scholarly journals Study on discriminant method of rock type for porous carbonate reservoirs based on Bayesian theory

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xinxin Fang ◽  
Hong Feng

AbstractRock typing is an extremely critical step in the estimation of carbonate reservoir quality and reserves in the Middle East. In order to recognize the rock types of carbonate reservoirs in the Mishrif Formation better, classify the reservoirs accurately, and establish the permeability model in line with the study area precisely, it is necessary to study the recognition method conforming to the actual situation of the study area. The practice shows that the current recognition methods based on capillary pressure curve, flow unit and NMR logging data can effectively distinguish rock types, but a large number of accurate experimental data are required, which can only be applied in a few cored well, however, cannot be applied in the whole oil field. In this study, based on core, thin section, logging data, the sedimentary characteristics of carbonate reservoir, logging response of four rock types as well as porosity and permeability characteristics of Mishrif Formation in W are comprehensively studied. Based on Bayesian stepwise discriminant theory in multivariate statistics, the Bayesian discrimination model based on conventional logging data is established. The examining results showed that, compared with the description of logging and coring, the accuracy of Bayesian discriminant model and cross confirmation rate have achieved more than 80% for the original sample. Reliability verification showed that the matching degree of the rock type recognized in the non-cored well with the core and mud logging was as high as 90%, which matched the depositional environment of the entire region. The study results confirm the validity and generalizability of the Bayesian method to identify and predict rock types, which can be applied to the entire Middle East region to solve the problem of the lack of core data to accurately evaluate the quality of non-cored wells and accurately predict production, meeting the needs of actual reservoir evaluation and production development in the Middle East.

2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Tiankui Guo ◽  
Songjun Tang ◽  
Yanchao Li ◽  
Fujian Zhou ◽  
Bijun Tan ◽  
...  

Abstract The acid-fracturing is applied wildly to simulate the formation in vuggy carbonate reservoirs. But it does not figure out clearly the mechanism of fracture propagation while fracture encountering dissolved cavern, and there are few researches considering the influence of dissolved cavern on fracture propagation. In order to study fracture propagation regularity in vuggy carbonate reservoirs, numerical simulations are carried out by the seepage–stress–damage coupling equation based on the damage mechanics theory and the accuracy of the model is validated by comparison with experimental results. Some factors influencing the fracture propagation such as dissolved cavern, formation parameters, and construction parameters are considered. The simulation results show that there are four fracture propagation forms after the fracture encountering dissolved cavern, namely, block, crossing over directly, crossing over after deflection, and deflection. The entire process of injecting the pressure curve can be divided into five stages: initial initiation zone, encountering dissolved cavern pressure released zone, the dissolved cavern inside builds the pressure zone, re-ruptured zone, and fracture propagation zone. The horizontal principal stress difference of the formation controls the tendency of fracture propagation and the generation of branch fractures. It is easy to generate branch fractures under the condition of low horizontal principal stress. The increase in horizontal principal stress limits the deformation of fracture, making it more convenient for fracture to extend toward the maximum horizontal principal stress. The study results are significant for optimizing fracturing construction plans and improving the probability of connection between fracture and dissolved cavern.


2018 ◽  
Vol 6 (3) ◽  
pp. T555-T567
Author(s):  
Zhuoying Fan ◽  
Jiagen Hou ◽  
Chengyan Lin ◽  
Xinmin Ge

Classification and well-logging evaluation of carbonate reservoir rock is very difficult. On one side, there are many reservoir pore spaces developed in carbonate reservoirs, including large karst caves, dissolved pores, fractures, intergranular dissolved pores, intragranular dissolved pores, and micropores. On the other side, conventional well-logging response characteristics of the various pore systems can be similar, making it difficult to identify the type of pore systems. We have developed a new reservoir rock-type characterization workflow. First, outcrop observations, cores, well logs, and multiscale data were used to clarify the carbonate reservoir types in the Ordovician carbonates of the Tahe Oilfield. Three reservoir rock types were divided based on outcrop, core observation, and thin section analysis. Microscopic and macroscopic characteristics of various rock types and their corresponding well-log responses were evaluated. Second, conventional well-log data were decomposed into multiple band sets of intrinsic mode functions using empirical mode decomposition method. The energy entropy of each log curve was then investigated. Based on the decomposition results, the characteristics of each reservoir type were summarized. Finally, by using the Fisher discriminant, the rock types of the carbonate reservoirs could be identified reliably. Comparing with conventional rock type identification methods based on conventional well-log responses only, the new workflow proposed in this paper can effectively cluster data within each rock types and increase the accuracy of reservoir type-based hydrocarbon production prediction. The workflow was applied to 213 reservoir intervals from 146 wells in the Tahe Oilfield. The results can improve the accuracy of oil-production interval prediction using well logs over conventional methods.


