Yang, Tao (Equinor ASA) | Arief, Ibnu Hafidz (Equinor ASA) | Niemann, Martin (Equinor ASA) | Houbiers, Marianne (Equinor ASA) | Meisingset, Knut Kristian (Equinor ASA) | Martins, Andre (Teradata) | Froelich, Laura (Teradata)
Mud gas data from drilling operations provide the very first indication of the presence of hydrocarbons in the reservoir. It has been a dream for decades in the oil industry to predict reservoir gas and oil properties from mud gas data, because it would provide knowledge of the reservoir fluid properties in an early stage, continuously for all reservoir zones, and at low costs. Previous efforts reported in the literature did not lead to a reliable method for quantitative prediction of the reservoir fluid properties from mud gas data. In this paper, we propose a novel approach based on machine learning which enables us to predict gas oil ratio (GOR) from advanced mud gas (AMG) data.
The current work is based on a previous successful pilot in unconventional (shale) reservoirs. Our aim is to extend the results of the pilot study to conventional reservoirs. In general, prediction of reservoir fluid properties is more challenging for conventional reservoirs than for unconventional reservoirs, due to the complexity of petroleum systems in conventional reservoirs. Instead of building a model directly from AMG data, we trained a machine learning model using a well-established reservoir fluid database with more than 2000 PVT samples. After thorough investigation of compositional similarity between PVT samples and AMG data, we applied the model developed from PVT samples to AMG data.
The predicted GORs from AMG data were compared with GOR measurements from corresponding PVT samples to assess the accuracy of the GOR predictions. The results from 22 wells with both AMG data and corresponding PVT samples show large agreement between prediction vs. measurement. The accuracy of the predictive model is much higher than previous results reported in the literature. In addition, a Quality Check (QC) metric was developed to efficiently flag low-quality AMG data. The QC metric is vital to give confidence level for GOR prediction based on AMG data when PVT samples are not available.
The study confirms that AMG data can be used as a new data source to quantitatively predict continuous reservoir fluid properties in the drilling phase. The method can be used to optimize wireline operations and for some cases, it provides a unique opportunity to acquire reservoir fluid data when conventional fluid sampling or use of wireline tools is not possible. After high-quality PVT data becomes available in the wireline logging phase, the continuous GOR prediction can be further improved and used to determine reservoir fluid gradient and reservoir compartmentalization.
Jie, Zhang (CNPC Engineering technology R&D company limited) | Xu, Xianguang (CNPC Engineering technology R&D company limited) | Wang, Lihui (CNPC Engineering technology R&D company limited) | Li, long (CNPC Engineering technology R&D company limited) | Zhang, Die (CNPC Engineering technology R&D company limited) | Zhao, Zhiliang (CNPC Engineering technology R&D company limited) | Wang, Shuangwei (CNPC Engineering technology R&D company limited)
Severe formation damage is induced by the invasion of working fluid and the subsequent water blocking. Surface modification by surfactant adsorption can change the wettability of the rock surface to enhance the removal efficiency of reservoir fluid and reduce the water blockage damage. Therefore, surfactant shows a good potential applicant in condense reservoir. In the current paper, an oligomeric silicone surfactant (OSSF) containing sulfonic acid groups is synthesized to improve the water flowback effect.
The critical micelle concentration (CMC) is determined by equilibrium surface tension. Micelle can be formed above the CMC and its size and distribution increase with the concentration. At the same time, the surface tension increases with the aging temperature but decreases with the adding of inorganic salt. The OSSF adsorption through solid-liquid surface can change the surface chemical composition and transfer the wettability of reservoir from water-wet to gas-wet by decreasing the surface energy. Increasing temperature leads to the change in the adsorption isotherm from Langmuir type (L-type) to "double plateau" type (LS- type). Quantum chemistry study shows that the adsorbed layer of OSSF can reduce the adhesive force of CH4 and H2O on the pore surface of cores. The OSSF can also decease the initial foaming volume and stability in induction period and accelerating period of sodium dodecyl benzene sulfonate (SDBS).
It is found that the surface tension of OSSF increases with aging temperature but decreases with the adding of inorganic salts.The OSSF has positive effect on wettability reversal to water-wet reservoir by adsorption on solid-liquid interface. The results indicate OSSF adsorption layer can change surface chemical composition and exhibit lower interface energy than that of the cores. The presence of NaCl can decrease foaming volume and improve foam stability of OSSF. At the same time, OSSF can decease the initial foaming volume and stability in induction period and accelerating period of sodium dodecyl benzene sulfonate (SDBS).
