Determination of Petrophysical Parameters and Mud Filtrate Invasion Profile Using Joint Inversion of Induction Logging and Pressure Transient Measurements

2009 ◽  
Author(s):  
Lin Liang ◽  
Aria Abubakar ◽  
Tarek Habashy
Keyword(s):  
Joint Inversion ◽  
Pressure Transient ◽  
Petrophysical Parameters ◽  
Induction Logging ◽  
Mud Filtrate ◽  
Transient Measurements

Estimating petrophysical parameters and average mud-filtrate invasion rates using joint inversion of induction logging and pressure transient data

Geophysics ◽  
2011 ◽  
Vol 76 (2) ◽  
pp. E21-E34 ◽  
Author(s):  
Lin Liang ◽  
Aria Abubakar ◽  
Tarek M. Habashy
Keyword(s):  
Fluid Flow ◽  
Finite Difference ◽  
Water Saturation ◽  
Joint Inversion ◽  
Invasion Process ◽  
Invasion Rate ◽  
Pressure Transient ◽  
Induction Logging ◽  
Transient Data ◽  
Mud Filtrate

We introduce an inversion approach for determining the water-based mud-filtrate invasion profile, as well as the formation porosity and horizontal permeability, from the induction logging data. The inversion is constrained by a multiphase fluid flow simulator that simulates the mud-filtrate invasion process to obtain the spatial distributions of the water saturation and the salt concentration, which are in turn transformed into the formation resistivity using a resistivity-saturation formula. By ignoring the diffusion effect, we assume that the mud-filtrate invasion process is mainly convective so that it can be equivalently simulated by providing an average invasion rate and the duration of invasion. The average invasion rate can be directly inverted from the fluid-flow-constrained inversion of induction logging data. We also obtain the mud-filtrate invasion profile, which is consistent with the fluid flow physics. The reconstructed mud-filtrate invasion profile benefits the interpretation of the formation test. When the pressure transient data are available, this approach can be also used to jointly invert both induction logging data and pressure transient data to obtain the mud-filtrate invasion profile, as well as a parametric distribution of the TI-anisotropic formation permeability and porosity. Assuming a vertical well penetrating horizontal formations, the fluid flow problem is solved using an implicit black oil finite-difference simulator with brine tracking option based on a cylindrical, axially symmetric grid, whereas the response of the induction logging tool is simulated using a frequency-domain finite-difference solver based on a Cartesian grid. A Gauss-Newton inversion scheme using the multiplicative regularization technique is used for either the fluid-flow-constrained inversion or the joint inversion. The reliability of the inversion results depends on the accuracy of a priori knowledge of the reservoir, which needs to be confirmed via sensitivity analysis.

Joint petrophysical inversion of electromagnetic and full-waveform seismic data

Geophysics ◽  
2012 ◽  
Vol 77 (3) ◽  
pp. WA3-WA18 ◽  
Author(s):  
Guozhong Gao ◽  
Aria Abubakar ◽  
Tarek M. Habashy
Keyword(s):  
Bulk Modulus ◽  
Seismic Data ◽  
Joint Inversion ◽  
Large Percentage ◽  
Rock Matrix ◽  
Petrophysical Parameters ◽  
Electromagnetic Data ◽  
Full Waveform ◽  
Fluid Saturation

Accurate determination of reservoir petrophysical parameters is of great importance for reservoir monitoring and characterization. We developed a joint inversion approach for the direct estimation of in situ reservoir petrophysical parameters such as porosity and fluid saturations by jointly inverting electromagnetic and full-waveform seismic measurements. Full-waveform seismic inversions allow the exploitation of the full content of the data so that a more accurate geophysical model can be inferred. Electromagnetic data are linked to porosity and fluid saturations through Archie’s equations, whereas seismic data are linked to them through rock-physics fluid-substitution equations. For seismic modeling, we used an acoustic approximation. Sensitivity studies combined with inversion tests show that seismic data are mainly sensitive to porosity distribution, whereas electromagnetic data are more sensitive to fluid-saturation distribution. The separate inversion of electromagnetic or seismic data is highly nonunique and thus leads to great ambiguity in the determination of porosity and fluid saturations. In our approach, we used a Gauss-Newton algorithm equipped with the multiplicative regularization and proper data-weighting scheme. We tested the implemented joint petrophysical inversion method using various synthetic models for surface and crosswell measurements. We found that the joint inversion approach provides substantial advantage for an improved estimation of porosity and fluid-saturation distributions over the one obtained from the separate inversion of electromagnetic and seismic data. This advantage is achieved by significantly reducing the ambiguity on the determination of porosity and fluid saturations using multiphysics measurements. We also carried out a study on the effects of using inaccurate petrophysical transform parameters on the inversion results. Our study demonstrated that up to 20% errors in the saturation and porosity exponents in Archie’s equations do not cause significant errors in the inversion results. On the other hand, if the bulk modulus and density of the rock matrix have a large percentage of errors (i.e., more than 5%), the inversion results will be significantly degraded. However, if the density of the rock matrix has an error of less than 2%, the joint inversion can tolerate a large percentage of errors in the bulk modulus of the rock matrix.

