Development of polygonal fault systems: a test of hypotheses

Polygonal networks of normal faults in layer-bound sequences of fine-grained mudstones have formed without regional tectonic extension. The two leading hypotheses concerning the generic mechanism responsible for their development are: (1) horizontal stresses are reduced by syneresis; and (2) coefficients of residual friction are very low. To discriminate between these hypotheses, the ratios between the minimum horizontal and the vertical effective stresses have been estimated in four North Sea wells penetrating Oligocene and Miocene sequences that contain polygonal fault networks. The effective stress ratios are c. 0.8, consistent with very low coefficients of friction but not with syneresis

Pore pressure estimation from mudrock porosities in Tertiary basins, SE Asia

Porosity reduction during mechanical compaction of a sediment generally has been assumed to be controlled by the increase in vertical effective stress, which is convenient because vertical stress profiles may be readily calculated from density logs. Poroelasticity theory shows, however, that mean effective stress controls porosity reduction. According to published data, horizontal stresses increase with overpressure, as well as with depth, so mean stress and vertical stress profiles are poorly correlated in overpressured sections. We have used wireline logs to compare the pore pressures estimated in mudrocks by relating porosity to mean effective stress and to vertical effective stress for overpressured Tertiary sections in southeast Asia. Wells from three different basins were studied. Mudrock porosities were estimated from the sonic log response and sorted by lithology according to the natural gamma-log response. Two sets of normal compaction curves, relating porosity to mean effective stress and to vertical effective stress, were determined empirically by fitting data points where the pore pressure was thought to be hydrostatic. These curves were then used to estimate the minimum pore pressure corresponding to mudrock porosity values in the overpressured sections. The pore pressures inferred using the mean effective stress are consistent with direct measurements of pore pressure in the adjacent sands. In contrast, pore pressures inferred in mudrocks using the vertical effective stress are significantly lower for the overpressured sections, implying discontinuities in the pore pressure profiles at lithological boundaries, which cannot readily be explained. We conclude that the pore pressures estimated using the vertical effective stress are wrong and that empirical relationships between porosity and vertical effective stress should not be used for estimating pore pressures: porosity should be empirically related to mean effective stress instead

Variation of velocity with effective stress in chalk – null result from North Sea well data

Wireline log data and pore pressure measurements from eight wells have been analysed to investigate how velocity in the Chalk of the Central Graben, North Sea depends on porosity and vertical effective stress. The main conclusion is that velocity shows no detectable dependence on vertical effective stress when porosity and vertical effective stress are treated as independent variables. This result contrasts with the behaviour of shales, which exhibit a reduction in velocity on unloading. The significance is that velocity in the Chalk cannot be used to detect the presence of any overpressure caused by unloading. It is suggested that the absence of an observable velocity reduction in unloaded Chalk is due to cementation

Discussion on development of polygonal fault systems: a test of hypotheses

We were surprised that James should criticize a test based on field data for not bearing some relation to physical reality, but infer that this comment relates to his later assertion that the polygonal fault systems concerned are inactive. We admit that we cannot prove the fault systems are active, but we think the available evidence strongly supports the assumption that they are

Dependence of sonic velocity on effective stress in North Sea Mesozoic mudstones

Overpressure estimation methods that use sonic velocity as a proxy for porosity only account for excess pressure due to undercompaction, so the influence of unloading processes in generating overpressure is ignored. We have used wireline log data and pore pressure measurements in mudstones of the Cromer Knoll Group and the Heather Formation in the North Sea to investigate whether velocity is sensitive to the contribution of unloading processes to observed overpressures. Our approach was to fit the data by four alternative linear relationships with sonic velocity as the dependent variable. The independent variables necessarily included porosity and vertical effective stress, and optionally the natural gamma log response and depth. Our preferred results are Vp=3746-3744phi+11.1sigmav-4.7gamma in the Cromer Knoll mudstones and Vp=4035-4269phi+8.6sigmav-5.5gamma in the Heather mudstones, for vertical effective stress over the range 10—30 MPa. The sensitivity of sonic velocity to vertical effective stress is, therefore, around 10 m s-1 MPa-1. This sensitivity should be sufficient to improve estimates of pore pressure while drilling by using sonic, density and natural gamma logs in combination. To make use of this sensitivity for pore pressure estimation, robust empirical relationships with vertical effective stress as the dependent variable would have to be established for the formations of interest

Microwave digestion of oils for platinum group and rare earth elements by ICP-MS.

no abstrac

Modelling Uncertainty in Pore Pressure Using Dynamic Bayesian Networks

Pore pressure prediction is vital when drilling a well, as unexpected overpressure can cause drilling challenges and uncontrolled hydrocarbon leakage. Predictions often use porosity-based techniques, relying on an idealised compaction trend and using a single wireline log as a proxy for porosity, ignoring the many sources of uncertainty and the system's multivariate nature. We propose a sequential dynamic Bayesian network (SDBN) as a solution to these issues. The SDBN models the quantities in the system (such as pressures, porosity, lithology, wireline logs etc.), capturing their joint behaviour using conditional probability distributions. A compaction model is central to the SDBN, relating porosity to vertical effective stress with uncertainty, so that the logic resembles that of the equivalent depth method. Given data, the probability distribution for each quantity is updated, so that instead of a single-valued prediction for pore pressure, the SDBN gives a full specification of uncertainty that takes into account the whole system, knowledge and data. We can use this to analyse the model's sensitivity to its parameters, through sensitivity analysis. The vertical correlation in the SDBN makes it suitable for real-time analysis of logging while drilling data. We show examples using real well data

Quantifying uncertainty in pore pressure estimation using Bayesian networks, with application to use of an offset well

Pore pressure estimation is a crucial yet difficult problem in the oil industry. If unexpected overpressure is encountered while drilling it can result in costly challenges and leaked hydrocarbons. Prediction methods often use empirical porosity-based methods such as the Eaton ratio method, requiring an idealised normal compaction trend and using a single wireline log as a proxy for porosity. Such methods do not account for the complex and multivariate nature of the system, or for the many sources of uncertainty. We propose a Bayesian network approach for modelling pore pressure, using conditional probability distributions to capture the joint behaviour of the quantities in the system (such as pressures, porosity, lithology, wireline logs). These distributions allow the inclusion of expert scientific information, for example a compaction model relating porosity to vertical effective stress and lithology is central to the model. The probability distribution for each quantity is updated in light of data, producing a prediction with uncertainty that takes into account the whole system, knowledge and data. Our method can be applied to a setting where an offset well is used to learn about the compaction behaviour of the planned well, and we demonstrate this with two wells from the Magnolia field