Evaluation of Hydraulic Fracturing Treatment with Microseismic Data Analysis in A Marcellus Shale Horizontal Well

2021 ◽  
Author(s):  
Mohamed El Sgher ◽  
Kashy Aminian ◽  
Samuel Ameri
Keyword(s):  
Reservoir Simulation ◽  
Hydraulic Fracture ◽  
Horizontal Well ◽  
Marcellus Shale ◽  
Production Performance ◽  
Well Logs ◽  
Well Log ◽  
Fracture Properties ◽  
The Core ◽  
Reservoir Simulation Model

Abstract The objective of this study was to perform an integrated analysis to gain insight for optimizing fracturing treatment and gas recovery from Marcellus shale. The analysis involved all the available data from a Marcellus Shale horizontal well which included vertical and lateral well logs, hydraulic fracture treatment design, microseismic, production logging, and production data. A commercial fracturing software was utilized to predict the hydraulic fracture properties based on the available vertical and lateral well logs data, diagnostic fracture injection test (DFIT), fracture stimulation treatment data, and microseismic recordings during the fracturing treatment. The predicted hydraulic fracture properties were then used in a reservoir simulation model developed based on the Marcellus Shale properties to predict the production performance. In this study, the rock mechanical properties were estimated from the well log data. The minimum horizontal stress, instantaneous shut-in pressure (ISIP), process zone stress (PZS), and leak-off mechanism were determined from DFIT analysis. The stress conditions were then adjusted based on the results of microseismic interpretations. Subsequently, the results of the analyses were used in the fracturing software to predict the hydraulic fracture properties. Marcellus Shale properties and the predicted hydraulic fracture properties were used to develop a reservoir simulation model. Porosity, permeability, and the adsorption characteristics were estimated from the core plugs measurements and the well log data. The image logs were utilized to estimate the distribution of natural fractures (fissures). The relation between the formation permeability and the fracture conductivity and the net stress (geomechanical factors) were obtained from the core plugs measurements and published data. The predicted production performance was then compared against production history. The analysis of core data, image logs, and DFIT confirmed the presence of natural fractures in the reservoir. The formation properties and in-situ stress conditions were found to influence the hydraulic fracturing geometry. The hydraulic fracture properties are also impacted by stress shadowing and the net stress changes. The production logging tool results could not be directly related to the hydraulic fracture properties or natural fracture distribution. The inclusion of the stress shadowing, microseismic interpretations, and geomechanical factors provided a close agreement between the predicted production performance and the actual production performance of the well under study.

Impact of the Cluster Spacing on Hydraulic Fracture Conductivity and Productivity of a Marcellus Shale Horizontal Well

2021 ◽  
Author(s):  
Mohamed El Sgher ◽  
Kashy Aminian ◽  
Ameri Samuel
Keyword(s):  
Hydraulic Fracture ◽  
Marcellus Shale ◽  
Technical Information ◽  
Gas Production ◽  
Production Performance ◽  
Valuable Insight ◽  
Fracture Conductivity ◽  
Fracture Properties ◽  
Gas Recovery ◽  
The Impact

Abstract The objective of this study was to investigate the impact of the hydraulic fracturing treatment design, including cluster spacing and fracturing fluid volume on the hydraulic fracture properties and consequently, the productivity of a horizontal Marcellus Shale well with multi-stage fractures. The availability of a significant amount of advanced technical information from the Marcellus Shale Energy and Environment Laboratory (MSEEL) provided an opportunity to perform an integrated analysis to gain valuable insight into optimizing fracturing treatment and the gas recovery from Marcellus shale. The available technical information from a horizontal well at MSEEL includes well logs, image logs (both vertical and lateral), diagnostic fracture injection test (DFIT), fracturing treatment data, microseismic recording during the fracturing treatment, production logging data, and production data. The analysis of core data, image logs, and DFIT provided the necessary data for accurate prediction of the hydraulic fracture properties and confirmed the presence and distribution of natural fractures (fissures) in the formation. Furthermore, the results of the microseismic interpretation were utilized to adjust the stress conditions in the adjacent layers. The predicted hydraulic fracture properties were then imported into a reservoir simulation model, developed based on the Marcellus Shale properties, to predict the production performance of the well. Marcellus Shale properties, including porosity, permeability, adsorption characteristics, were obtained from the measurements on the core plugs and the well log data. The Quanta Geo borehole image log from the lateral section of the well was utilized to estimate the fissure distribution s in the shale. The measured and published data were utilized to develop the geomechnical factors to account for the hydraulic fracture conductivity and the formation (matrix and fissure) permeability impairments caused by the reservoir pressure depletion during the production. Stress shadowing and the geomechanical factors were found to play major roles in production performance. Their inclusion in the reservoir model provided a close agreement with the actual production performance of the well. The impact of stress shadowing is significant for Marcellus shale because of the low in-situ stress contrast between the pay zone and the adjacent zones. Stress shadowing appears to have a significant impact on hydraulic fracture properties and as result on the production during the early stages. The geomechanical factors, caused by the net stress changes have a more significant impact on the production during later stages. The cumulative gas production was found to increase as the cluster spacing was decreased (larger number of clusters). At the same time, the stress shadowing caused by the closer cluster spacing resulted in a lower fracture conductivity which in turn diminished the increase in gas production. However, the total fracture volume has more of an impact than the fracture conductivity on gas recovery. The analysis provided valuable insight for optimizing the cluster spacing and the gas recovery from Marcellus shale.

