This paper discusses the use of a novel data-driven method for automated facies classification and characterization of carbonate reservoirs. The approach makes an extensive use of wireline and while drilling electrical borehole image logs and provides a direct and fast recognition of the main geological features at multi-scale level, together with secondary porosity estimation. This embodies an unbiased and valuable key-driver for rock typing, dynamic behavior understanding and reservoir modeling purposes in these puzzling scenarios.
The implemented methodology takes advantage of a non-conventional approach to the analysis and interpretation of image logs, based upon image processing and automatic classification techniques applied in a structural and petrophysical framework. In particular, the Multi-Resolution Graph-based Clustering (MRGC) algorithm that is able to automatically shed light on the significant patterns hidden in a given image log dataset. This allows the system to perform an objective multi-well analysis within a time-efficient template. A further characterization of the facies can be established by means of the Watershed Transform (WT) approach, based on digital image segmentation processes and which is mainly aimed at quantitative porosity partition (primary and secondary).
The added value from this data-driven image log analysis is demonstrated through selected case studies coming from vertical and sub-horizontal wells in carbonate reservoirs characterized by high heterogeneity. First, the MRGC has been carried out in order to obtain an alternative log-facies classification with an inherent textural meaning. Next, the WT-based algorithm provided a robust quantification of the secondary porosity contribution to total porosity, in terms of connected vugs, isolated vugs, fractures and matrix contribution rates. Finally, image log-facies classification and quantitative porosity partition have been integrated with production logs and pressure transient analyses to reconcile the obtained carbonate rock types with the effective fluid flows and the associated dynamic behavior at well scale.
The presented novel methodology is deemed able to perform an automatic, objective and advanced interpretation of field-scale image log datasets, avoiding time-consuming conventional processes and inefficient standard analyses when the number of wells to be handled is large and/or in harsh circumstances. Moreover, secondary porosity can be proficiently identified, evaluated and also characterized from the dynamic standpoint, hence representing a valuable information for any 3D reservoir models.
Estimates derived under these definitions rely on the integrity, skill, and judgement of the evaluator and are affected by the geological complexity, stage of exploration or development, degree of depletion of the reservoirs, and amount of available data. Use of the definitions should sharpen the distinction between various classifications and provide more consistent resources reporting. The resource classification system is summarized in Figure 1 and the relevant definitions are given below. Elsewhere, resources have been defined as including all quantities of petroleum which are estimated to be initially-in-place; however, some users consider only the estimated recoverable portion to constitute a resource. In these definitions, the quantities estimated to be initially-in-place are defined as Total Petroleum-initially-in-place, Discovered Petroleum-initially-in-place and Undiscovered Petroleum-initiallyin- place, and the recoverable portions are defined separately as Reserves, Contingent Resources and Prospective Resources.
In this paper, we present for the first time, a classification system for naturally-occurring gas hydrate deposits existing in the permafrost and marine environment. This classification is relatively simple but highlights the salient features of a gas hydrate deposit which are important for their exploration and production such as location, porosity system, gas origin and migration path. We then show how this classification can be used to describe eight well-studied gas hydrate deposits in permafrost and marine environment. Potential implications of this classification are also discussed.
Choudhary, Pradeep (Kuwait Oil Company) | Freeman, Mike (Kuwait Oil Company) | Al-Boloushi, Ahmed (Kuwait Oil Company) | Benham, Philip (Shell Kuwait Exploration and Production B.V) | Sakia, Pabitra (Kuwait Oil Company) | Tyagi, Aditya (Kuwait Oil Company) | Ahmad, Khalid (Kuwait Oil Company) | Jha, Madan (Kuwait Oil Company) | Zhang, Ian (Shell Kuwait Exploration and Production B.V) | Warlich, Georg (Shell Kuwait Exploration and Production B.V) | Al-Rabah, Abdullah (Kuwait Oil Company)
The shallow depth unconventional reservoir in Northern Kuwait is essentially a monoclinal structure. Sediments have undergone significant shallow depth diagenesis, which resulted in selective oil/water accumulation, controlled mainly by lithological variations. Thus, the reservoir can be classified as stratigraphic-dominant trap. A correlation approach required addressing these variations, which can also be well understood by non-geologist, and the scheme should be appropriate for selection of perforation intervals.
Reservoir sands are in the form of multi-stacked distributary/fluvial channels. Subsequent to sediment deposition, moderate to intense diagenesis took place. The diagenesis resulted in formation of cemented baffles under low reservoir pressure (250psi) regime. For demarcation of bed boundaries, mapping and modelling purpose the reservoir sand, shale, baffles, gas, water, water above oil, this petrofacies classification method is proposed. The method is well capable of defining the various bed boundaries with fluid/gas content in it with confidence. The method developed after extensive core, core data and log calibration and study. More than one thousand wells correlated.
