scholarly journals Initial pore pressures under the Lusi mud volcano, Indonesia

2015 ◽  
Vol 3 (1) ◽  
pp. SE33-SE49 ◽  
Author(s):  
Mark Tingay
Keyword(s):  
Pore Pressure ◽  
Mud Volcano ◽  
Prediction Methods ◽  
Pressure Gradients ◽  
Modern Times ◽  
Fine Grained ◽  
High Magnitude ◽  
Pore Pressures ◽  
Pore Pressure Prediction ◽  
Well Data

The Lusi mud volcano of East Java, Indonesia, remains one of the most unusual geologic disasters of modern times. Since its sudden birth in 2006, Lusi has erupted continuously, expelling more than 90 million cubic meters of mud that has displaced approximately 40,000 people. This study undertakes the first detailed analysis of the pore pressures immediately prior to the Lusi mud volcano eruption by compiling data from the adjacent (150 m away) Banjar Panji-1 wellbore and undertaking pore pressure prediction from carefully compiled petrophysical data. Wellbore fluid influxes indicate that sequences under Lusi are overpressured from only 350 m depth and follow an approximately lithostat-parallel pore pressure increase through Pleistocene clastic sequences (to 1870 m depth) with pore pressure gradients up to [Formula: see text]. Most unusually, fluid influxes, a major kick, connection gases, elevated background gases, and offset well data confirm that high-magnitude overpressures also exist in the Plio-Pleistocene volcanic sequences (1870 to approximately 2833 m depth) and Miocene (Tuban Formation) carbonates, with pore pressure gradients of [Formula: see text]. The varying geology under the Lusi mud volcano poses a number of challenges for determining overpressure origin and undertaking pore pressure prediction. Overpressures in the fine-grained and rapidly deposited Pleistocene clastics have a petrophysical signature typical of disequilibrium compaction and can be reliably predicted from sonic, resistivity, and drilling exponent data. However, it is difficult to establish the overpressure origin in the low-porosity volcanic sequences and Miocene carbonates. Similarly, the volcanics do not have any clear porosity anomaly, and thus pore pressures in these sequences are greatly underestimated by standard prediction methods. The analysis of preeruption pore pressures underneath the Lusi mud volcano is important for understanding the mechanics, triggering, and longevity of the eruption, as well as providing a valuable example of the unknowns and challenges associated with overpressures in nonclastic rocks.

Seismic pore pressure prediction without well data and poorly defined normal compaction trend lines: a case study from the Río Bravo Delta, Northern Mexico

2005 ◽  
Author(s):  
Juan C. Clarembaux ◽  
Marcelo Giusso ◽  
Roberto Gullco ◽  
Daniel Mujica ◽  
Carlos Carabeo Miranda ◽  
...  
Keyword(s):  
Pore Pressure ◽  
Northern Mexico ◽  
Pore Pressure Prediction ◽  
Rio Bravo ◽  
Well Data

Predrill pore‐pressure prediction using seismic data

Geophysics ◽  
2002 ◽  
Vol 67 (4) ◽  
pp. 1286-1292 ◽  
Author(s):  
C. M. Sayers ◽  
G. M. Johnson ◽  
G. Denyer
Keyword(s):  
Velocity Field ◽  
Gulf Of Mexico ◽  
Pore Pressure ◽  
Seismic Data ◽  
Seismic Velocities ◽  
Pressure Data ◽  
Pore Pressure Prediction ◽  
Well Data ◽  
Interval Velocities ◽  
Reflection Tomography

1A predrill estimate of pore pressure can be obtained from seismic velocities using a velocity‐to–pore‐pressure transform, but the seismic velocities need to be derived using methods having sufficient resolution for well planning purposes. For a deepwater Gulf of Mexico example, significant differences are found between the velocity field obtained using reflection tomography and that obtained using a conventional method based on the Dix equation. These lead to significant differences in the predicted pore pressure. Parameters in the velocity‐to–pore‐pressure transform are estimated using seismic interval velocities and pressure data from nearby calibration wells. The uncertainty in the pore pressure prediction is analyzed by examining the spread in the predicted pore pressure obtained using parameter combinations which sample the region of parameter space consistent with the available well data. If calibration wells are not available, the ideas proposed in this paper can be used with measurements made while drilling to predict pore pressure ahead of the bit based on seismic velocities.

Abnormal High Pore Pressure Prediction and Cause Analysis of Salt and Anhydrite Formation of Fauqi Oilfield in Iraq

2014 ◽  
Vol 638-640 ◽  
pp. 350-354
Author(s):  
Sheng Xiang Wang ◽  
Feng Lin ◽  
Fan Zhang ◽  
Jin Gen Deng ◽  
Bao Hua Yu ◽  
...  
Keyword(s):  
High Pressure ◽  
Pore Pressure ◽  
Oil Field ◽  
Prediction Methods ◽  
Sonic Velocity ◽  
Composite Analysis ◽  
Cause Analysis ◽  
Density Data ◽  
Field Situation ◽  
Pore Pressure Prediction

Abnormal high pressure exists in Lower Fars formation of Fauqi oil field in Iraq and lead to many complicated problems during drilling. There are salt, anhydrite and shale in Lower Fars formation through lithology analysis. Through the crossplot of sonic velocity vs. density data, it can be identified that the high pressure of Lower Fars is cause by the undercompaction of shale. Through composite analysis of different prediction methods of pore pressure, Eaton model is used to calculate the pore pressure of Lower Fars. The pore pressure begins to increase at the MB4 layer and declines to normal value at MB2 layer, and the peak is about 2.20 . The calculated results are in conformity with field situation, which can be applid to guide drilling practice in Fauqi oil field.

