reservoir modeling
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Author(s):  
M. F. Abu-Hashish ◽  
M. M. Abuelhassan ◽  
Gamal Elsayed

AbstractRecent advances in computer sciences have resulted in a significant improvement in reservoir modeling, which is an important stage in studying and comprehending reservoir geometry and properties. It enables the collection of various types of activities such as seismic, geological, and geophysical aspects in a single container to facilitate the characterization of reservoir continuity and homogeneity. The main goal of this work is to build a three-dimensional reservoir model of the Abu Roash G reservoir in the Hamra oil field with enough detail to represent both vertical and lateral reservoir heterogeneity at the well, multi-well, and field scales. The Late Cenomanian Abu Roash G Member is the main reservoir in the Hamra oil field. It is composed mainly of shale, carbonate and some streaks of sandstone, these streaks are shaly in some parts. Conducting the 3D geostatic model begins with the interpretation of seismic data to detect reflectors and horizons, as well as fault picking to explain the structural framework and frequently delineate the container style with proposed limitations to construct the structural model. The lithology and physical properties of Abu Roash G reservoir rock, including total and effective porosity and fluid saturation, were determined using well log data from four wells in the Hamra field. The constructed 3D geological model of the Abu Roash G has showed that the petrophysical parameters are controlled by the facies distribution and structure elements, whereas properties are the central part to the northern side of the deltaic environment than the other sides of the same environment. The model will be useful in displaying the reservoir community and indicating prospective zones for enhancing the dynamic model to improve the behavior of the flow unit productivity, as well as, section of the best sites for the future drilling.


2022 ◽  
Author(s):  
Ahmed Elsayed Hegazy ◽  
Mohammed Rashdi

Abstract Pressure transient analysis (PTA) has been used as one of the important reservoir surveillance tools for tight condensate-rich gas fields in Sultanate of Oman. The main objectives of PTA in those fields were to define the dynamic permeability of such tight formations, to define actual total Skin factors for such heavily fractured wells, and to assess impairment due to condensate banking around wellbores. After long production, more objectives became also necessary like assessing impairment due to poor clean-up of fractures placed in depleted layers, assessing newly proposed Massive fracturing strategy, assessing well-design and fracture strategies of newly drilled Horizontal wells, targeting the un-depleted tight layers, and impairment due to halite scaling. Therefore, the main objective of this paper is to address all the above complications to improve well and reservoir modeling for better development planning. In order to realize most of the above objectives, about 21 PTA acquisitions have been done in one of the mature gas fields in Oman, developed by more than 200 fractured wells, and on production for 25 years. In this study, an extensive PTA revision was done to address main issues of this field. Most of the actual fracture dynamic parameters (i.e. frac half-length, frac width, frac conductivity, etc.) have been estimated and compared with designed parameters. In addition, overall wells fracturing responses have been defined, categorized into strong and weak frac performances, proposing suitable interpretation and modeling workflow for each case. In this study, more reasonable permeability values have been estimated for individual layers, improving the dynamic modeling significantly. In addition, it is found that late hook-up of fractured wells leads to very poor fractures clean out in pressure-depleted layers, causing the weak frac performance. In addition, the actual frac parameters (i.e. frac-half-length) found to be much lower than designed/expected before implementation. This helped to improve well and fracturing design and implementation for next vertical and horizontal wells, improving their performances. All the observed PTA responses (fracturing, condensate-banking, Halite-scaling, wells interference) have been matched and proved using sophisticated single and sector numerical simulation models, which have been incorporated into full-field models, causing significant improvements in field production forecasts and field development planning (FDP).


2021 ◽  
Vol 54 (2F) ◽  
pp. 22-35
Author(s):  
Haider Mahmood ◽  
Omar Al-Fatlawi

The paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applied based on sensitivity and uncertainty of five variables to determine an accurate estimation of stock-tank oil initially in place of the reservoir. The oil-water contact appeared to be the major uncertain parameter for stock-tank oil initially in place estimation because the available geological and field data was not enough to demonstrate it confidently, and only 13% of the total wells have penetrated the water zone in the Mishrif formation. The results of all scenarios indicate that the reservoir has huge stock-tank oil initially in place. The importance of developing this oilfield is validated by its very high stock-tank oil. This is where the value of this study becomes obvious.