Hu, Zhenhua (PetroChina Liaohe Oilfield Company) | Zhang, Shenqin (PetroChina Qinghai Oilfield Company) | Wu, Fangfang (Schlumberger) | Liu, Xunqi (Schlumberger) | Wu, Jinlong (Schlumberger) | Li, Shenzhuan (Schlumberger) | Wang, Yuxi (Schlumberger) | Zhao, Xianran (Schlumberger) | Zhao, Haipeng (Schlumberger)
The igneous reservoir of Shahejie formation in eastern sag of Liaohe depression is characterized by complex geological environment, variable lithology and high heterogeneity. Reservoir evaluation is difficult only based on conventional logs due to complex lithology and pore structures. Effective igneous reservoirs were identified and reservoir controlling factors were analyzed based on effective porosity calculation, pore structure analysis, lithology identification, lithofacies analysis, fracture evaluation and heterogeneity analysis by combing nuclear magnetic resonance data, micro-resistivity image data, conventional logs as well as mud logging data.
Based on our study, the igneous reservoirs in the study area are more related with effective porosity and pore connectivity, and less related with fractures. Good reservoirs are mainly distributed on the top part of explosive facies and effusive facies, where lithologies are mainly Trachyte, volcanic breccia and breccia-bearing tuff. The weathering leaching process is quite important for igneous reservoirs, but the reservoir qulity would not be good if the weathering process is too strong as it will lead to low effective porosity.
The accuracy of igneous reservoir evaluation gets improved a lot by this integrated approach and the conclusion from this study will help to optimize igneous reservoire exploration plan.
Wu, Kunyu (Research Institute of Exploration & Development of Qinghai Oil Field, CNPC) | Zhang, Yongshu (Research Institute of Exploration & Development of Qinghai Oil Field, CNPC) | Zhang, Shenqin (Research Institute of Exploration & Development of Qinghai Oil Field, CNPC)
The Qaidam Basin is a big intermountain Mesozoic-Cenozoic petroliferous basin in western China. The huge thickness Cenozoic strata and tectonic deformation formed a good combination of hydrocarbon sources, reservoirs and caps, leading to huge hydrocarbon potential of the basin. The Western Yingxiongling Area locates in the western part of the Qaidam basin, during the Cenozoic era a special tectonic dynamics background was formed by the joint control of the sinistral strike-slip fault of the East Kunlun and the sinistral strike-slip fault of the Altun (
Is Surfactant Environmentally Safe for Offshore Use and Discharge? The current presentation date and time shown is a TENTATIVE schedule. The final/confirm presentation schedule will be notified/available in February 2019. Designing Cement Jobs for Success - Get It Right the First Time! Connected Reservoir Regions Map Created From Time-Lapse Pressure Data Shows Similarity to Other Reservoir Quality Maps in a Heterogeneous Carbonate Reservoir. X. Du, Y. Jin, X. Wu, U. of Houston; Y. Liu, X. Wu, O. Awan, J. Roth, K.C. See, N. Tognini, Shell Intl.
By International Petroleum Technology Conference (IPTC) Monday, 25 March 0900-1600 hours Instructors: Olivier Dubrule and Lukas Mosser, Imperial College London Deep Learning (DL) is already bringing game-changing applications to the petroleum industry, and this is certainly the beginning of an enduring trend. Many petroleum engineers and geoscientists are interested to know more about DL but are not sure where to start. This one-day course aims to provide this introduction. The first half of the course presents the formalism of Logistic Regression, Neural Networks and Convolutional Neural Networks and some of their applications. Much of the standard terminology used in DL applications is also presented. In the afternoon, the online environment associated with DL is discussed, from Python libraries to software repositories, including useful websites and big datasets. The last part of the course is spent discussing the most promising subsurface applications of DL.
Introduction Of the three permafrost regions, our calculations show Mohe Basin has the thickest hydrate stability (1300 m). This is followed by Qinghai-Tibet Plateau (1200 m) and Qilian Mountain (800 m).
With the purpose of studying Chinese mainland shallow crustal stress state, we have built a spherical shell finite element model including main active faults, tectonic blocks, topography, and Moho discontinuity with the consideration of lithospheric heterogeneity. In this model, we deem gravity and plate tectonic stress as the main influential factors, and use the in-situ stress as the main constraints to make the simulation results and in-situ stress measurement comparable. By this way, we obtain the absolute value estimations of China mainland stress field.
Numerical results are: (1) the general directions of maximum horizontal stress are distributed radially with the center of Tibetan Plateau. From east to west, the directions of maximum horizontal stress gradually rotate clockwise from NS to NNE, NE, NEE, SE, consistent with previous results of focal mechanism solution; (2) the stress states in different study regions vary greatly. Stress is obviously lower in the center of Qinghai-Tibet active block and higher in its surrounding areas; (3) the maximum and minimum tectonic stress σΗ and σh are mainly compressive at the depth of 2000 meters in the shallow crust of Chinese mainland, and the magnitude range are 14.5MPa < σΗ <58.0MPa and 3.8MPa < σh <26.7MPa respectively.