2018 ◽  
Vol 2 (1) ◽  
pp. 8
Author(s):  
Tariq Kakarash ◽  
Qays M. Sadeq

Permeability and porosity are the most difficult parameters to estimate in the oil reservoir because they are varying significantly over the reservoir, especially in the carbonate formation. Porosity and permeability can only be sampled at the well location. However, porosity is easy to estimate directly from well log data, permeability is not. In addition, permeability measurements from core samples are very expensive. Carbonate reservoirs are very difficult to characterize because of their tendency to be tight and heterogeneous due to deposition and diagenetic processes. Therefore, many engineers and geologists try to establish methods to get the best characterization for the carbonate reservoir. In this study, available routine core data from three wells are used to develop permeability model based on hydraulic flow unit method (HFUM) (RQI/FZI) for cretaceous carbonate middle reservoirs of Bai Hassan oil field. The results show that the HFUM is work perfectly to characterize and predict permeability for uncored wells because R2 ≥ 0.9. It is indicating that permeability can be accurately predicted from porosity if rock type is known.


2021 ◽  
pp. 014459872199465
Author(s):  
Yuhui Zhou ◽  
Sheng Lei ◽  
Xuebiao Du ◽  
Shichang Ju ◽  
Wei Li

Carbonate reservoirs are highly heterogeneous. During waterflooding stage, the channeling phenomenon of displacing fluid in high-permeability layers easily leads to early water breakthrough and high water-cut with low recovery rate. To quantitatively characterize the inter-well connectivity parameters (including conductivity and connected volume), we developed an inter-well connectivity model based on the principle of inter-well connectivity and the geological data and development performance of carbonate reservoirs. Thus, the planar water injection allocation factors and water injection utilization rate of different layers can be obtained. In addition, when the proposed model is integrated with automatic history matching method and production optimization algorithm, the real-time oil and water production can be optimized and predicted. Field application demonstrates that adjusting injection parameters based on the model outputs results in a 1.5% increase in annual oil production, which offers significant guidance for the efficient development of similar oil reservoirs. In this study, the connectivity method was applied to multi-layer real reservoirs for the first time, and the injection and production volume of injection-production wells were repeatedly updated based on multiple iterations of water injection efficiency. The correctness of the method was verified by conceptual calculations and then applied to real reservoirs. So that the oil field can increase production in a short time, and has good application value.


2021 ◽  
Author(s):  
Mohamed Masoud ◽  
W. Scott Meddaugh ◽  
Masoud Eljaroshi ◽  
Khaled Elghanduri

Abstract The Harash Formation was previously known as the Ruaga A and is considered to be one of the most productive reservoirs in the Zelten field in terms of reservoir quality, areal extent, and hydrocarbon quantity. To date, nearly 70 wells were drilled targeting the Harash reservoir. A few wells initially naturally produced but most had to be stimulated which reflected the field drilling and development plan. The Harash reservoir rock typing identification was essential in understanding the reservoir geology implementation of reservoir development drilling program, the construction of representative reservoir models, hydrocarbons volumetric calculations, and historical pressure-production matching in the flow modelling processes. The objectives of this study are to predict the permeability at un-cored wells and unsampled locations, to classify the reservoir rocks into main rock typing, and to build robust reservoir properties models in which static petrophysical properties and fluid properties are assigned for identified rock type and assessed the existed vertical and lateral heterogeneity within the Palaeocene Harash carbonate reservoir. Initially, an objective-based workflow was developed by generating a training dataset from open hole logs and core samples which were conventionally and specially analyzed of six wells. The developed dataset was used to predict permeability at cored wells through a K-mod model that applies Neural Network Analysis (NNA) and Declustring (DC) algorithms to generate representative permeability and electro-facies. Equal statistical weights were given to log responses without analytical supervision taking into account the significant log response variations. The core data was grouped on petrophysical basis to compute pore throat size aiming at deriving and enlarging the interpretation process from the core to log domain using Indexation and Probabilities of Self-Organized Maps (IPSOM) classification model to develop a reliable representation of rock type classification at the well scale. Permeability and rock typing derived from the open-hole logs and core samples analysis are the main K-mod and IPSOM classification model outputs. The results were propagated to more than 70 un-cored wells. Rock typing techniques were also conducted to classify the Harash reservoir rocks in a consistent manner. Depositional rock typing using a stratigraphic modified Lorenz plot and electro-facies suggest three different rock types that are probably linked to three flow zones. The defined rock types are dominated by specifc reservoir parameters. Electro-facies enables subdivision of the formation into petrophysical groups in which properties were assigned to and were characterized by dynamic behavior and the rock-fluid interaction. Capillary pressure and relative permeability data proved the complexity in rock capillarity. Subsequently, Swc is really rock typing dependent. The use of a consistent representative petrophysical rock type classification led to a significant improvement of geological and flow models.


