Geofluids

Volume 2017 (2017), Article ID 3179617, 12 pages

https://doi.org/10.1155/2017/3179617

## Real-Time Pore Pressure Detection: Indicators and Improved Methods

^{1}Geomech Energy, Houston, TX, USA^{2}North China Institute of Science and Technology, Yanjiao, Beijing, China

Correspondence should be addressed to Jincai Zhang and Shangxian Yin

Received 6 June 2017; Accepted 1 August 2017; Published 27 September 2017

Academic Editor: Fengshou Zhang

Copyright © 2017 Jincai Zhang and Shangxian Yin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### Abstract

High uncertainties may exist in the predrill pore pressure prediction in new prospects and deepwater subsalt wells; therefore, real-time pore pressure detection is highly needed to reduce drilling risks. The methods for pore pressure detection (the resistivity, sonic, and corrected -exponent methods) are improved using the depth-dependent normal compaction equations to adapt to the requirements of the real-time monitoring. A new method is proposed to calculate pore pressure from the connection gas or elevated background gas, which can be used for real-time pore pressure detection. The pore pressure detection using the logging-while-drilling, measurement-while-drilling, and mud logging data is also implemented and evaluated. Abnormal pore pressure indicators from the well logs, mud logs, and wellbore instability events are identified and analyzed to interpret abnormal pore pressures for guiding real-time drilling decisions. The principles for identifying abnormal pressure indicators are proposed to improve real-time pore pressure monitoring.

#### 1. Introduction

Many deep sedimentary formations have abnormal pore fluid pressures or overpressures. Abnormal pore pressures may cause serious drilling incidents (e.g., fluid influx, kicks, and even blowouts), if these abnormal pressures are not accurately predicted in predrill stage or detected in real-time drilling. Pore pressure analysis mainly includes three aspects, that is, predrill pore pressure prediction, real-time pore pressure detection, and postwell analysis. If predrill pore pressure prediction has big uncertainty, real-time pore pressure detection is needed to update predrill pore pressure prediction and advise drilling operations in real-time to adjust the mud weight to reduce drilling risks. Real-time pore pressure detection generally relies on the following available data for analyses and interpretations when they are available: logging-while-drilling (LWD), measurement-while-drilling (MWD), measured pore pressures, drilling parameters, and mud logging data.

#### 2. Methods of Real-Time Pore Pressure Detection

Different methods for pore pressure prediction have been proposed based on resistivity, sonic transit time (or interval velocity), and other petrophysical data (e.g., [1–10]). This paper will not focus on pore pressure prediction but on real-time detection. For real-time pore pressure detection, the pore pressure calculating methods need to be adapted to fit the real-time needs. In the following sections, methods for real-time pore pressure detection are implemented based on the shale properties with improved normal compaction trend lines.

##### 2.1. Resistivity Method

Resistivity logging data can be used to calculate pore pressure in shales. Eaton [2] proposed the following empirical equation to estimate pore pressure:where is the pore pressure gradient; is the normal pore pressure gradient;* R* is the measured shale resistivity; OBG is the overburden stress gradient; is the shale resistivity in the normal pressure condition;* n* is an exponent (may vary from 0.6 to 1.5 and normally ).

To use Eaton’s resistivity method for real-time pore pressure calculation, we need to determine the shale resistivity in the normal compaction condition. The following depth-dependent equation can be used to calculate the normal compaction trend (NCT):where is the resistivity value when ; is a compaction parameter; is the true vertical depth below the mudline (i.e., the surface level for onshore drilling or the sea floor in offshore drilling).

Determining the NCT is critically important for the real-time pore pressure detection. A case study [9] is used here to illustrate how to obtain the depth-dependent NCT parameters for real-time applications (Figure 1). We firstly calculate the NCT based on (2) and then estimate the pore pressure from Eaton’s equation (see (1)), as shown in Figure 1. The calculated pore pressure needs to be calibrated to the measured pore pressure data (e.g., the RTF in Figure 1). Based on this calibration we can adjust the parameters and . When the calculated pore pressure matches the measured pore pressure, it indicates that the NCT (i.e., the parameters and ) is applicable for the real-time pore pressure detection in this area. Certainly, this NCT is also needed to adjust based on the pore pressure indicators in the real-time drilling, which will be discussed later. Therefore, prior to the real-time pore pressure detection, a critical step is to determine the NCT from the offset wells. The formation resistivity may be affected by salinity, anisotropy, and temperature; therefore, corrections are needed when these effects are profound.