Pore-pressure prediction in carbonate rock using wavelet transformation

Geophysics ◽  
2014 ◽  
Vol 79 (4) ◽  
pp. D243-D252 ◽  
Author(s):  
Fu Yu ◽  
Yan Jin ◽  
Kang Ping Chen ◽  
Mian Chen
Keyword(s):  
Pore Pressure ◽  
Wave Velocity ◽  
Carbonate Rocks ◽  
Wavelet Transformation ◽  
Pressure Change ◽  
P Wave ◽  
Small Scale ◽  
Prediction Methods ◽  
P Wave Velocity ◽  
Pore Pressure Prediction

Accurate prediction of pore pressure can assist engineers to better work out and optimize an oilfield development plan. Because the P-wave velocity only experiences small-scale fluctuations for pore-pressure change in carbonate rocks, existing well-known pore-pressure prediction methods are incapable of predicting pore pressure in carbonate rocks with field-required accuracy. We evaluated a new method based on the P-wave velocity decomposition and wavelet transformation to predict pore pressure in carbonate rocks. The P-wave velocity was decomposed into contributions from the pore fluid and the rock framework using Biot’s theory. The effect of lithology, pore structure, porosity, and pore pressure on P-wave velocity was studied by theoretical analysis and experiments. Rapid triaxial rock-system tests were carried out to measure the P- and S-wave velocities when pore pressure, pore structure, and porosity were changed, and X-ray diffraction tests were used to measure mineral components. The small-scale fluctuations of the P-wave velocity can be extracted and amplified using wavelet transformation. We found that the small-scale fluctuations of the P-wave velocity were caused by pore-pressure change in carbonate rocks and the large-scale fluctuations of the P-wave velocity depended on the rock framework. Overpressure formation can be identified by the high-frequency detail of wavelet transformation of P-wave velocity. A pore-pressure prediction model relating the contribution from the pore fluid to the P-wave velocity was developed. This model is an improvement over existing pore-pressure prediction methods that mainly rely on empirical relations between the P-wave velocity and the pore pressure. This new method was successfully applied to carbonate rocks in Tazhong Block, Tarim oilfield, demonstrating the feasibility of the proposed pore-pressure prediction method.

scholarly journals COMPARING TWO MULTIVARIATE GEOSTATISTICS TOOLS FOR PORE PRESSURE PREDICTIVE MODELLING

2019 ◽  
Vol 37 (4) ◽  
pp. 471
Author(s):  
Flávia Braz Ponte ◽  
Francisco Fábio de Araújo Ponte ◽  
Adalberto Silva ◽  
Alberto Garcia Figueiredo Jr
Keyword(s):  
High Pressure ◽  
Pore Pressure ◽  
Seismic Velocity ◽  
Predictive Modelling ◽  
Pressure Gradients ◽  
Multivariate Geostatistics ◽  
Interval Velocity ◽  
Pressure Fields ◽  
Collocated Cokriging ◽  
Pore Pressure Prediction

 ABSTRACT. Pore pressure prediction has been an increasing concern during well designing due to the numerous accidents recorded because of mistaken estimations of high pressure fields. This paper depicts a predictive modelling of pore pressure using multivariate geostatistics tools called LVM and collocated cokriging. The resulting maps of LVM and collocated cokriging were compared. Geostatistics were used to estimate pore pressure distribution in unsampled places considering the two different scales and spatial variation from well measurements (pore pressure) and 3D seismic velocity data. When pore pressure gradients recorded in the wells have been defined and the seismic interval velocity analyzed, pore pressure estimation can be done by using the geostatistics approaches. This is a method for estimating the geopressure field distribution at basin or reservoir level that offers the advantage of the possibility of extracting pore pressure information at any place.Keywords: geostatistics approaches, LVM, collocated cokriging, high pressure fields.RESUMO. Devido aos numerosos acidentes registrados por estimativas equivocadas de campos de alta pressão, a preocupação com a previsão de pressão de poros tem aumentado durante projetos de poços. Este artigo descreve uma modelagem para previsão de pressão de poros usando duas ferramentas da geoestatística multivariada, a LVM e a cokrigagem colocada. Neste estudo, essas duas metodologias foram comparadas. A geoestatística foi utilizada para estimar a distribuição de pressão de poros em locais não amostrados, permitindo a integração dos dados das duas variáveis, velocidade sísmica e dados de poço, em diferentes escalas e variação espacial. Quando os gradientes de pressão de poros, registrados em poços, são definidos e a velocidade intervalar da sísmica é analisada, existindo correlação entre eles, a previsão de pressão de poros pode ser feita utilizando a abordagem geoestatística. A vantagem de uma modelagem geoestatística 3D de gradiente pressão de poros é a possibilidade de extração de informação de pressão em qualquer local dentro da área modelada.Palavras-chave: abordagem geoestatística, LVM, cokrigagem colocada, campos de alta pressão.

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