness maps have been used to determine the distribution areas of Permian deposits, Triassic and Jurassic fluid-sealing rocks. Using structural maps, thickness maps, faults and well data, the most oil and gas promising zones and objects of Permian deposits were identified. The promising zones are associated with a reduction in the thickness of Permian deposits, and identified near the wedge line. The fault-limited positive structures are promising objects.

The field-A1 is an offshore gas field located about 56 km from the coast of East Africa with the water depth of 1153 m. The permeability distribution varies across different layers with an overall permeability of 680 m and porosity distribution for the reservoir field-A1 varies 0.21-023. The reservoir thickness also varies up to 50 m thick. This research work identifies parameters that will contribute to the impact of water coning. Simulation sensitivities are run to observe the effect of water coning/cresting in horizontal gas wells and predicting the performance of these wells using Petrel simulator. Results have shown that put horizontal well in East-west will have early water breakthrough and not recommended due to the impact of edge aquifer due to less recovery compared to north-south and original wells orientation (northwest-southeast). The varying height of perforation and standoff as identified is at the standoff between 30-40 m in the field-A2 will delay water coning high recovery with more extended plateau length period. The gas recovery may happen to be low, due to the distribution of permeability layer for the horizontal wells and low productivity index that is the performance of the well. Rate-dependent skin and mechanical skin evolution in time show that increasing non-Darcy /turbulence factor reduces the performance of the well and decreases gas recovery the high drawdown tendency is observed before water breakthrough time however there is early water breakthrough, thus use of deep penetration. Horizontal gas wells have a constant horizontal length for all cases of 300 m increasing tubing head pressure from 40-100 bars result to decrease plateau length period of the gas production, low water production rate, and low gas recovery. Varying the kv/kh ratio from 0.1, 0.6 to 1 shows early water breakthrough by 6 months earlier from the base case with 0.1 hence will not delay water coning. The gas recovery is reduced by 5%. Gas recovery is increased with an increase in gas rates constrain, and early water breakthrough is observed when producing at high rates. Producing at low rates may delay water coning. However, it is not economical since there is less gas recovery and may take a more extended period for production to reach to its total maximum gas production of which is less compared when producing at high gas rates. There is a stronger of the aquifer from the west side, which is predictable to cause water coning than on the east side. This aquifer impacts the gas recovery reduction by 19%, with water coning radial extension of 1.7 km and peak water production rate for 16 years. The aquifer influx rate is seen to be increased by 69% when the aquifer volume is double. Therefore, from the results producing at a high rate that has high recovery before the impact of aquifer or water has occurred to the wells, known as outrunning of the aquifer. To avoid water coning, using advance completion technique such as inflow control devices (ICD), installing a down hole gauge. Also, it is essential not to perforate if well is near to gas water contact the horizontal wells should be located at maximum distance from gas water contact to maximize gas recovery. Not only that but also use of fully open choke allows much water production rate increase, which leads to water coning.

One of a key responsibility for oil and gas industry is to ensure the balance between energy sustainability and minimizing the net carbon footprint to the environment. PTTEP, Thai national oil and gas company, has aligned this goal to achieve net zero greenhouse gas emission in 2050. Therefore, the scope of this project is to utilize carbon capture and storage (CCS) technology by injecting CO2 into the depleted reservoirs in the Gulf of Thailand. To evaluate the feasibility of the project, the simulation model was required to mimic the physics behaviors, including free gas structural storage, residual trapping, soluble gas in water and mineralization, when the CO2 was injected into many layers of depleted reservoirs. This is to obtain the optimized scenario for CO2 injection. However, the key step for reservoir simulation is the history matching by calibrating the model with production data. First, the static model was built by integrating geological understanding, well data, logging data and petrophysical interpretation, core data, and quantitative interpretation (QI) from seismic data. Then, the subsurface uncertainties were captured and transferred to dynamic model for history matching step. The sensitivity analysis was performed to understand causes and effects and determine the significant uncertain parameters. Then, the assisted history matching was performed to explore the possible solutions using evolutionary algorithm. Lastly, multiple realizations of history matching solutions were obtained. From sensitivity analysis, the key parameters to be calibrated with production data and routine shut-in bottomhole surveys are gas-water contacts, porosity and permeability correlation and relative permeability endpoint parameters. From history matching solutions, we narrowed down the range of uncertainty of uncertain parameters during history matching. The pressure, gas and water production could be matched. Obtaining the calibrated model from history matching is the critical step because this will determine the feasibility of the project in terms of injection strategy and CO2 storage volume. This study was the first history matching task performed for Thailand CCS project. The practical and robust history matching workflow used in this CCS project could be set as a milestone and provides the guideline how to implement assisted history matching technique for any future CCS projects.

