The role of reservoir modelling in unlocking unconventional (resource) plays

2013 ◽  
Vol 53 (2) ◽  
pp. 440
Author(s):  
Hiwa Sidiq ◽  
Eli Silalahi ◽  
Grant Skinner ◽  
Perdana Noverda Pamurty
Keyword(s):  
Seismic Data ◽  
Fracture Network ◽  
Fracture Density ◽  
Reservoir Modelling ◽  
Technical Developments ◽  
Well Spacing ◽  
Shale Reservoirs ◽  
Unconventional Resource ◽  
Sweet Spots

There has been a recent focus on the insight that reservoir modelling provides into devising the best workflows and its ability to include reservoir attributes that affect recovery factors in shale. This extended abstract examines recent technical developments in reservoir modelling and how such modelling can identify sweet spots in shale reservoirs. An accurate characterisation of a pre-existing fracture network and its structural complexities, however, requires the gathering of a large amount of data. In addition, investigating sweet spots at the presently low gas prices sometimes prevents the acquisition of such data that is essential as an input to drilling strategies, fracture program design, well spacing, and understanding stimulated reservoir volumes (SRV) in shale. The pre-existing fractures may also have a limited impact on recovery rates. The transport along a wellbore is mainly controlled by the drained volume, not only by the fractures around the well. In such cases, the pre-existing fractures and their reactivation during the fracturing stage are not sufficient to determine the amount of gas that can be recovered during production. This volume is effectively not only a function of the fracture density, but also of the propped fractures. The challenge, therefore, becomes the ability to have a good estimation of the size of the SRV and be able to calibrate this volume using relevant data such as micro-seismic data and the recovery from previous fraccing stages. This extended abstract also discusses how reservoir modelling can play a key role in this area.

Unified Assessment of Unconventional Resource Plays – Implications for Global Exploration and Development

2021 ◽  
Author(s):  
Tarun Grover ◽  
Jamie Stuart Andrews ◽  
Irfan Ahmed ◽  
Ibnu Hafidz Arief
Keyword(s):  
Commodity Prices ◽  
Design Parameters ◽  
First Year ◽  
Well Productivity ◽  
Well Spacing ◽  
Cumulative Production ◽  
Unconventional Resource ◽  
Log Normal ◽  
The Impact ◽  
Sweet Spots

Abstract Unconventional resource plays, herein referred to as source rock plays, have been able to significantly increase the supply of hydrocarbons to the world. However, majority of the companies developing these resource plays have struggled to generate consistent positive cash flows, even during periods of stable commodity prices and after successfully reducing the development costs. The fundamental reasons for poor financial performance can be attributed to various reasons, such as; rush to lease acreage and drill wells to hold acreage, delayed mapping of sweet spots, slow acknowledgement of high geological variability, spending significant capital in trial and errors to narrow down optimal combinations of well spacing and stimulation designs. The objective of this paper is to present a systematic integrated multidisciplinary analysis of several unconventional plays worldwide which, if used consistently, can lead to significantly improved economics. We present an analysis of several unconventional plays in the US and Argentina with fluid systems ranging from dry gas to black oil. We utilize the publicly available datasets of well stimulation and production data along with laboratory measured core data to evaluate the sweet spots, the measure of well productivity, and the variability in well productivity. We investigate the design parameters which show the strongest correlation to well productivity. This step allows us to normalize the well productivity in such a way that the underlying well productivity variability due to geology is extracted. We can thus identify the number of wells which should be drilled to establish geology driven productivity variability. Finally, we investigate the impact of well spacing on well productivity. The data indicates that, for any well, first year cumulative production is a robust measure of ultimate well productivity. The injected slurry volume shows the best correlation to the well productivity and "completion normalized" well productivity can be defined as first year cumulative production per barrel of injected slurry volume. However, if well spacing is smaller than the created hydraulic fracture network, the potential gain of well productivity is negated leading to poor economics. Normalized well productivity is log-normally distributed in any play due to log-normal distribution of permeability and the sweet spots will generally be defined by most permeable portions of the play. Normalized well productivity is shown to be independent of areal scale of any play. We show that in every play analyzed, typically 20-50 wells (with successful stimulation and production) are sufficient to extract the log-normal productivity distribution depending on play size and target intervals. We demonstrate that once the log-normal behavior is anticipated, creation of production profiles with p10-p50-p90 values is quite straightforward. The way the data analysis is presented can be easily replicated and utilized by any operator worldwide which can be useful in evaluation of unconventional resource play opportunities.