2008 ◽  
Author(s):  
Emmanuel Gaucher ◽  
Christophe C. Maisons ◽  
Abdullatif Y. Al-Kandari ◽  
Kamal Al-Atroshi and Jassim M. Al-Kanderi

1999 ◽  
Vol 2 (02) ◽  
pp. 149-160 ◽  
Author(s):  
D.K. Davies ◽  
R.K. Vessell ◽  
J.B. Auman

Summary This paper presents a cost effective, quantitative methodology for reservoir characterization that results in improved prediction of permeability, production and injection behavior during primary and enhanced recovery operations. The method is based fundamentally on the identification of rock types (intervals of rock with unique pore geometry). This approach uses image analysis of core material to quantitatively identify various pore geometries. When combined with more traditional petrophysical measurements, such as porosity, permeability and capillary pressure, intervals of rock with various pore geometries (rock types) can be recognized from conventional wireline logs in noncored wells or intervals. This allows for calculation of rock type and improved estimation of permeability and saturation. Based on geological input, the reservoirs can then be divided into flow units (hydrodynamically continuous layers) and grid blocks for simulation. Results are presented of detailed studies in two, distinctly different, complex reservoirs: a low porosity carbonate reservoir and a high porosity sandstone reservoir. When combined with production data, the improved characterization and predictability of performance obtained using this unique technique have provided a means of targeting the highest quality development drilling locations, improving pattern design, rapidly recognizing conformance and formation damage problems, identifying bypassed pay intervals, and improving assessments of present and future value. Introduction This paper presents a technique for improved prediction of permeability and flow unit distribution that can be used in reservoirs of widely differing lithologies and differing porosity characteristics. The technique focuses on the use and integration of pore geometrical data and wireline log data to predict permeability and define hydraulic flow units in complex reservoirs. The two studies presented here include a low porosity, complex carbonate reservoir and a high porosity, heterogeneous sandstone reservoir. These reservoir classes represent end-members in the spectrum of hydrocarbon reservoirs. Additionally, these reservoirs are often difficult to characterize (due to their geological complexity) and frequently contain significant volumes of remaining reserves.1 The two reservoir studies are funded by the U.S. Department of Energy as part of the Class II and Class III Oil Programs for shallow shelf carbonate (SSC) reservoirs and slope/basin clastic (SBC) reservoirs. The technique described in this paper has also been used to characterize a wide range of other carbonate and sandstone reservoirs including tight gas sands (Wilcox, Vicksburg, and Cotton Valley Formations, Texas), moderate porosity sandstones (Middle Magdalena Valley, Colombia and San Jorge Basin, Argentina), and high porosity reservoirs (Offshore Gulf Coast and Middle East). The techniques used for reservoir description in this paper meet three basic requirements that are important in mature, heterogeneous fields.The reservoir descriptions are log-based. Flow units are identified using wireline logs because few wells have cores. Integration of data from analysis of cores is an essential component of the log models.Accurate values of permeability are derived from logs. In complex reservoirs, values of porosity and saturation derived from routine log analysis often do not accurately identify productivity. It is therefore necessary to develop a log model that will allow the prediction of another producibility parameter. In these studies we have derived foot-by-foot values of permeability for cored and non-cored intervals in all wells with suitable wireline logs.Use only the existing databases. No new wells will be drilled to aid reservoir description. Methodology Techniques of reservoir description used in these studies are based on the identification of rock types (intervals of rock with unique petrophysical properties). Rock types are identified on the basis of measured pore geometrical characteristics, principally pore body size (average diameter), pore body shape, aspect ratio (size of pore body: size of pore throat) and coordination number (number of throats per pore). This involves the detailed analysis of small rock samples taken from existing cores (conventional cores and sidewall cores). The rock type information is used to develop the vertical layering profile in cored intervals. Integration of rock type data with wireline log data allows field-wide extrapolation of the reservoir model from cored to non-cored wells. Emphasis is placed on measurement of pore geometrical characteristics using a scanning electron microscope specially equipped for automated image analysis procedures.2–4 A knowledge of pore geometrical characteristics is of fundamental importance to reservoir characterization because the displacement of hydrocarbons is controlled at the pore level; the petrophysical properties of rocks are controlled by the pore geometry.5–8 The specific procedure includes the following steps.Routine measurement of porosity and permeability.Detailed macroscopic core description to identify vertical changes in texture and lithology for all cores.Detailed thin section and scanning electron microscope analyses (secondary electron imaging mode) of 100 to 150 small rock samples taken from the same locations as the plugs used in routine core analysis. In the SBC reservoir, x-ray diffraction analysis is also used. The combination of thin section and x-ray analyses provides direct measurement of the shale volume, clay volume, grain size, sorting and mineral composition for the core samples analyzed.Rock types are identified for each rock sample using measured data on pore body size, pore throat size and pore interconnectivity (coordination number and pore arrangement).