Lithofacies classification in the Marcellus Shale by applying a statistical clustering algorithm to petrophysical and elastic well logs

2016 ◽  
Vol 4 (2) ◽  
pp. SE31-SE49 ◽  
Author(s):  
Kristen Schlanser ◽  
Dario Grana ◽  
Erin Campbell-Stone
Keyword(s):  
Clustering Algorithm ◽  
Marcellus Shale ◽  
Organic Content ◽  
Recognition Algorithm ◽  
Well Logs ◽  
Well Log ◽  
The Core ◽  
Petrophysical Logs ◽  
Marcellus Formation ◽  
Facies Models

Interpreting shale lithofacies is an important step in identifying productive zones in the Marcellus Shale gas play; the target reservoir can be less than 3 m (10 ft) thick with overlying shales that appear similar on certain petrophysical well logs and in the core. However, these nonreservoir-quality shales contain widely varying organic and mechanical properties. To distinguish between reservoir- and nonreservoir-quality shale facies, this classification method applies a pattern-recognition algorithm, expectation maximization, to a set of commonly available petrophysical and elastic well logs to create 1D shale facies models along the wellbore. The statistical algorithm classifies the petrophysical and elastic well-log data into defined facies using the theory that each well log contains a distribution of Gaussian curves for each facies. The method is applied to 12 wells across Pennsylvania and northern West Virginia, and it is able to discriminate between shale facies based on organic content and brittleness, characteristics which are not always evident in core. To verify the geologic accuracy of the facies models, the results are compared with the core data, well logs, mudlogs, and regional stratigraphic studies when available. In addition, we were able to designate a lithofacies-defined top to the Marcellus Formation in parts of the Appalachian Basin where the gradational contact with the overlying Mahantango Formation is poorly defined on petrophysical logs.

scholarly journals Depositional facies model and reservoir characterization of USANI field 1, Niger delta basin, Nigeria

2017 ◽  
Vol 5 (2) ◽  
pp. 57 ◽  
Author(s):  
Godwin Aigbadon ◽  
A.U Okoro ◽  
Chuku Una ◽  
Ocheli Azuka
Keyword(s):  
Tidal Flat ◽  
Water Saturation ◽  
Well Logs ◽  
Physical Analysis ◽  
Well Log ◽  
Delta Front ◽  
Depositional Facies ◽  
Facies Model ◽  
Core Data ◽  
The Core

The 3-D depositional environment was built using seismic data. The depositional facies was used to locate channels with highly theif zones and distribution of various sedimentary facies. The integration core data and the gamma ray log trend from the wells within the studied interval with right boxcar/right bow-shape indicate muddy tidal flat to mixed tidal flat environments. The bell–shaped from the well logs with the core data indicate delta front with mouth bar, the blocky box- car trend from the well logs with the core data indicate tidal point bar with tidal channel fill. The integration of seismic to well log tie display a good tie in the wells across the field. The attribute map from velocity analysis revealed the presence of hydrocarbons in the identified sands (A, B, C, D1, D2, D4, D5). The major faults F1, F2, F3 and F4 with good sealing capacity are responsible for hydrocarbon accumulation in the field. Detailed petro physical analysis of well log data showed that the studied interval are characterized by sand-shale inter-beds. Eight reservoirs were mapped at depth intervals of 2886m to 3533m with their thicknesses ranging from 12m to 407m. Also the Analysis of the petrophysical results showed that porosity of the reservoirs range from 14% to 28 %; permeability range from 245.70 md to 454.7md; water saturation values from 21.65% to 54.50% and hydrocarbon saturation values from 45.50% to 78.50 %. The by-passed hydrocarbons were identified and estimated in low resistivity pay sands D1, D2 at depth of 2884m – 2940m, sand D5 at depth of 3114m – 3126m respectively. The model serve as a basis for establishing facies model in the field.

