A data processing algorithm proposed for identification of breakout zones in tight formations: A case study in Barnett gas shale

Due to low permeability of tight gas shale, production in commercial quantities requires effective hydraulic fracturing and horizontal drilling technologies. Therefore, understanding rock properties and earth's stresses is an important step toward reservoir evaluation and ultimately development of these kinds of resources. Furthermore, successful production from such a complex formation is heavily dependent on selection of appropriate completion technology which requires having sufficient knowledge of borehole shape or say enlarged zones.Borehole enlargements or specifically breakouts provide valuable information for evaluation of in-situ stresses and verification of geomechanical models. Customarily used methods to identify breakouts, i.e., caliper and image logs, suffer from several limitations. In addition, good quality image logs are not usually available in shaly formations due to requirement of using oil-based mud. This led to the need for developing a new technique to identify borehole enlargement zones using petrophysical logs which are often acquired in majority of the wells.This study proposes a new multi-variable approach to identify borehole enlargement zones in tight gas shale using some petrophysical logs, mud weight and overburden stress data. This approach employs number of data processing techniques including Bayesian classification, wavelet decomposition and data fusion to determine borehole intervals with maximum likelihood of enlargement. This paper explains the methodology and presents its results in four study wells in Barnett gas shale. The study confirms the applicability and the generalization capability of the approach in shaly formations with a significant accuracy

High Drilling Methane Drainage in Fracturing Zones Formed by Water Injection into Boreholes

Methane drainage method should be used before coal mining of many modern collieries because venti lation air methane is in sufficient to keep methane level within regulation values. The technology of high drilling methane drainage (HDMD) has been used for methane drainage although its effect is not very stable due to parameter design. The height of the fracturing zones is determined mostly according to empirical formula, on-site observation and numerical simulation analysis. In this paper, a method was introduced for determining the height of the air f ract uring zones (AFZs) based on its high similarity to the characteristics of Fracturing zones and the relationship between the height of Fracturing zones and the strain of overl ying rock strata. The application of water injection in both Shuangdingshan and Dongrong collieries found that the theoretically calculated the height of the Fracturing zones was approximately equal to the measured one in field tests within a permissible error of less than 5%, proving that the method is feasible. Based on the designed drainage parameters, the u tilization of HDMD technology in the collieries mentioned above found that the methane concentrations in both tail gate and upper corner were controlled in the ranges of 0.17% to 0.32% and 0.26% to 0.84%, respectively. These results showed that the water injection verified HDMD in Fracturing zones could effectively solve the problem of metha ne overrun and also verified the accuracy and reliability of its related theory.Przed rozpoczęciem wydobycia węgla w wielu obecnie eksploatowanych kopalniach wskazane jest odprowadzenie metanu, ponieważ stosowane systemy wentylacji powietrza są niewystarczające aby utrzymać stężenia metanu na dopuszczalnym poziomie. Technologia odprowadzania metanu metodą odwiertów prowadzonych na różnej wysokości (HDMD) wykorzystywana jest w tym celu, choć jej wyniki nie zawsze są stabilne ze względu na konieczność doboru parametrów obliczeniowych. Wysokość strefy szczelinowania określa się zazwyczaj empirycznie, na podstawie obserwacji w terenie oraz drogą symulacji numerycznych. W pracy tej określono wysokość strefy wykonania szczelin w oparciu o podobieństwo do charakterystyk Strefy szczelinowania oraz o analizę odkształceń warstw nadkładu. Zastosowano wtrysk wody w kopalniach Shuangdingshan i Dongrong i stwierdzono, że teoretycznie obliczona wysokość stref szczelinowania była w przybliżeniu równa wysokości zmierzonej empirycznie w trakcie badań terenowych, z dopuszczalnym poziomem błędu poniżej 5%, co wskazuje na możliwość zastosowania metody. W oparciu o parametry obliczeniowe stwierdzono, że zastosowanie metody HDMD w wyżej wymienionych kopalniach spowodowało, że stężenia metanu rejestrowane w chodniku nadścianowym i górnych narożach utrzymywały się odpowiednio na poziomie 0.17%, 0.32% i 0.26%-0.84%. Wyniki te pokazują, że wtrysk wody w strefie szczelin pomaga skutecznie rozwiązać problem obecności zbyt wysokich ilości metanu, ponadto potwierdza dokładność i wiarygodność teorii na której metoda jest oparta

Integration of Adaptive Neuro-Fuzzy Inference System, Neural Networks and Geostatistical Methods for Fracture Density Modeling

Image logs provide useful information for fracture study in naturally fractured reservoir. Fracture dip, azimuth, aperture and fracture density can be obtained from image logs and have great importance in naturally fractured reservoir characterization. Imaging all fractured parts of hydrocarbon reservoirs and interpreting the results is expensive and time consuming. In this study, an improved method to make a quantitative correlation between fracture densities obtained from image logs and conventional well log data by integration of different artificial intelligence systems was proposed. The proposed method combines the results of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Neural Networks (NN) algorithms for overall estimation of fracture density from conventional well log data. A simple averaging method was used to obtain a better result by combining results of ANFIS and NN. The algorithm applied on other wells of the field to obtain fracture density. In order to model the fracture density in the reservoir, we used variography and sequential simulation algorithms like Sequential Indicator Simulation (SIS) and Truncated Gaussian Simulation (TGS). The overall algorithm applied to Asmari reservoir one of the SW Iranian oil fields. Histogram analysis applied to control the quality of the obtained models. Results of this study show that for higher number of fracture facies the TGS algorithm works better than SIS but in small number of fracture facies both algorithms provide approximately same results

Fractures network analysis and interpretation in carbonate rocks using a multi-criteria statistical approach. Case study of Jebal Chamsi and Jebal Belkhir, South-western part of Tunisia

International audienceThe quantitative analysis of fractures in carbonate rocks across termination folds is important for the understanding of the fractures network distribution and arrangement. In this study, we performed a quantitative analysis and interpretation of fracture network to identify the fracture networks type. For this reason, we used a multi-criteria statistical analysis. The distribution of directional families in all measured stations and their elemental distribution are firstly examined. Then we performed the analysis of directional criteria for each of the two and three neighbouring stations. Finally, the elemental analyses of fracture families crossing others were carried out. This methodology was applied to the folds of Jebal Chamsi and Jebal Belkhir areas located in south western Tunisia characterized by simple folds of carbonate geological formations. The application of the global and the elemental statistical analysis criteria of directional families show a random arrangement of fractures. However, elemental analysis of two and three neighbouring stations for families crossing one another shows a pseudo-organization of fracture arrangements