scholarly journals An Efficient Approach for Real-Time Prediction of Rate of Penetration in Offshore Drilling

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Xian Shi ◽  
Gang Liu ◽  
Xiaoling Gong ◽  
Jialin Zhang ◽  
Jian Wang ◽  
...  

Predicting the rate of penetration (ROP) is critical for drilling optimization because maximization of ROP can greatly reduce expensive drilling costs. In this work, the typical extreme learning machine (ELM) and an efficient learning model, upper-layer-solution-aware (USA), have been used in ROP prediction. Because formation type, rock mechanical properties, hydraulics, bit type and properties (weight on the bit and rotary speed), and mud properties are the most important parameters that affect ROP, they have been considered to be the input parameters to predict ROP. The prediction model has been constructed using industrial reservoir data sets that are collected from an oil reservoir at the Bohai Bay, China. The prediction accuracy of the model has been evaluated and compared with the commonly used conventional artificial neural network (ANN). The results indicate that ANN, ELM, and USA models are all competent for ROP prediction, while both of the ELM and USA models have the advantage of faster learning speed and better generalization performance. The simulation results have shown a promising prospect for ELM and USA in the field of ROP prediction in new oil and gas exploration in general, as they outperform the ANN model. Meanwhile, this work provides drilling engineers with more choices for ROP prediction according to their computation and accuracy demand.

10.29007/4sdt ◽  
2022 ◽  
Author(s):  
Vu Khanh Phat Ong ◽  
Quang Khanh Do ◽  
Thang Nguyen ◽  
Hoang Long Vo ◽  
Ngoc Anh Thy Nguyen ◽  
...  

The rate of penetration (ROP) is an important parameter that affects the success of a drilling operation. In this paper, the research approach is based on different artificial neural network (ANN) models to predict ROP for oil and gas wells in Nam Con Son basin. The first is the process of collecting and evaluating drilling parameters as input data of the model. Next is to find the network model capable of predicting ROP most accurately. After that, the study will evaluate the number of input parameters of the network model. The ROP prediction results obtained from different ANN models are also compared with traditional models such as the Bingham model, Bourgoyne & Young model. These results have shown the competitiveness of the ANN model and its high applicability to actual drilling operations.


2020 ◽  
Vol 8 (1) ◽  
pp. SA49-SA61
Author(s):  
Huihuang Tan ◽  
Donghong Zhou ◽  
Shengqiang Zhang ◽  
Zhijun Zhang ◽  
Xinyi Duan ◽  
...  

Amplitude-variation-with-offset (AVO) technique is one of the primary quantitative hydrocarbon discrimination methods with prestack seismic data. However, the prestack seismic data are usually have low data quality, such as nonflat gathers and nonpreserved amplitude due to absorption, attenuation, and/or many other reasons, which usually lead to a wrong AVO response. The Neogene formations in the Huanghekou area of the Bohai Bay Basin are unconsolidated clastics with a high average porosity, and we find that the attenuation on seismic signal is very strong, which causes an inconsistency of AVO responses between seismic gathers and its corresponding synthetics. Our research results indicate that the synthetic AVO response can match the field seismic gathers in the low-frequency end, but not in the high-frequency components. Thus, we have developed an AVO response correction method based on high-resolution complex spectral decomposition and low-frequency constraint. This method can help to achieve a correct high-resolution AVO response. Its application in Bohai oil fields reveals that it is an efficient way to identify hydrocarbons in rocks, which provides an important technique for support in oil and gas exploration and production in this area.


2021 ◽  
Author(s):  
Huang Zhen ◽  
Yang Bo ◽  
Li Guoying ◽  
Ren Jian ◽  
Wang Xiaoling

Abstract Laizhouwan sag in Bohai Bay basin is a fault basin controlled by extensional fault depression and strike slip pull apart, which is an important oil and gas exploration area in Bohai Bay. Exploration practice shows that the prediction of high quality reservoir is the core problem of exploration in this area. Based on the analysis of drilling, seismic data and structural physical simulation in Laizhouwan depression, this paper analyzes the structural deformation under the stress field of strike slip extensional superposition, and points out the dynamic source controlled sand model in the strike slip extensional superposition area. Firstly, The structural response of "pressure relief settlement, pressure boosting uplift" under the mechanism of strike slip extension stress superposition stress is the root cause of block uplift drop alternation transformation. As a result, the southern slope zone of Laizhouwan depression shows the structural pattern of early uplift and late uplift in the East and early uplift and late uplift in the west, forming a "seesaw" structural evolution pattern. Secondly, the unique paleogeomorphology controls the orderly distribution of sedimentary system in time and space. In the Paleocene, the east uplifted, forming a local provenance system. In the denudation area above the slope break developed fracture weathering shell type reservoirs, and the subsidence area under the slope break developed fan delta deposits; In the early Eocene, the relatively flat platform palaeogeomorphology was developed, which created favorable conditions for the development of mixed sedimentary body of lacustrine carbonate and delta; At the end of Eocene, the West was pressurized and uplifted, the East was released and subsided, and the braided river delta sediments of Western provenance were developed. Under the guidance of this recognition, the hidden dynamic provenance was successfully identified in the study area.