scholarly journals Improve The Efficiency Of The Study Of Complex Reservoirs And Hydrocarbon Deposits - East Baghdad Field

2020 ◽  
Author(s):  
Sudad H Al-Obaidi
Keyword(s):  
Oil And Gas ◽  
Water Saturation ◽  
Well Logging ◽  
Well Testing ◽  
Petrophysical Parameters ◽  
Oil And Gas Fields ◽  
Hydrocarbon Fields ◽  
Gas Fields ◽  
Hydrocarbon Deposits

Practical value of this work consists in increasing the efficiency of exploration for oil and gas fields in Eastern Baghdad by optimizing and reducing the complex of well logging, coring, sampling and well testing of the formation beds and computerizing the data of interpretation to ensure the required accuracy and reliability of the determination of petrophysical parameters that will clarify and increase proven reserves of hydrocarbon fields in Eastern Baghdad. In order to calculate the most accurate water saturation values for each interval of Zubair formation, a specific modified form of Archie equation corresponding to this formation was developed.

Statistical determination of geophysical well log response functions

Geophysics ◽  
1983 ◽  
Vol 48 (11) ◽  
pp. 1525-1535 ◽  
Author(s):  
Eugene A. Nosal
Keyword(s):  
Power Spectrum ◽  
Response Function ◽  
System Response ◽  
General Terms ◽  
Induction Logging ◽  
Conductivity Profile ◽  
Statistical Determination ◽  
The One

The vertical response function of induction logging tools is shown to be derivable from a power spectrum analysis of the measurement. The vertical response function is the one‐dimensional sequence of weights that characterizes how the tool combines the rock conductivities along the borehole to form an output called the apparent conductivity; it is the system impulse response. The value of knowing this function lies in the possible use of filter theory to aid in data processing and interpretation. Two general notions establish the framework for the analysis. The first is that logging is a linear, convolutional operation. Second, the earth’s conductivity profile forms a stochastic process. The probabilistic component is fleshed out by reasonably based assumptions about the occurrence of bed boundaries and nature of conductivity changes across them. Brought together, these tenets create a characterization of the conductivity sequence that is not a stationary process, but rather is intrinsic, as defined in the discipline of geostatistics. Such a process is described by a variogram, and it is increments of the process that are stationary. The connection between the power spectrum of the measurement and the system response function is made when the convolutional model is merged with the conductivity process. Some examples of induction log functions are shown using these ideas. The analysis is presented in general terms for possibly wider application.

Determination of Producible Hydrocarbon Type and Oil Quality in Wells Drilled With Synthetic Oil-Based Muds

1999 ◽  
Vol 2 (02) ◽  
pp. 125-133 ◽  
Author(s):  
M.N. Hashem ◽  
E.C. Thomas ◽  
R.I. McNeil ◽  
Oliver Mullins
Keyword(s):  
Spectroscopic Data ◽  
Near Infrared ◽  
Data Set ◽  
Synthetic Oil ◽  
Open Hole ◽  
Invaded Zone ◽  
Mud Filtrate