Assessment of Water Saturation Using Dielectric Permittivity Measurements in Formations with Complex Pore Structure: Application to the Core- and Log- Scale Domains

2021 ◽  
Author(s):  
Zulkuf Azizoglu ◽  
Zoya Heidari ◽  
Leonardo Goncalves ◽  
Lucas Abreu Blanes De Oliveira ◽  
Moacyr Silva Do Nascimento Neto
Keyword(s):  
Dielectric Permittivity ◽  
Pore Structure ◽  
Water Saturation ◽  
Rock Type ◽  
Dielectric Dispersion ◽  
Well Logs ◽  
Well Log ◽  
Dielectric Measurements ◽  
The Core ◽  
Permittivity Measurements

Abstract Broadband dielectric dispersion measurements are attractive options for assessment of water-filled pore volume, especially when quantifying salt concentration is challenging. However, conventional models for interpretation of dielectric measurements such as Complex Refractive Index Model (CRIM) and Maxwell Garnett (MG) model require oversimplifying assumptions about pore structure and distribution of constituting fluids/minerals. Therefore, dielectric-based estimates of water saturation are often not reliable in the presence of complex pore structure, rock composition, and rock fabric (i.e., spatial distribution of solid/fluid components). The objectives of this paper are (a) to propose a simple workflow for interpretation of dielectric permittivity measurements in log-scale domain, which takes the impacts of complex pore geometry and distribution of minerals into account, (b) to experimentally verify the reliability of the introduced workflow in the core-scale domain, and (c) to apply the introduced workflow for well-log-based assessment of water saturation. The dielectric permittivity model includes tortuosity-dependent parameters to honor the complexity of the pore structure and rock fabric for interpretation of broadband dielectric dispersion measurements. We estimate tortuosity-dependent parameters for each rock type from dielectric permittivity measurements conducted on core samples. To verify the reliability of dielectric-based water saturation model, we conduct experimental measurements on core plugs taken from a carbonate formation with complex pore structures. We also introduce a workflow for applying the introduced model to dielectric dispersion well logs for depth-by-depth assessment of water saturation. The tortuosity-dependent parameters in log-scale domain can be estimated either via experimental core-scale calibration, well logs in fully water-saturated zones, or pore-scale evaluation in each rock type. The first approach is adopted in this paper. We successfully applied the introduced model on core samples and well logs from a pre-salt formation in Santos Basin. In the core-scale domain, the estimated water saturation using the introduced model resulted in an average relative error of less than 11% (compared to gravimetric measurements). The introduced workflow improved water saturation estimates by 91% compared to CRIM. Results confirmed the reliability of the new dielectric model. In application to well logs, we observed significant improvements in water saturation estimates compared to cases where a conventional effective medium model (i.e., CRIM) was used. The documented results from both core-scale and well-log-scale applications of the introduced method emphasize on the importance of honoring pore structure in the interpretation of dielectric measurements.

Applying a Reservoir Simulation Model to Drill a Horizontal Well in a Post-Steamflood Reservoir, Wilmington Field, California

2005 ◽  
Author(s):  
Philip Scott Hara ◽  
Julius J. Mondragon ◽  
Hung Henry Sun ◽  
Zhengming Yang ◽  
Iraj Ershaghi
Keyword(s):  
Simulation Model ◽  
Reservoir Simulation ◽  
Horizontal Well ◽  
Reservoir Simulation Model

scholarly journals Case study of gas drainage well location optimization in abandoned coal mine based on reservoir simulation model

2021 ◽  
pp. 014459872110189
Author(s):  
Guiqiang Zheng ◽  
Jiaye Han ◽  
Fengyun Sang ◽  
Tianxin Gao ◽  
Dong Chen ◽  
...  
Keyword(s):  
Simulation Model ◽  
Coal Mine ◽  
Reservoir Simulation ◽  
Gas Production ◽  
Production Performance ◽  
Location Optimization ◽  
Well Location ◽  
Simulation Results ◽  
Reservoir Simulation Model ◽  
Abandoned Coal Mine

The development of abandoned coal mine gas has multiple advantages in terms of safety, economy, environment, and society. Due to previous excavations, the gas distribution is heterogeneous, thereby hindering well location optimization. In this study, considering the Shenbei abandoned coal mine as an example, the authors developed a workflow for well location optimization through simulation. The workflow includes: (1) the setup of an initial reservoir simulation model with the preliminary well location designed by experience; (2) the optimization of the well location based on the flowline distribution, and it is preferred that the well connect a large number of flowlines; (3) the simulation based on the optimized well location, and (4) repetition of the steps until the optimized well locations are determined. Moreover, the role of fracturing is also examined through simulation scenarios. The simulation results show that the locations of the two originally designed wells (1# and 4#) should be optimized due to the relatively low gas production without fracturing. The two wells are optimized according to the flow streamlines, demonstrating performance improvement. Moreover, the simulation results also show that there is no need to optimize the well 4# location if the fracturing technology is applied. An additional well is suggested based on the flow streamline analysis and gas production performance simulation. The main conclusions drawn from this study are as follows. (1) Five optimized well locations are determined for the Shenbei abandoned coal mine, and they should be located within the “O” ring, a high permeability region nearby the previous excavation zone; (2) Fracturing is an effective method for stimulating gas production; however, the extent of fracturing varies from well to well; (3) The workflow applied in this study is effective for the well location optimization in abandoned coal mines.

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