2020 ◽  
Vol 17 (6) ◽  
pp. 1540-1555
Author(s):  
Jin-Jun Xu ◽  
Qiang Jin

AbstractNatural gas and condensate derived from Carboniferous-Permian (C-P) coaly source rocks discovered in the Dagang Oilfield in the Bohai Bay Basin (east China) have important implications for the potential exploration of C-P coaly source rocks. This study analyzed the secondary, tertiary, and dynamic characteristics of hydrocarbon generation in order to predict the hydrocarbon potentials of different exploration areas in the Dagang Oilfield. The results indicated that C-P oil and gas were generated from coaly source rocks by secondary or tertiary hydrocarbon generation and characterized by notably different hydrocarbon products and generation dynamics. Secondary hydrocarbon generation was completed when the maturity reached vitrinite reflectance (Ro) of 0.7%–0.9% before uplift prior to the Eocene. Tertiary hydrocarbon generation from the source rocks was limited in deep buried sags in the Oligocene, where the products consisted of light oil and gas. The activation energies for secondary and tertiary hydrocarbon generation were 260–280 kJ/mol and 300–330 kJ/mol, respectively, indicating that each instance of hydrocarbon generation required higher temperature or deeper burial than the previous instance. Locations with secondary or tertiary hydrocarbon generation from C-P coaly source rocks were interpreted as potential oil and gas exploration regions.


2020 ◽  
pp. 1051-1062
Author(s):  
Zaher JabbarAttwan AL Zirej ◽  
Hassan Abdul Hadi

The main objective of this study is to develop a rate of penetration (ROP) model for Khasib formation in Ahdab oil field and determine the drilling parameters controlling the prediction of ROP values by using artificial neural network (ANN).      An Interactive Petrophysical software was used to convert the raw dataset of transit time (LAS Readings) from parts of meter-to-meter reading with depth. The IBM SPSS statistics software version 22 was used to create an interconnection between the drilling variables and the rate of penetration, detection of outliers of input parameters, and regression modeling. While a JMP Version 11 software from SAS Institute Inc. was used for artificial neural modeling.      The proposed artificial neural network method depends on obtaining the input data from drilling mud logging data and wireline logging data. The data then analyzes it to create an interconnection between the drilling variables and the rate of penetration.      The proposed ANN model consists of an input layer, hidden layer and outputs layer, while it applies the tangent function (TanH) as a learning and training algorithm in the hidden layer. Finally, the predicted values of ROP are compared with the measured values. The proposed ANN model is more efficient than the multiple regression analysis in predicting ROP. The obtained coefficient of determination (R2) values using the ANN technique are 0.93 and 0.91 for training and validation sets, respectively. This study presents a new model for predicting ROP values in comparison with other conventional drilling measurements.


2013 ◽  
Vol 663 ◽  
pp. 876-881
Author(s):  
Qiang Lan ◽  
Qian Zhang

Kongdian is located in the eastern part of Bohai Bay. This region has good prospects for oil and gas exploration, but the seismic geologic condition is very complex. After several stages of exploration, a number of significant exploration results have been achieved, but the gradually exposed problems restricted the exploration to go further. In a new round of exploration, the high and low frequency energy compensation technology, advantaged band deconvolution processing technology, dividing frequency high-precision residual static corrections, high-resolution well control-target wavelet deconvolution technology, common scattering point imaging technology and prestack time migration processing technology have been used to improve exploration accuracy. Five potential areas were found in this region according to the new processed seismic data and subsequent interpretation work, achieving the pleasant situation of initial success following the exploration in that year.


2018 ◽  
Vol 6 (2) ◽  
pp. T283-T298 ◽  
Author(s):  
Xianzheng Zhao ◽  
Lihong Zhou ◽  
Xiugang Pu ◽  
Wenzhong Han ◽  
Zhannan Shi ◽  
...  