Optimising CSG development: quantitative estimation of lithological and geomechanical reservoir quality parameters from seismic data

2012 ◽  
Vol 52 (2) ◽  
pp. 675
Author(s):  
Eric Bathellier ◽  
Jon Downton ◽  
Gabino Castillo
Keyword(s):  
Seismic Data ◽  
Seismic Inversion ◽  
Quality Parameters ◽  
Azimuthal Anisotropy ◽  
Reservoir Quality ◽  
Valuable Insight ◽  
Fracture Density ◽  
Successful Recovery ◽  
Sweet Spots

Within the past decade, new developments in seismic azimuthal anisotropy have identified a link between fracture density and orientation observed in well logs and the intensity and orientation of the actual anisotropy. Recent studies have shown a correlation between these measurements that provide quantitative estimations of fracture density from 3D wide-azimuth seismic data in tight-gas sand reservoirs. Recent research shows the significance of advanced seismic processing in the successful recovery of reliable fracture estimations, which directly correlates to borehole observations. These quantitative estimations of fracture density provide valuable insight that helps optimise drilling and completion programs, particularly in tight reservoirs. Extending this analysis to CSG reservoirs needs to consider additional reservoir quality parameters while implementing a similar quantitative approach on the interpretation of seismic data and correlation with borehole logging observations. The characterisation of CSG plays involves the understanding of the reservoir matrix properties as well as the in-situ stresses and fracturing that will determine optimal production zones. Pre-stack seismic data can assist with identifying the sweet spots—productive areas—in CSG resource plays by detailed reservoir-oriented gather conditioning followed by pre-stack seismic inversion and multi-attribute analysis. This analysis provides rock property estimations such as Poisson's ratio and Young's modulus, among others, which in turn relate to quantitative reservoir properties such as porosity and brittleness. This study shows an integrated workflow based on pre-stack azimuthal seismic data analysis and well log information to identify sweet spots, estimate geo-mechanical properties, and quantify in-situ principal stresses.

The Role of Seismic Data in the Exploration and Development of Carbonate Karst Cave Reservoir

2014 ◽  
Author(s):  
Zhenzhong Cai ◽  
Chunduan Zhao ◽  
Xingliang Deng ◽  
Yanming Tong ◽  
Yangyong Pan ◽  
...  
Keyword(s):  
Seismic Data ◽  
Karst Cave ◽  
Exploration And Development

Machine Translation for EFL

Relay Journal ◽  
2019 ◽  
pp. 228-235
Author(s):  
Paul J. Moore ◽  
Phil Murphy ◽  
Luann Pascucci ◽  
Scott Sustenance
Keyword(s):  
Foreign Language ◽  
Language Learning ◽  
Machine Translation ◽  
English Language ◽  
Foreign Language Learning ◽  
Efl Learners ◽  
Technical Developments ◽  
English Language Institute ◽  
Changing Role

This paper reports on an ongoing study into the affordances of free online machine translation for students learning English as a foreign language (EFL) at the tertiary level in Japan. The researchers are currently collecting data from a questionnaire, task performance, and interviews with 10-15 EFL learners in an English Language Institute in a university in Japan. The paper provides some background on the changing role of translation in language learning theory and pedagogy, before focusing literature related to technical developments in machine translation technology, and its application to foreign language learning. An overview of the research methodology is provided, along with some insights into potential findings. Findings will be presented in subsequent publications.

scholarly journals Prediction of Shale Gas Reservoirs Using Fluid Mobility Attribute Driven by Post-Stack Seismic Data: A Case Study from Southern China

2020 ◽  
Vol 11 (1) ◽  
pp. 219
Author(s):  
Jing Zeng ◽  
Alexey Stovas ◽  
Handong Huang ◽  
Lixia Ren ◽  
Tianlei Tang
Keyword(s):  
Shale Gas ◽  
Seismic Data ◽  
Spectral Decomposition ◽  
Southern China ◽  
Gas Reservoirs ◽  
Seismic Attribute ◽  
Longmaxi Formation ◽  
Shale Gas Reservoirs ◽  
The Sichuan Basin ◽  
Shale Reservoirs

Paleozoic marine shale gas resources in Southern China present broad prospects for exploration and development. However, previous research has mostly focused on the shale in the Sichuan Basin. The research target of this study is expanded to the Lower Silurian Longmaxi shale outside the Sichuan Basin. A prediction scheme of shale gas reservoirs through the frequency-dependent seismic attribute technology is developed to reduce drilling risks of shale gas related to complex geological structure and low exploration level. Extracting frequency-dependent seismic attribute is inseparable from spectral decomposition technology, whereby the matching pursuit algorithm is commonly used. However, frequency interference in MP results in an erroneous time-frequency (TF) spectrum and affects the accuracy of seismic attribute. Firstly, a novel spectral decomposition technology is proposed to minimize the effect of frequency interference by integrating the MP and the ensemble empirical mode decomposition (EEMD). Synthetic and real data tests indicate that the proposed spectral decomposition technology provides a TF spectrum with higher accuracy and resolution than traditional MP. Then, a seismic fluid mobility attribute, extracted from the post-stack seismic data through the proposed spectral decomposition technology, is applied to characterize the shale reservoirs. The application result indicates that the seismic fluid mobility attribute can describe the spatial distribution of shale gas reservoirs well without well control. Based on the seismic fluid mobility attribute section, we have learned that the shale gas enrich areas are located near the bottom of the Longmaxi Formation. The inverted velocity data are also introduced to further verify the reliability of seismic fluid mobility. Finally, the thickness map of gas-bearing shale reservoirs in the Longmaxi Formation is obtained by combining the seismic fluid mobility attribute with the inverted velocity data, and two favorable exploration areas are suggested by analyzing the thickness, structure, and burial depth. The present work can not only be used to evaluate shale gas resources in the early stage of exploration, but also help to design the landing point and trajectory of directional drilling in the development stage.