The in-situ stress measurement method is a primary means to understand the present-day state of stress, but due to the measurement restriction, we can only measure the shallow crust stress state. How to take advantage of various known data to analyze the regional crustal stress state quantitatively is a complex problem involving geology, mechanics, mathematics and many other disciplines. The formation of tectonic stress field is determined by many factors such as tectonic movements, geological lithology, topography, rock weight, etc. In-situ stress is the result of the combined effects of these factors. Based on the measured data of stress, the deduction of stress in non-measured region can be regarded as a process of simulating the effects of these factors. In this paper, finite element method is applied to calculate the absolute stress of the shallow crust in China. The fundamental concept of our research is following: (1) Establish our finite element model with the consideration of previous studies concerning geology, geophysics, rock mechanics, etc.; (2) Use gravitational field as the initial field and apply horizontal boundary loading based on results of previous related researches; (3) Adjust physical parameters and boundary conditions to make the simulated shell surface stress directions and value close to the in-situ stress measurement results as possible, and eventually obtain the current Chinese land shallow stress field.
The Beetaloo Sub-basin in the Northern Territory is one of Australia's most prospective basins for shale gas production. The Beetaloo gas shales are unique in that they could become some of the oldest producing source rocks in the world, if commercialized successfully. In this work we characterise gas shales from two target reservoirs in the Beetaloo Sub-basin and compare them to other shales from around the globe to improve the current understanding of what controls gas adsorption on shales.
We characterise the methane adsorption capacity of two sets of Beetaloo shale samples: middle Velkerri B shale (8 samples, ~2450 m depth) and lower Kyalla shale (10 samples, ~1300 m depth). Measurements are performed at reservoir conditions, i.e. up to 110°C and 30 MPa, using CSIRO's gravimetric isotherm rig. The samples’ mineralogy is analysed using X-ray powder diffraction (XRD) and the total organic carbon (TOC) is determined using a LECO machine.
Our experiments demonstrate that the gravimetric rig is capable of obtaining fast and reliable measurements on low adsorbing shales at high pressures and high temperatures for sample quantities of around 90 g. The results highlight that the adsorption capacity of middle Velkerri B shale is significantly higher than of lower Kyalla shale (average Langmuir volume 3.23 m3/t compared to 2.27 m3/t) and that the isotherms can be represented using a Langmuir relationship. In spite of their age, the Beetaloo shales exhibit adsorption behaviour comparable to that of other shales with similar TOC.
Two global shale data sets, which include the Beetaloo samples, demonstrate that there is a strong relationship between TOC and a shale's adsorption capacity. However, the TOC alone cannot account for the differences in adsorbed amount observed within the two sets of Beetaloo shale samples.
Bulk clay content appears to control the adsorption capacity of shales with low TOC (< 2%), such as the lower Kyalla shale. Analysis assessing the contribution of individual clay minerals to the CH4 adsorption capacity indicates that it is the high illite/muscovite content (30-40%) that controls adsorption on the lower Kyalla shale samples. For the high TOC/low clay middle Velkerri B samples (3.7-6.3% TOC, 20-23% clay) clay content cannot account for the differences observed in adsorbed gas between the samples, even as a secondary control. Further investigation is required to understand what controls gas adsorption on this shale.
Wu, Yongguo (BGP Inc, CNPC) | He, Zhenhua (State Key Laboratory of Oil & Gas Reservoir Geology and Exploitation, Chengdu University of Technology) | He, Jie (State Key Laboratory of Oil & Gas Reservoir Geology and Exploitation, Chengdu University of Technology) | Deng, Zhiwen (Qinghai Oilfield Company, PetroChina) | Wang, Yongsheng (BGP Inc, CNPC) | Yin, Wuhai (Qinghai Oilfield Company, PetroChina)
Summary Sanhu area in Qaidam Basin is one of the major onshore gas fields in China Mainland, its pay zone is at Quaternary and the depth of gas reservoir is shallow. It is difficult to solve the gas-bearing anomaly and the low-relief structure imaging problems in true or false "Gas Cloud Areas" through pure P-wave seismic data acquired previously. According to the special features of the seismic and geological conditions in this area, the following techniques are used: 1) The joint excitation technology through low-frequency vibrator and S-wave-vibrator is adopted. Through the implementation of the P-wave and S-wave joint acquisition technology, high-quality P-wave and S-wave seismic data are obtained in Sanhu area. The boundaries of the gas-bearing anomalous zone are clear in P-wave section and the low relief structures are better imaging in S-wave section.