Cangdong is a typical oil-rich sag in the Bohai Bay Basin, China. After more than 50 years of exploration and development, the Kong2 Member (the major hydrocarbon play in the sag) still has considerable residual oil and gas resource potential. To pursue replacement areas of oil and gas exploration and development, the basic geology of the entire Kong2 Member in Cangdong Sag as a unit has been reexamined, and the findings have been used to guide the secondary exploration deployment. In this study, the characteristics of sedimentary reservoirs, source rocks, and oil and gas distribution in the Kong2 Member have been systematically studied, and a sedimentary model of the ring belt-circle layer of the closed lake basin in the Kong2 Member of the Cangdong Sag, with three segments (high, middle, and low) on the profile, three ring belts (outer, middle, and inner) on the plane, and three circle layers (outer, middle, and inner) in space has been established. The ring belt and circle layer are jointly controlled by water-body differentiation in the closed lake basin, source-material supply, depositional accommodation space, and deposition base-level cycle, and they can be in round, oval, long strip, and irregular shapes. The outer ring (circle), located near the basin margin, mainly has delta-front subfacies conventional coarse-grained medium-thick sandstone and near-source structural and stratigraphic-lithologic reservoirs; the middle ring (circle), the transitional zone from the basin margin to the central basin, is dominated by fine sandstone, siltstone, and lacustrine carbonates of front delta subfacies, and it mainly contains isolated lithologic reservoirs and unconventional tight oil; the inner ring (circle) is the high-quality hydrocarbon source-rock development zone in the center of the closed lake basin, featuring a high abundance of shale, where the dolomite and siltstone of distal gravity flow right next to source rock, and fine-grained diamictite of the source reservoir in one area rich in tight oil, whereas the high-abundance shale of frequent source-reservoir interbeds is rich in shale oil. The strategy of oil and gas exploration deployment is to look for structural, stratigraphic-lithologic reservoirs in the outer circle (outside source), lithologic reservoirs in the middle circle (near source), and retained tight oil and shale oil in the inner ring (inside source). In recent years, major discoveries have been made in oil and gas exploration in the three circle layers of the Kong2 Member in the Cangdong Sag through drilling, especially in tight-oil exploration in the inner-circle layer: two sandstone sweet-spot intervals of greater than 60 m and three dolomite sweet-spot intervals of greater than 100 m have been confirmed. The maximum daily oil production of vertical wells after fracturing is up to 50 t; several hundred square kilometers of favorable exploration area has been delineated, with an estimated oil geologic resource of 100 million tons.


2013 ◽  
Vol 703 ◽  
pp. 123-126
Author(s):  
Jing Jun Zhang ◽  
Cheng Zhi Liu

Properties of Energy Materials (oil and gas) is very complex and important. In recent years, in Chinese eastern, western and mid continental basins, multiple rock oil and gas fields are found, such as Songliao Basin, Bohai Bay Basin, Erlian Basin, Tuha Basin, Junggar Basin, Sichuan Basin. Volcanic rock reservoir with its rich oil and gas resources, tremendous development potential, has aroused the domestic and foreign experts and scholars attention, volcanic rock oil and gas exploration theory and technology has been rapid development. In order to understand volcanic rock reservoir from the origin, further exploration target and guide the exploration deployment, the Properties of Energy Materials (oil and gas), main factors affecting of the development and comprehensive evaluation have become the research hot spots and the focus, there are many research techniques and results.


2018 ◽  
Vol 36 (6) ◽  
pp. 1519-1545 ◽  
Author(s):  
Siding Jin ◽  
Haiyang Cao ◽  
Hua Wang ◽  
Shanbin Chen

The Bohai Bay Basin is the second largest oil-producing basin in China located on the east Asian margin. The Bohai Bay Basin contains numerous depressions, sub-basins, and sags. One of these, the Nanpu Sag, has played a particularly important role in oil and gas exploration in recent years. Four depositional systems are recognized in the Nanpu Sag, fan-delta, braided-river delta, turbidite deposits, and lacustrine systems. In the Paleogene, the Nanpu Sag underwent complex and multi-phased rifting evolution. Two evolutionary phases have been identified: the syn-rift phase and the post-rift phase, the syn-rift stage can be further sub-divided into four episodes. This study reveals the considerable faulting activity and associated strong subsidence that occurred during the deposition of the Dongying Formation in the fourth episode of the syn-rift stage. The depositional systems and the tectonic activity during the fourth episode in the Nanpu Sag have very different characteristics compared to those of other depressions or sub-basins in the Bohai Bay Basin. Boundary fault activity was extremely intense during the deposition of the Dongying Formation, especially the east to west trending faults, including the Xinanzhuang Fault and the Gaoliu Fault. Moreover, the migration of subsidence centers from the Shahejie Formation to the Dongying Formation is a result of the strong down-warping that occurred during the fourth episode of the syn-rift stage. In the Nanpu Sag, the Dongying Formation is of great significance to hydrocarbon exploration, which is affected by both the intensity of fault activity and magnitude of basement subsidence.


2020 ◽  
Vol 61 (5) ◽  
pp. 104-113
Author(s):  
Oanh Thi Tran ◽  
Khanh Duy Pham ◽  
Quy Van Hoang ◽  
Muoi Duy Nguyen ◽  
Ngan Thi Bui Ha Hai Thi Nguyen ◽  
...  

The presence of volcanic materials in reservoir will reduce the porosity value and effect to the quality of reservoirs. Therefore, understanding the distribution of this object will be of great significance in the orientation of oil and gas exploration and exploitation. This paper applies seismic attribute analysis method combined with artificial neural network (ANN) application to predict the distribution of volcanic materials in D sequence. Attributes selected as input for ANN training including RMS, RAI and Specdecom attribute. The results indicate that volcanic materials mainly appear in the to the Southwest of block (around D well and the West of E well), a small part is scattered near Con Son swell. The correlation coefficient among seismic attribute is from 71 to ~ 80%, this shows that the reliability of the results of network training is relatively high. Therefore, this method can be used to predict the distribution of volcanic materials in the study area.


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