2021 ◽  
pp. 1-65
Author(s):  
Charlotte Botter ◽  
Alex Champion

Seismic data is one of the main ways to characterize faults in the subsurface. Faults are 3D entities and their internal structure play a key role in controlling fluid flow in the subsurface. We aim to characterize a geologically sound fault volume that could be used for subsurface model conditioning. We present an attribute analysis of a normal fault from a high resolution seismic dataset of the Thebe Field, offshore NW Australia. We merge together a series of common attributes for fault characterization: dip, semblance and tensor (DST), and we also introduce a new Total Horizontal Derivative (THD) attribute to define the edges of the fault zone. We apply a robust statistical analysis of the attributes and fault damage definition through the analysis of 2D profiles along interpreted horizons. Using the THD attribute, we interpret a smaller width of the fault zone and a more straightforward definition of the boundaries than from the DST cube. Following the extraction of this fault volume, we define two seismic facies that are correlated to lithologies extracted from our conceptual model. We observe a wider fault zone at larger throws, which corresponds also to syn-rift sequence, hence more complex internal fault damage. Our method provides volumes at adequate scale for reservoir modeling and could therefore be used as a proxy for property conditioning.


Geosciences ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 520
Author(s):  
Arezki Chabani ◽  
Ghislain Trullenque ◽  
Johanne Klee ◽  
Béatrice A. Ledésert

Scanlines constitute a robust method to better understand in 3D the fracture network variability in naturally fractured geothermal reservoirs. This study aims to characterize the spacing variability and the distribution of fracture patterns in a fracture granitic reservoir, and the impact of the major faults on fracture distribution and fluid circulation. The analogue target named the Noble Hills (NH) range is located in Death Valley (DV, USA). It is considered as an analogue of the geothermal reservoir presently exploited in the Upper Rhine Graben (Soultz-sous-Forêts, eastern of France). The methodology undertaken is based on the analyze of 10 scanlines located in the central part of the NH from fieldwork and virtual (photogrammetric models) data. Our main results reveal: (1) NE/SW, E/W, and NW/SE fracture sets are the most recorded orientations along the virtual scanlines; (2) spacing distribution within NH shows that the clustering depends on fracture orientation; and (3) a strong clustering of the fracture system was highlighted in the highly deformed zones and close to the Southern Death Valley fault zone (SDVFZ) and thrust faults. Furthermore, the fracture patterns were controlled by the structural heritage. Two major components should be considered in reservoir modeling: the deformation gradient and the proximity to the regional major faults.


2021 ◽  
Author(s):  
Rabah Mesdour ◽  
Moemen Abdelrahman ◽  
Abdulbari Alhayaf

Abstract Horizontal drilling and multistage hydraulic fracturing applied in unconventional reservoirs over the past decade to create a large fracture surface area to improve the well productivity. The combination of reservoir quality with perforation cluster spacing and fracture staging are keys to successful hydraulic fracturing treatment for horizontal wells. The objective of this work is to build and calibrate a dynamic model by integrating geologic, hydraulic fracture, and reservoir modeling to optimize the number of clusters and other completion parameters for a horizontal well drilled in the source rock reservoir using simulation and analytical models. The methodology adopted in this study covers the integration of geological, petrophysical, and production data analysis to evaluate reservoir and completion qualities and quantify the heterogeneity and the perforation clusters number required within a frac stage. Assuming all perforation clusters are uniformly distributed within a stage. The hydraulic planer fracture attributes assumed and the surface production measurement together with the production profile were used to calibrate the reservoir model. The properties of the Stimulated Reservoir Volume "SRV" were defined after the final calibration using reservoir model including hydraulic fractures. The calibrated reservoir model was used to carry out sensitivity analyses for cluster spacing optimization and other completion parameters considering the surface and reservoir constraints. An optimum cluster spacing was observed based on the Estimated Ultimate Recovery "EUR" of the subject well by reservoir properties. The final results based on 70% of perforation clusters contribution to production observed from PLT log, and the results of this study were implemented. Afterwards, another study has been undertaken to increasing the stimulation effectiveness and maximizing the number of perforation clusters contributing to productivity as an area for improvement to engineering the completion design. The methodology adopted in this study identifies the most important parameters of completion affecting well productivity for specific unconventional reservoirs. This study will help to engineer completion design, improve cluster efficiency, reduce cost and increase well EUR for the development phase.