2007 ◽  
Vol 10 (06) ◽  
pp. 730-739 ◽  
Author(s):  
Genliang Guo ◽  
Marlon A. Diaz ◽  
Francisco Jose Paz ◽  
Joe Smalley ◽  
Eric A. Waninger

Summary In clastic reservoirs in the Oriente basin, South America, the rock-quality index (RQI) and flow-zone indicator (FZI) have proved to be effective techniques for rock-type classifications. It has long been recognized that excellent permeability/porosity relationships can be obtained once the conventional core data are grouped according to their rock types. Furthermore, it was also observed from this study that the capillary pressure curves, as well as the relative permeability curves, show close relationships with the defined rock types in the basin. These results lead us to believe that if the rock type is defined properly, then a realistic permeability model, a unique set of relative permeability curves, and a consistent J function can be developed for a given rock type. The primary purpose of this paper is to demonstrate the procedure for implementing this technique in our reservoir modeling. First, conventional core data were used to define the rock types for the cored intervals. The wireline log measurements at the cored depths were extracted, normalized, and subsequently analyzed together with the calculated rock types. A mathematical model was then built to predict the rock type in uncored intervals and in uncored wells. This allows the generation of a synthetic rock-type log for all wells with modern log suites. Geostatistical techniques can then be used to populate the rock type throughout a reservoir. After rock type and porosity are populated properly, the permeability can be estimated by use of the unique permeability/porosity relationship for a given rock type. The initial water saturation for a reservoir can be estimated subsequently by use of the corresponding rock-type, porosity, and permeability models as well as the rock-type-based J functions. We observed that a global permeability multiplier became unnecessary in our reservoir-simulation models when the permeability model is constructed with this technique. Consistent initial-water-saturation models (i.e., calculated and log-measured water saturations are in excellent agreement) can be obtained when the proper J function is used for a given rock type. As a result, the uncertainty associated with volumetric calculations is greatly reduced as a more accurate initial-water-saturation model is used. The true dynamic characteristics (i.e., the flow capacity) of the reservoir are captured in the reservoir-simulation model when a more reliable permeability model is used. Introduction Rock typing is a process of classifying reservoir rocks into distinct units, each of which was deposited under similar geological conditions and has undergone similar diagenetic alterations (Gunter et al. 1997). When properly classified, a given rock type is imprinted by a unique permeability/porosity relationship, capillary pressure profile (or J function), and set of relative permeability curves (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993). As a result, when properly applied, rock typing can lead to the accurate estimation of formation permeability in uncored intervals and in uncored wells; reliable generation of initial-water-saturation profile; and subsequently, the consistent and realistic simulation of reservoir dynamic behavior and production performance. Of the various quantitative rock-typing techniques (Gunter et al. 1997; Hartmann and Farina 2004; Amaefule et al. 1993; Porras and Campos 2001; Jennings and Lucia 2001; Rincones et al. 2000; Soto et al. 2001) presented in the literature, two techniques (RQI/FZI and Winland's R35) appear to be used more widely than the others for clastic reservoirs (Gunter et al. 1997, Amaefule et al. 1993). In the RQI/FZI approach (Amaefule et al. 1993), rock types are classified with the following three equations: [equations]


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