scholarly journals Numerical modeling of complex hydraulic fracture networks based on the discontinuous deformation analysis (DDA) method

2021 ◽  
pp. 014459872098153
Author(s):  
Yanzhi Hu ◽  
Xiao Li ◽  
Zhaobin Zhang ◽  
Jianming He ◽  
Guanfang Li
Keyword(s):  
Hydraulic Fracturing ◽  
Hydraulic Fracture ◽  
Fracture Network ◽  
Discontinuous Deformation Analysis ◽  
Deformation Analysis ◽  
Fracture Networks ◽  
Proposed Model ◽  
Discontinuous Deformation ◽  
Shale Reservoirs ◽  
Dda Method

Hydraulic fracturing is one of the most important technologies for shale gas production. Complex hydraulic fracture networks can be stimulated in shale reservoirs due to the existence of numerous natural fractures. The prediction of the complex fracture network remains a difficult and challenging problem. This paper presents a fully coupled hydromechanical model for complex hydraulic fracture network propagation based on the discontinuous deformation analysis (DDA) method. In the proposed model, the fracture propagation and rock mass deformation are simulated under the framework of DDA, and the fluid flow within fractures is simulated using lubrication theory. In particular, the natural fracture network is considered by using the discrete fracture network (DFN) model. The proposed model is widely verified against several analytical and experimental results. All the numerical results show good agreement. Then, this model is applied to field-scale modeling of hydraulic fracturing in naturally fractured shale reservoirs. The simulation results show that the proposed model can capture the evolution process of complex hydraulic fracture networks. This work offers a feasible numerical tool for investigating hydraulic fracturing processes, which may be useful for optimizing the fracturing design of shale gas reservoirs.

Acquire Ocean Bottom Seismic Data and Time-Lapse Geochemistry Data Simultaneously to Identify Compartmentalization and Map Hydrocarbon Movement

2021 ◽  
Author(s):  
Rick Schrynemeeckers
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Time Lapse ◽  
Field Trials ◽  
Detection Methods ◽  
Ocean Bottom ◽  
Field Development ◽  
Dense Grid ◽  
Hydrocarbon Charge ◽  
Sweet Spots

Abstract Current offshore hydrocarbon detection methods employ vessels to collect cores along transects over structures defined by seismic imaging which are then analyzed by standard geochemical methods. Due to the cost of core collection, the sample density over these structures is often insufficient to map hydrocarbon accumulation boundaries. Traditional offshore geochemical methods cannot define reservoir sweet spots (i.e. areas of enhanced porosity, pressure, or net pay thickness) or measure light oil or gas condensate in the C7 – C15 carbon range. Thus, conventional geochemical methods are limited in their ability to help optimize offshore field development production. The capability to attach ultrasensitive geochemical modules to Ocean Bottom Seismic (OBS) nodes provides a new capability to the industry which allows these modules to be deployed in very dense grid patterns that provide extensive coverage both on structure and off structure. Thus, both high resolution seismic data and high-resolution hydrocarbon data can be captured simultaneously. Field trials were performed in offshore Ghana. The trial was not intended to duplicate normal field operations, but rather provide a pilot study to assess the viability of passive hydrocarbon modules to function properly in real world conditions in deep waters at elevated pressures. Water depth for the pilot survey ranged from 1500 – 1700 meters. Positive thermogenic signatures were detected in the Gabon samples. A baseline (i.e. non-thermogenic) signature was also detected. The results indicated the positive signatures were thermogenic and could easily be differentiated from baseline or non-thermogenic signatures. The ability to deploy geochemical modules with OBS nodes for reoccurring surveys in repetitive locations provides the ability to map the movement of hydrocarbons over time as well as discern depletion affects (i.e. time lapse geochemistry). The combined technologies will also be able to: Identify compartmentalization, maximize production and profitability by mapping reservoir sweet spots (i.e. areas of higher porosity, pressure, & hydrocarbon richness), rank prospects, reduce risk by identifying poor prospectivity areas, accurately map hydrocarbon charge in pre-salt sequences, augment seismic data in highly thrusted and faulted areas.

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