The classification method is simple, yet robust to characterise reservoir vs. non-reservoir variations and oil/gas vs. water quite effectively. Cementation activities typically noticed on top/bottom of the units but many times in between the reservoir sand also. We are able to correlate cemented layers across the area. The cementation also gives rise to water perched above oil phenomenon due to relatively higher capillary pressure in the zone. Oil is migrated post-cementation and occupied reachable pore spaces. Oil also has undergone significant biodegradation because of favourable temperature and restricted nutrient supply. As a result, thin layers of thermal/biodegraded gas also formed locally. The method allows for surface related categorisation representing clean sand, cemented sand, shale, gas/oil/trapped water zones.
This unconventional reservoir is being developed with thermal application. Thickness of baffles, barrier, gas, water zones are critical in selection of perforation interval for steam application. This classification method is part of perforation selection for first phase of development and modelling purpose, and it was applied to hundreds of wells, many of them are undergoing production operations successfully.
Perrier, Sebastien (TOTAL E&P USA, secondee to Chesapeake Energy) | Araman, Alexandre (TOTAL E&P USA, secondee to Chesapeake Energy) | Shrestha, Ashis (Chesapeake Energy) | Shawuti, Zulibukaer (Chesapeake Energy)
Rate Transient Analysis (RTA) is a classic characterization method for unconventional wells. In this paper, we propose to leverage RTA rate-pressure transforms by analyzing the data at play scale, using pattern and anomaly classification algorithms, to derive new quantitative and qualitative indicators for more than 600 wells operated by Chesapeake Energy on Utica gas shale play.
Estimating reserves is one of the most important steps in the oil industry by which the hydrocarbon volumes in a field are evaluated economically. The principal objective of this work was to present an analysis of the main differences in the estimation of OOIP for assessing the reserves in the block II of Urdaneta-01 heavy oil reservoir, using both the rock typing approach of this study and the traditional open hole log analysis with standard specifications of the area, as well as identifying the impact into the outcomes of the following parameters, net pay thickness, porosity and water saturation through a full 3D Geomodel processing and calculations.
The complete petrophysical model for the rock type approach follows all mayor steps in computing rock type percentages, modified lorenz plot, stratigraphic modified lorenz plot, flow unit and rock properties per each well from laboratory measurements of key reservoir parameters such as porosity and permeability, while the standard open hole log analysis is set with official parameters values from the study area. For both methods a 3D-Grid model of block II is created with specific settings in order to see the spatial distribution of rock properties and oil volume reckoning.
The final result shows a contrast between the two models generated, that is, the total hydrocarbon volume is higher in the case of rock typing evaluation, there is a difference between the two models of 302 MM SBT. In addition, in terms of rock properties, the storage capacity and water saturation are the most sensitive parameters at the moment of calculations, at least 4 % difference between average porosity from log-based traditional techniques and the rock classification approach. A reliable OOIP was obtained when water saturation distribution can be controlled.
Ettehadi, Reza (Baker Hughes, a GE Company) | May, Roland (Baker Hughes, a GE Company) | Dahl, Thomas (Baker Hughes, a GE Company) | Clapper, Dennis (Baker Hughes, a GE Company) | Swartwout, Rosa (Baker Hughes, a GE Company)
The accurate characterization of drilling fluid rheological properties at the in-situ downhole temperature and pressure is essential for designing the hydraulic program as well as for managing potential challenges during the drilling operation. A rheometer capable of operating at high temperature and high pressure (HTHP) is the common experimental method used to measure drilling fluid rheological properties at in-situ conditions. This method is costly and time consuming and requires skilled fluids laboratory personnel to carry out the tests. At the rigsite these devices are usually not available.
This paper/study presents an analytics based method to estimate drilling fluid rheological properties at in-situ downhole temperature and pressure and provide the required inputs for hydraulic modeling during well planning, for real-time monitoring and automation. The performance of the developed method is evaluated by utilizing data obtained from both, Mud Check tests and HTHP Viscosity measurements of synthetic and oil based drilling fluid samples.
Drilling fluid samples were collected from the rigs in operations around the world. An algorithm is developed to retrieve data out of unstructured field service laboratory databases and to uncover hidden patterns by utilizing the text pattern matching, text analytics, table-based approach, data visualization and classification techniques. Several computational intelligence techniques and statistical methods are applied to interpret the data by correlation of variables measured in the Mud Check tests and HTHP rheometer data. Of the available data 70 percent have been randomly extracted to train the data driven-model to predict drilling fluids rheological behavior at the in-situ downhole temperature and pressure.