2021 ◽  
Author(s):  
Qianru Qi ◽  
Khoja Ghaliah ◽  
Iraj Ershaghi

Abstract With the maturation of many oilfields, further well abandonments will occur in the years to come. There are issues about improper well abandonment that can have far-reaching effects for responsible companies or entities. At this time in the US, where most of the operation is operated by non-government entities, sometimes the sovereign state may end up covering the cost of well abandonment when the operator is not financially capable in managing such costs. That will be a burden to the public taxpayers. In this paper, we review an important aspect of the well abandonment practices and at present, based on a reservoir modeling approach, more clearance on the potential formation of free gas that can be a cause of concern. We also discuss the integrity issues of the sealing process. We point out how the development of cracks caused by many factors, including geomechanical effects or slow deterioration of the cement seal, in the long run, may result in generating escape paths for the evolved hydrocarbon gases.


2021 ◽  
Author(s):  
Abdul Saboor Khan ◽  
Salahaldeen Alqallabi ◽  
Anish Phade ◽  
Arne Skorstad ◽  
Faisal Al-Jenaibi ◽  
...  

Abstract The aim of this study is to demonstrate the value of an integrated ensemble-based modeling approach for multiple reservoirs of varying complexity. Three different carbonate reservoirs are selected with varying challenges to showcase the flexibility of the approach to subsurface teams. Modeling uncertainties are included in both static and dynamic domains and valuable insights are attained in a short reservoir modeling cycle time. Integrated workflows are established with guidance from multi-disciplinary teams to incorporate recommended static and dynamic modeling processes in parallel to overcome the modeling challenges of the individual reservoirs. Challenges such as zonal communication, presence of baffles, high permeability streaks, communication from neighboring fields, water saturation modeling uncertainties, relative permeability with hysteresis, fluid contact depth shift etc. are considered when accounting for uncertainties. All the uncertainties in sedimentology, structure and dynamic reservoir parameters are set through common dialogue and collaboration between subsurface teams to ensure that modeling best practices are adhered to. Adaptive pluri-Gaussian simulation is used for facies modeling and uncertainties are propagated in the dynamic response of the geologically plausible ensembles. These equiprobable models are then history-matched simultaneously using an ensemble-based conditioning tool to match the available observed field production data within a specified tolerance; with each reservoir ranging in number of wells, number of grid cells and production history. This approach results in a significantly reduced modeling cycle time compared to the traditional approach, regardless of the inherent complexity of the reservoir, while giving better history-matched models that are honoring the geology and correlations in input data. These models are created with only enough detail level as per the modeling objectives, leaving more time to extract insights from the ensemble of models. Uncertainties in data, from various domains, are not isolated there, but rather propagated throughout, as these might have an important role in another domain, or in the total response uncertainty. Similarly, the approach encourages a collaborative effort in reservoir modeling and fosters trust between geo-scientists and engineers, ascertaining that models remain consistent across all subsurface domains. It allows for the flexibility to incorporate modeling practices fit for individual reservoirs. Moreover, analysis of the history-matched ensemble shows added insights to the reservoirs such as the location and possible extent of features like high permeability streaks and baffles that are not explicitly modeled in the process initially. Forecast strategies further run on these ensembles of equiprobable models, capture realistic uncertainties in dynamic responses which can help make informed reservoir management decisions. The integrated ensemble-based modeling approach is successfully applied on three different reservoir cases, with different levels of complexity. The fast-tracked process from model building to decision making enabled rapid insights for all domains involved.