Gas reservoirs in the Nile Delta of Egypt are characterized vertically by its thin beds of sands and shale and laterally by severe variations in facies. These challenges in the static modeling have a strong impact in the dynamic modeling which can be summarized in the following points. First, the vertical sequence of sands and shale leads to the difficulty in detecting a single gas-water contact in the field. Second, the vertical heterogeneity leads to the use of fine gridding especially in the vertical direction to accurately simulate the fluid flow in the reservoir. Third, the lateral variation in facies forces to use different saturation functions at different parts of the reservoir.The dynamic behavior of pressure and production performance from few wells (total seven wells) producing from this field show severe vertical discrepancy in pressure, gas and water production. This adds another challenge in the dynamic modeling and leads to dividing the field into three main reservoirs that are completely isolated with each has different reservoir and production characters.Due to these challenges, we developed an unconventional approach to model this field and estimate its gas in place that honors both static and dynamic data. First, we used the concept of initialization by enumeration instead of the conventional approach of initialization by equilibration that requires accurate detection of gas-water contact. The initial pressures are obtained from MDT (Modular Dynamic Tester) data and the water saturation are obtained from the petrophysical analysis in initial wells and populated in the reservoir to honor the seismic and the production data. Second, we used low vertical permeability to simulate the vertical variations in sand-shale sequence. This also helps in reducing the severity of the phases being not in equilibrium due to the initialization by enumeration. Third, we used fine gridding to capture the heterogeneous variation in property. To reduce the CPU time for running one single fine grid model, we divided it into three different models each represent one reservoir with running each model separately. Both production and pressure data confirms that these reservoirs are completely isolated and no wells are producing commingled from these reservoirs thus separating them will not have any effect on its performance.This work summarizes the workflow we developed in the dynamic modeling of this field, the history match approach we used to calibrate the model and finally the suggested optimum development plan to increase its reserves.

We present a new exploration and optimization method to select customized implementations for dynamic data sets, as encountered in telecom network, database and multimedia applications. Our method fits in the context of embedded system synthesis for such applications, and enables to further raise the abstraction level of the initial specification, where dynamic data sets can be specified without low-level details. Our method is suited for hardware and software implementations. In this paper, it mainly aims at minimizing the memory power consumption, although it can also be driven by other cost functions such as area or performance. Compared with existing methods, it can save up to 2/3 of the memory power consumption and 3/4 of the memory area.

During the last decade, some problems have appeared and being affecting the oil production of the mature giant oil field such as: flow boundaries, by pass zones, fractures, etc. hence, the characterization of the reservoir by the integration of static and dynamic data acquired along the field life is required. The new generation of static model is justified in the need to involve the lessons learnt from the previous static/dynamic models with the incorporation of the recent studies and well data. The aim of this article is to integrate the structural seismic interpretation and results of pressure transient analysis obtained from well test, such as distance to potential flow boundaries, average permeability, among others, into the workflow of the new geological static model, through the validation with the conceptual geological understanding of the reservoir. Such workflow not only considers different sources for the reservoir characterization but also reduce the alternative solutions of the well test data to the best-fit solution for the integration. In a typical geological modeling workflow, structural framework is built first, based on the zones definition that include well information, well log data, structural seismic interpretation and the stratigraphic characterization that allow capturing the vertical heterogeneity. Subsequently, the sedimentary-stratigraphic architecture is used as main constrain together with geostatistical methods to distribute the petrophysical properties for each zones. The well test results independently are a punctual dynamic response of the reservoir in a portion of the time and within a certain tested area around the well. However, the integration with the conceptual geological model can resolve the uncertainty that alone cannot respond enable a more robust interpretation of main reservoir heterogeneities. The study proposes the inclusion of the well test data to support and validate, firstly the structural connectivity of the zones through the well test interpretation (validation of faults, dual porosity zones, dense zones, etc.), and secondly calibrate the permeability model with additional dataset than only from cores, which, even though derived from dynamic data, are incorporated in the static model workflow. Implementation of workflow allowed modeling of 48 zones with different petrophysical properties and 122 faults in the static model, which were ranked in three confidence categories. Faults observed by only seismic interpretation were ranked as low, faults calibrated by one of the 57 borehole images logs (BHI) were ranked as mid confidence, and finally, faults that were validated with best-fit result of well test, where interpretation suggest the presence of a boundary as fault and is consistent with the seismic and/or BHI interpretation, is ranked as the highest confidence, inasmuch as the fault is validated statically and dynamically.