The model is further tested with the remaining 30 percent of the available data to confirm that the model can not only fit the data used for training but also characterize the drilling fluid rheology at the in-situ downhole temperature and pressure with the required accuracy. This study indicates that in addition to temperature and pressure, several parameters including density, salt concentration, low and high gravity solid volume percentage, oil-water ratio, and oil phase volume percentage should be considered to accurately predict the rheological properties of drilling fluids at downhole conditions. Since the method presented here depends on several variables measured in the Mud Check tests, it can effectively be employed independent of location or formation.
The developed method can be utilized at the rigsite by field personnel to estimate downhole rheological properties of drilling fluids with a small error margin, without using expensive test equipment and time consuming procedures.
The ADGAS plant facilities include three LNG trains (Trains-1 & 2 commissioned in 1977 and Train-3 commissioned in 1994), Offshore Associated Gas (OAG) and Integrated Gas Development (IGD) facilities along with utilities and other associated facilities such as storage tankage, jetties for export of the products, etc. The gas feedstock comes from various offshore oil and gas fields surrounding Das Island. The feed gas, delivered to the plant at different pressure levels is compressed through different stages and purified before liquefaction. The feed gas contains impurities like CO2 (Carbon Di Oxide) and H2S (Hydrogen Sulphide), which are removed by gas sweetening process. H2S removed by the sweetening process is converted into liquid Sulphur in the Sulphur Recovery Units. After sweetening, the hydrocarbon gas mixture is cooled in stages followed by fractionation and liquefaction to produce different hydrocarbon products ranging from LNG (a mixture of methane and ethane) to Paraffinic Naphtha.
ADGAS commissioned the OAG and IGD facilities in 2010 and 2013 respectively, enabling gas export from Das Island to onshore Habshan facilities through a subsea pipeline. The primary objective of OAG facility is to process additional quantities of LP Gases that has become available at Das Island from ADMA-OPCO, following increase in oil production. The process involves compression of LP Gases, Dehydrate and dispatch 211 mmscfd of Gas & Condensate through marine pipeline to GASCO facility at Habshan. OAG (two processing trains) processes about 200mmscfd gas whereas The IGD was commissioned in the year 2013. This comprises of three Trains capable of delivering 900 mmscfd of dry compressed HP Gas at 155 Bara through marine pipeline to GASCO facility at Habshan.
Existing rock mass classification systems, such as rock mass rating (RMR) are often used in many empirical design practices in rock engineering contrasting with their original application, i.e. estimation of TBM performance in various ground conditions. However, the use of RMR or similar classification systems in providing an accurate estimation of TBM penetration rate has had limited success due to the nature of the weights assigned to the input parameters. The results of many investigations on this topic have shown a weak correlation between TBM penetration rate and RMR. This limitation can be addressed by performing regression tree analysis which revises the weights assigned to input parameters to better represent influence of rock mass properties on TBM performance. This paper offers an overview of the impact of rock mass classification on TBM performance and introduces a new model based on regression tree using the input parameters of RMR system to predict the performance of hard rock TBMs. The results of the preliminary analysis show that the use of the proposed model can improve the accuracy of TBM performance estimates in various rock masses. This is based on the comparison between the estimated and actual rate of penetration of TBMs in two tunneling projects in igneous and sedimentary rocks. This study shows the potential of regression tree approach to offer more suitable rating of input parameters for this application, if sufficiently diverse database of machine performance is used in the analysis.
Hard rock tunnel boring has become the preferred method of tunneling for tunnels of various sizes with length over 1.5-2 km due to achievement of higher speed and lower cost. Estimating the performance of TBM is a vital part of tunnel design and selection of the most appropriate machine type and specification. During the past three decades, numerous TBM performance prediction models have been proposed which can be divided into two distinguished approaches, namely theoretical and empirical methods . Currently three different models including Colorado School of Mines or CSM  and Norwegian University of Science and Technology or NTNU , and field penetration index (FPI)  models are the most recognized TBM performance prediction and prognosis models in use around the world.
The CSM model allows calculation of the cutting forces on disc cutters to reach certain penetration into the rock surface with given physical and mechanical properties. This method offers the advantages of being able to consider the detail geometry of the cutterhead (disc diameter, tip width, and spacing). However, the original CSM model does not take the natural discontinues of the rock mass into consideration. Obviously, rock mass characteristics play a great role in determining the cutting speed of the TBM. To address this shortcoming, Yagiz  and Ramezanzadeh  have offered modifications to the original CSM model to incorporate rock mass properties as input parameters into the model. On the other hand, Bruland  updated and improved the NTNU models based on field data originally collected from Norwegian tunnels, and later expanded to other tunneling projects around the world. The NTNU model uses specialized rock drillability/boreability indices such as Drilling Rate Index (DRI) and rock mass properties including joint spacing and orientation to estimate TBM performance. The indices used by NTNU model originated from the drilling experiments and the related tests are only available in specialized rock mechanics laboratories and not very common.