2021 ◽  
Author(s):  
Kanat Aktassov ◽  
Dauletbek Ayaganov ◽  
Kanat Imagambetov ◽  
Ruslan Alissov ◽  
Said Muratbekov ◽  
...  

Abstract This paper presents a practical methodology of optimizing and building a detailed field surface network system by using the high-resolution reservoir simulator driven custom-made Python scripts to efficiently predict the future performance of the vast oil and gas-condensate carbonate field. All existing surface hydraulic tables are quality checked and lifting issue constraints corrected. Pressure losses at the wellhead chokes incorporated into the high-resolution reservoir simulator in the form of equation by using the custom scripts instead of a table format to calculate gas rate dependent pressure losses more precisely. Consequently, all 400+ surface production system manifolds, pipes and well chokes Horizontal Flow Performance (HFP) tables are updated and coupled to the reservoir simulator through Field Management (FM) controller which in turn generates Inflow Performance Relationship (IPR) tables for the coupled wells and passes them to solve the network. The methodology described in this paper applied for a complex field development planning of the Karachaganak. At present, reservoir management strategy requires constant balancing effort to uniformly spread gas re-injection into the lower Voidage Replacement Ratio areas in the Upper Gas-Condensate part of the reservoir due to reservoir heterogeneity. Additionally, an increase in field and wells gas-oil ratio and water-cut creates bottlenecks in the surface gathering system and requires robust solutions to decongest the surface network. Current simulation tools are not always effective due longer run times and simulation instability due to complex network system. As a solution, project-specific network balancing challenges are resolved by incorporating custom-made scripts into the high-resolution simulator. Faster and flexible integrated model based on hydraulic tables reproduced the historical pressure losses of the surface pipelines at similar resolution and generated accurate prediction profiles in a twice-quicker time than existing reservoir simulator. Overall, this approach helped to generate more stable production profiles by identifying bottlenecks in the surface network and evaluate future projects with more confidence by achieving a significant CAPEX cost savings. The comprehensive guidelines provided in this paper can aid reservoir modeling by setting up flexible integrated models to account for surface network effects. The value of incorporating Python scripts demonstrated to implement non-standard and project specific network balancing solutions leveraging on the flexibility and the openness of the modelling tool.


Author(s):  
Ahmed M. Ali ◽  
Ahmed E. Radwan ◽  
Esam A. Abd El-Gawad ◽  
Abdel-Sattar A. Abdel-Latief

AbstractThe Coniacian–Santonian Matulla Formation is one of the important reservoirs in the July oilfield, Gulf of Suez Basin. However, this formation is characterized by uncertainty due to the complexity of reservoir architecture, various lithologies, lateral facies variations and heterogeneous reservoir quality. These reservoir challenges, in turn, affect the effectiveness of further exploitation of this reservoir along the Gulf of Suez Basin. In this work, we conduct an integrated study using multidisciplinary datasets and techniques to determine the precise structural, petrophysical, and facies characteristics of the Matulla Formation and predict their complex geometry in 3D space. To complete this study, 30 2D seismic sections, five digital well logs, and core samples of 75 ft (ft = 0.3048 m) length were used to build 3D models for the Matulla reservoir. The 3D structural model shows strong lateral variation in thickness of the Matulla Formation with NW–SE, NE–SW and N–S fault directions. According to the 3D facies model, shale beds dominate the Matulla Formation, followed by sandstone, carbonate, and siltstone beds. The petrophysical model demonstrates the Matulla reservoir's ability to store and produce oil; its upper and lower zones have good quality reservoir, whereas its middle zone is a poor quality reservoir. The most promising areas for hydrocarbon accumulation and production via the Matulla reservoir are located in the central, southeast, and southwest sectors of the oilfield. In this approach, we combined multiple datasets and used the most likely parameters calibrated by core measurements to improve the reservoir modeling of the complex Matulla reservoir. In addition, we reduced many of the common uncertainties associated with the static modeling process, which can be applied elsewhere to gain better understanding of a complex reservoir.


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