Summary Determination of the type and quality of hydrocarbon fluid that can be produced from a formation prior to construction of production facilities is of equal economic importance to predicting the fluid rate and flowing pressure. We have become adept at making such estimates for formations drilled with water-based muds, using open-hole formation evaluation procedures. However, these standard open-hole methods are somewhat handicapped in wells drilled with synthetic oil-based mud because of the chemical and physical similarity between the synthetic oil-based filtrate and any producible oil that may be present. Also complicating the prediction is that in situ hydrocarbons will be miscibly displaced away from the wellbore by the invading oil-based mud filtrate, leaving little or no trace of the original hydrocarbon in the invaded zone. Thus, normal methods that sample fluids in the invaded zone will be of little use in predicting the in situ type and quality of hydrocarbons deeper in the formation. Only when we can pump significant volume of filtrate from the invaded zone to reconnect and sample the virgin fluids are we successful. However, since the in situ oil and filtrate are miscible, diffusion mixes the materials and blurs the interface; as mud filtrate is pumped from the formation into the borehole, the degree of contamination is greater than one might expect, and it is difficult to know when to stop pumping and start sampling. What level of filtrate contamination in the in situ fluid is tolerable? We propose a procedure for enhancing the value of the data derived from a particular open-hole wireline formation tester by quantitatively evaluating in real time the quality of the fluid being collected. The approach focuses on expanding the display of the spectroscopic data as a function of time on a more sensitive scale than has been used previously. This enhanced sensitivity allows one to confidently decide when in the pumping cycle to begin the sampling procedure. The study also utilizes laboratory determined PVT information on collected samples to form a data set that we use to correlate to the wireline derived spectroscopic data. The accuracy of these correlations has been verified with subsequent predictions and corroborated with laboratory measurements. Lastly, we provide a guideline for predicting the pump-out time needed to obtain a fluid sample of a pre-determined level of contamination when sampling conditions fall within our range of empirical data. Conclusions This empirical study validates that PVT quality hydrocarbon samples can be obtained from boreholes drilled with synthetic oil-based mud utilizing wireline formation testers deployed with downhole pump-out and optical analyzer modules. The data set for this study has the following boundary conditions: samples were obtained in the Gulf of Mexico area; the rock formations are unconsolidated to slightly consolidated, clean to slightly shaly sandstones; the in situ hydrocarbons and the synthetic oil-based mud filtrate have measurable differences in their visible and/or near infrared spectra. Specifically, this study demonstrates that during the pump-out phase of operations we can use the optical analyzer response to predict the API gravity and gas/oil ratio of the reservoir hydrocarbons prior to securing a downhole sample. Additionally, we can predict the pump out time required to obtain a reservoir sample with less than 10% mud filtrate contamination if we know or can estimate reservoir fluid viscosity and formation permeability. Extension of this method to other formations and locales should be possible using similar empirical correlation methodology. Introduction The high cost of offshore production facilities construction and deployment require accurate prediction of hydrocarbon PVT properties prior to fabrication. In the offshore Gulf of Mexico, one method to obtain a PVT quality hydrocarbon sample is to use a cased hole drill stem test. However, this procedure is usually quite costly due to the need for sand control. Shell has been an advocate of eliminating this costly step by utilizing openhole wireline test tools to obtain the PVT quality sample of the reservoir hydrocarbon. The success of this approach depends upon the availability of a wireline tool with a downhole pump that permits removal of the mud filtrate contamination prior to sampling the reservoir fluids, and a downhole fluid analyzer that can distinguish reservoir fluid from filtrate. One such tool is the Modular Formation Dynamics Tester (MDT).1 The optical fluid analyzer module of the MDT functions by subjecting the fluids being pumped to absorption spectroscopy in the visible and near-infrared (NIR) ranges. Interpretation of these spectra is the subject of this paper. Tool descriptions and basic theory of operations were presented in an earlier text.2 The concept of using visible and/or NIR spectroscopy to characterize the fluids being sampled while pumping is straightforward when there are measurable differences in the spectra of the mud filtrate and the reservoir hydrocarbons. As shown in Fig. 1, there are well known areas3,4 of the NIR spectrum (800-2000 nm) that are diagnostic of water and oil. The optical fluid analyzer module (OFA) of the MDT has channels tuned at 10 locations as indicated in Fig. 1, and thus the response in channels 6, 8, and 9 can be used to discern water from hydrocarbon. Another section of the OFA is designed to detect gas by measuring reflected polarized light from the pumped fluids, but we do not discuss its operation further except to say that it is a reliable gas indicator.

Tomographic Determination of the Upper Crustal Structure in Jiashi Strong Earthquake Swarm Region-Joint Inversion of Explosion and Earthquake Data

2007 ◽  
Vol 50 (5) ◽  
pp. 1265-1273
Author(s):  
Su-Zhen PAN ◽  
Xian-Kang ZHANG ◽  
Zhuo-Xin YANG ◽  
Cheng-Ke ZHANG ◽  
Jin-Ren ZHAO ◽  
...  
Keyword(s):  
Crustal Structure ◽  
Strong Earthquake ◽  
Joint Inversion ◽  
Earthquake Swarm ◽  
Jiashi Strong Earthquake Swarm ◽  
Earthquake Data
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